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research questions about impact of technology to students

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Does the impact of technology sustain students’ satisfaction, academic and functional performance: an analysis via interactive and self-regulated learning.

research questions about impact of technology to students

1. Introduction

  • This research examines technology acceptance using learning factors of digital learning.
  • This study presents an empirical analysis to observe the relationship of technology between self-regulated and interactive learning.
  • Students’ engagement with the technology via the mediating role of interactive and self-regulated learning can improve their satisfaction and academic and functional performance.

1.1. Preliminaries

1.2. learning factors: interactive and self-regulated learning, 1.3. students engaging in technology via interactive and self-regulated learning, 2. research model and methodology, 2.1. sample selection and data analysis, 2.2. measures, 2.3. descriptive statistics, 2.4. common method bias (cmb), 2.5. confirmatory factor analysis (cfa), 2.6. model validity and reliability, 2.7. correlation, 2.8. structural models, 3. discussion, limitations and future research, 4. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

  • Blundell, C.N.; Lee, K.-T.; Nykvist, S. Digital Learning in Schools: Conceptualizing the Challenges and Influences on Teacher s. Practice. J. Inf. Technol. Educ. Res. 2016 , 15 , 535–560. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Gemmill, L.E.; Peterson, M.J. Technology use among college students: Implications for student affairs professionals. NASPA J. 2006 , 43 , 280–300. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Chukwuedo, S.O.; Ogbuanya, T.C. Potential pathways for proficiency training in computer maintenance technology among prospective electronic technology education graduates. Educ. Train. 2020 , 62 , 100–115. [ Google Scholar ] [ CrossRef ]
  • Cropley, A. Creativity-focused Technology Education in the Age of Industry 4.0. Creativity Res. J. 2020 , 32 , 184–191. [ Google Scholar ] [ CrossRef ]
  • Hamada, M.; Hassan, M. Science, An Interactive Learning Environment for Information and Communication Theory. Eurasia J. Math. Sci. Technol. Educ. 2017 , 13 , 35–59. [ Google Scholar ]
  • Wang, S.; Claire, C.; Wei, C.; Richard, T.; Louise, Y.; Linda, S.; Feng, M. When adaptive learning is effective learning: Comparison of an adaptive learning system to teacher-led instruction. Interact. Learn. Environ. 2020 , 1–11. [ Google Scholar ] [ CrossRef ]
  • Wong, J.; Martine, B.; Dan, D.; Tim, V.D.Z.; Geert-Jan, H.; Fred, P. Supporting self-regulated learning in online learning environments and MOOCs: A systematic review. Int. J. Hum. Comput. Interact. 2019 , 35 , 356–373. [ Google Scholar ] [ CrossRef ]
  • Nichols, M. A theory for eLearning. J. Educ. Technol. Soc. 2003 , 6 , 1–10. [ Google Scholar ]
  • Sarrab, M.; Laila, E.; Hamza, A. Mobile learning (m-learning) and educational environments. Int. J. Distrib. Parallel Syst. 2012 , 3 , 31. [ Google Scholar ] [ CrossRef ]
  • Minka, T.; Picard, R. Interactive learning with a “Society of Models”. Pattern Recognit. 1997 , 30 , 565–581. [ Google Scholar ] [ CrossRef ]
  • Hamari, J. Do badges increase user activity? A field experiment on the effects of gamification. Comput. Hum. Behav. 2017 , 71 , 469–478. [ Google Scholar ] [ CrossRef ]
  • Graham, C.R. Blended learning systems. In The handbook of Blended Learning: Global Perspectives, Local Designs, 1 ; John Wiley & Sons: Hoboken, NJ, USA, 2006; pp. 3–21. [ Google Scholar ]
  • Jamei, E.; Mortimer, M.; Seyedmahmoudian, M.; Horan, B.; Stojcevski, A. Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities. Sustainability 2017 , 9 , 2006. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Ejdys, J.; Halicka, K. Sustainable Adaptation of New Technology—The Case of Humanoids Used for the Care of Older Adults. Sustainability 2018 , 10 , 3770. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Smith, J.F.; Skrbiš, Z. A social inequality of motivation? The relationship between beliefs about academic success and young people’s educational attainment. Br. Educ. Res. J. 2017 , 43 , 441–465. [ Google Scholar ] [ CrossRef ]
  • Mun, Y.Y.; Hwang, Y. Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. Int. J. Hum.-Comput. Stud. 2003 , 59 , 431–449. [ Google Scholar ]
  • Schneberger, S.; Amoroso, D.L.; Durfee, A. Factors that influence the performance of computer-based assessments: An extension of the technology acceptance model. J. Comput. Inf. Syst. 2008 , 48 , 74–90. [ Google Scholar ]
  • Navarro, O.; Sanchez-Verdejo, F.J.; Anguita, J.M.; Gonzalez, A.L. Motivation of University Students Towards the Use of Information and Communication Technologies and Their Relation to Learning Styles. Int. J. Emerg. Technol. Learn. 2020 , 15 , 202–218. [ Google Scholar ] [ CrossRef ]
  • Michailidis, N.; Kapravelos, E.; Tsiatsos, T. Interaction Analysis for Supporting Students’ Self-Regulation during Blog-based CSCL Activities. J. Educ. Technol. Soc. 2018 , 21 , 37–47. [ Google Scholar ]
  • Weidlich, J.; Bastiaens, T.J. Technology Matters—The Impact of Transactional Distance on Satisfaction in Online Distance Learning. Int. Rev. Res. Open Distrib. Learn. 2018 , 19 . [ Google Scholar ] [ CrossRef ]
  • Pardo, A.; Han, F.; Ellis, R.A. Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance. IEEE Trans. Learn. Technol. 2016 , 10 , 82–92. [ Google Scholar ] [ CrossRef ]
  • Millsap, R.E.; Kwok, O.-M. Evaluating the Impact of Partial Factorial Invariance on Selection in Two Populations. Psychol. Methods 2004 , 9 , 93–115. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Parameswaran, S.; Kishore, R.; Li, P. Within-study measurement invariance of the UTAUT instrument: An assessment with user technology engagement variables. Inf. Manag. 2015 , 52 , 317–336. [ Google Scholar ] [ CrossRef ]
  • Onwuegbuzie, A.; Collins, K. A Typology of Mixed Methods Sampling Designs in Social Science Research. Qual. Rep. 2015 , 12 , 281–316. [ Google Scholar ] [ CrossRef ]
  • Rast, P.; Zimprich, D.; Van Boxtel, M.; Jolles, J. Factor Structure and Measurement Invariance of the Cognitive Failures Questionnaire Across the Adult Life Span. Assessment 2009 , 16 , 145–158. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Plott, A.R. Web 2.0 in Blackboard learn: Mind the template. In Proceedings of the 38th Annual ACM SIGUCCS Fall Conference: Navigation and discovery, Norfolk, VA, USA, 24–27 October 2010; pp. 285–286. [ Google Scholar ]
  • Yakubu, N.M.; Dasuki, S.I.J. Factors affecting the adoption of e-learning technologies among higher education students in Nigeria: A structural equation modelling approach. Inf. Dev. 2019 , 35 , 492–502. [ Google Scholar ] [ CrossRef ]
  • Kuh, G.D. What We’re Learning About Student Engagement From NSSE: Benchmarks for Effective Educational Practices. Chang. Mag. High. Learn. 2003 , 35 , 24–32. [ Google Scholar ] [ CrossRef ]
  • Herrman, J.W. Keeping Their Attention: Innovative Strategies for Nursing Education. J. Contin. Educ. Nurs. 2011 , 42 , 449–456. [ Google Scholar ] [ CrossRef ]
  • Elliott, K.M.; Shin, D. Student Satisfaction: An alternative approach to assessing this important concept. J. High. Educ. Policy Manag. 2002 , 24 , 197–209. [ Google Scholar ] [ CrossRef ]
  • Farooq, M.S.; Chaudhry, A.H.; Shafiq, M.; Berhanu, G. Factors affecting students’ quality of academic performance: A case of secondary school level. J. Qual. Technol. Manag. 2011 , 7 , 1–14. [ Google Scholar ]
  • McCoy, S.W.; Effgen, S.K.; Chiarello, L.A.; Jeffries, L.M.; Tezanos, A.V. School-based physical therapy services and student functional performance at school. Dev. Med. Child Neurol. 2018 , 60 , 1140–1148. [ Google Scholar ] [ CrossRef ]
  • Harris, K.R.; Graham, S. Programmatic Intervention Research: Illustrations from the Evolution of Self-Regulated Strategy Development. Learn. Disabil. Q. 1999 , 22 , 251–262. [ Google Scholar ] [ CrossRef ]
  • Beck, C.A.; Campbell, M. Interactive learning in a multicultural setting. Christ. Educ. J. 2006 , 3 , 101–118. [ Google Scholar ] [ CrossRef ]
  • Davis, F.J. Perceived Usefulness, Perceived Ease of Use and Acceptance of Information Technology. MIS Q. 1989 , 13 , 319. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Seck, A. International technology diffusion and economic growth: Explaining the spillover benefits to developing countries. Struct. Chang. Econ. Dyn. 2012 , 23 , 437–451. [ Google Scholar ] [ CrossRef ]
  • Cooper, R.N.; Perez, C. Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Foreign Aff. 2003 , 82 , 148. [ Google Scholar ] [ CrossRef ]
  • Broadbent, J. Comparing online and blended learner’s self-regulated learning strategies and academic performance. Internet High. Educ. 2017 , 33 , 24–32. [ Google Scholar ] [ CrossRef ]
  • Loeffler, S.N.; Bohner, A.; Stumpp, J.; Limberger, M.F.; Gidion, G. Investigating and fostering self-regulated learning in higher education using interactive ambulatory assessment. Learn. Individ. Differ. 2019 , 71 , 43–57. [ Google Scholar ] [ CrossRef ]
  • Croxton, R.A. The role of interactivity in student satisfaction and persistence in online learning. J. Online Learn. Teach. 2014 , 10 , 314. [ Google Scholar ]
  • Chavoshi, A.; Hamidi, H. Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran. Telematics Informatics 2019 , 38 , 133–165. [ Google Scholar ] [ CrossRef ]
  • Dunn, T.; Kennedy, M. Technology Enhanced Learning in higher education; motivations, engagement and academic achievement. Comput. Educ. 2019 , 137 , 104–113. [ Google Scholar ] [ CrossRef ]
  • Edmondson, A.C.; Winslow, A.B.; Bohmer, R.M.J.; Pisano, G.P. Learning How and Learning What: Effects of Tacit and Codified Knowledge on Performance Improvement Following Technology Adoption. Decis. Sci. 2003 , 34 , 197–224. [ Google Scholar ] [ CrossRef ]
  • Tsai, T.-H.; Chang, H.-T.; Chen, Y.-J.; Chang, Y.-S. Determinants of user acceptance of a specific social platform for older adults: An empirical examination of user interface characteristics and behavioral intention. PLoS ONE 2017 , 12 , e0180102. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
  • Raman, A.; Thannimalai, R. Importance of Technology Leadership for Technology Integration: Gender and Professional Development Perspective. SAGE Open 2019 , 9 , 2158244019893707. [ Google Scholar ] [ CrossRef ]
  • Kuo, Y.-C.; Walker, A.E.; Schroder, K.E.; Belland, B.R. Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. Internet High. Educ. 2014 , 20 , 35–50. [ Google Scholar ] [ CrossRef ]
  • Li, S.; Yamaguchi, S.; Takada, J.-I. The Influence of Interactive Learning Materials on Self-Regulated Learning and Learning Satisfaction of Primary School Teachers in Mongolia. Sustainability 2018 , 10 , 1093. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Hillman, C.D.; Willis, D.J.; Gunawardena, C.N.J. Learner-interface interaction in distance education: An extension of medicontemporary models and strategies for practitioners. Am. J. Distance Educ. 1994 , 8 , 30–42. [ Google Scholar ] [ CrossRef ]
  • Cooper, K.; Ashley, M.; Brownell, S.E. Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept. J. Microbiol. Biol. Educ. 2017 , 18 . [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Doménech-Betoret, F.; Abellán-Roselló, L.; Gómez-Artiga, A. Self-Efficacy, Satisfaction, and Academic Achievement: The Mediator Role of Students’ Expectancy-Value Beliefs. Front. Psychol. 2017 , 8 , 1193. [ Google Scholar ] [ CrossRef ]
  • George, D. SPSS for Windows Step by Step: A Simple Study Guide and Reference, 17.0 Update, 10/e ; Pearson Education India: Noida, India, 2011. [ Google Scholar ]
  • Podsakoff, P.M.; Organ, D.W. Self-Reports in Organizational Research: Problems and Prospects. J. Manag. 1986 , 12 , 531–544. [ Google Scholar ] [ CrossRef ]
  • Kline, R.B. Principles and Practice of Structural Equation Modeling , 4th ed.; The Guilford Press: New York, NY, USA, 2011. [ Google Scholar ]
  • Memon, A.; An, Z.Y.; Memon, M.Q. Does financial availability sustain financial, innovative, and environmental performance? Relation via opportunity recognition. Corp. Soc. Responsib. Environ. Manag. 2019 , 27 , 562–575. [ Google Scholar ] [ CrossRef ]
  • Cronbach, L.J. Coefficient alpha and the internal structure of tests. Psychometrika 1951 , 16 , 297–334. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Fornell, C.; Larcker, D.F.J. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981 , 18 , 39–50. [ Google Scholar ] [ CrossRef ]
  • Kashada, A.; Li, H.; Koshadah, O. Analysis Approach to Identify Factors Influencing Digital Learning Technology Adoption and Utilization in Developing Countries. Int. J. Emerg. Technol. Learn. 2018 , 13 , 48–59. [ Google Scholar ] [ CrossRef ] [ Green Version ]
  • Shukla, T.; Pilani, I.B.; Dosaya, D.; Nirban, V.S.; Vavilala, M.P. Factors Extraction of Effective Teaching-Learning in Online and Conventional Classrooms. Int. J. Inf. Educ. Technol. 2020 , 10 , 422–427. [ Google Scholar ] [ CrossRef ]
  • Hamidi, H.; Jahanshaheefard, M. Essential factors for the application of education information system using mobile learning: A case study of students of the university of technology. Telemat. Inform. 2019 , 38 , 207–224. [ Google Scholar ] [ CrossRef ]
  • Henrie, C.R.; Halverson, L.; Graham, C. Measuring student engagement in technology-mediated learning: A review. Comput. Educ. 2015 , 90 , 36–53. [ Google Scholar ] [ CrossRef ]
  • Domina, T.; Renzulli, L.; Murray, B.; Garza, A.N.; Perez, L. Remote or Removed: Predicting Successful Engagement with Online Learning during COVID-19. Socius: Sociol. Res. a Dyn. World 2021 , 7 , 2378023120988200. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

NMinimumMaximumMeanStandard DeviationSkewnessKurtosis
TechnologyEngag3023.005.003.52760.423750.188−0.198
SelfRegLearning3023.005.003.64640.44792−0.134−0.182
InteractiveLearning3023.005.003.68540.453050.0570.125
AcademicPerform3023.005.003.16210.37378−0.0681.602
Satisfaction3023.004.003.15300.391100.197−1.546
FunctionalPerform3023.004.003.140.35291−1.3250.199
Variables and ItemsEstimatesSum of Squared Loadings ()AVE√AVECRCronbach α
te1<---TechEngag0.801 ***3.5340.5890.7670.8950.899
te2<---TechEngag0.675 ***
te3<---TechEngag0.864 ***
te4<---TechEngag0.707 ***
te5<---TechEngag0.731 ***
te6<---TechEngag0.81 ***
srl1<---SelfRegLearn0.696 ***3.160.6320.7950.8950.908
srl2<---SelfRegLearn0.827 ***
srl3<---SelfRegLearn0.845 ***
srl4<---SelfRegLearn0.849 ***
srl5<---SelfRegLearn0.745 ***
il1<---InterLearn0.89 ***2.0210.6740.8210.8590.844
il2<---InterLearn0.65 ***
il3<---InterLearn0.898 ***
ap1<---AcadPerform0.69 ***3.2080.5340.7310.8730.877
ap2<---AcadPerform0.809 ***
ap3<---AcadPerform0.725 ***
ap4<---AcadPerform0.771 ***
ap5<---AcadPerform0.633 ***
ap6<---AcadPerform0.746 ***
sa1<---Satisfac0.57 ***2.6860.5370.7330.85070.846
sa2<---Satisfac0.739 ***
sa3<---Satisfac0.872 ***
sa4<---Satisfac0.698 ***
sa5<---Satisfac0.753 ***
fp1<---FuncPerform0.702 ***2.4180.6050.7770.8580.854
fp2<---FuncPerform0.861 ***
fp3<---FuncPerform0.683 ***
fp4<---FuncPerform0.847 ***
TechnologyEngagSelfRegLearningInteractiveLearningAcademicPerformSatisfactionFunctionalPerform
TechnologyEngag1
SelfRegLearning0.226 **1
InteractiveLearning0.292 **0.659 **1
AcademicPerform0.451 **0.308 **0.351 **1
Satisfaction0.217 **0.218 **0.320 **0.0911
FunctionalPerform−0.0080.119 *0.211 **0.061−0.0371
Structure Model 1EstimateC.R.P
Satisfaction<---Education−0.042−0.9940.320
Satisfaction<---EthnicGroup0.0020.0710.943
AcademicPerform<---Education−0.008−0.2100.833
AcademicPerform<---EthnicGroup0.0110.5440.586
AcademicPerform<---Major−0.011−0.5540.580
FunctionalPerform<---Major0.0140.6260.532
FunctionalPerform<---EthnicGroup0.0150.7470.455
Satisfaction<---Age0.0551.4890.136
FunctionalPerform<---Age−0.013−0.3790.704
Satisfaction<---Major0.0120.5180.604
FunctionalPerform<---Education−0.001−0.0230.982
AcademicPerform<---Age0.0210.6430.521
Satisfaction<---TechnologyEngag0.1993.839***
FunctionalPerform<---TechnologyEngag0.000−0.0050.996
AcademicPerform<---TechnologyEngag0.3938.687***
Satisfaction<---Education−0.046−1.0780.281
Satisfaction<---EthnicGroup−0.007−0.2960.768
AcademicPerform<---Education−0.013−0.3240.746
AcademicPerform<---EthnicGroup−0.004−0.1920.848
AcademicPerform<---Major−0.015−0.6940.488
FunctionalPerform<---Major0.0180.8410.400
FunctionalPerform<---EthnicGroup0.0140.6890.491
Satisfaction<---Age0.0531.4380.151
FunctionalPerform<---Age−0.019−0.5480.583
Satisfaction<---Major0.0130.5500.582
FunctionalPerform<---Education−0.003−0.0680.946
AcademicPerform<---Age0.0240.6870.492
Satisfaction<---SelfRegLearning0.1873.828***
FunctionalPerform<---SelfRegLearning0.1042.3190.020
AcademicPerform<---SelfRegLearning0.2485.436***
Satisfaction<---Education−0.028−0.6850.493
Satisfaction<---EthnicGroup−0.006−0.2770.782
AcademicPerform<---Education0.0060.1610.872
AcademicPerform<---EthnicGroup−0.003−0.1320.895
AcademicPerform<---Major−0.019−0.8720.383
FunctionalPerform<---Major0.0180.8480.396
FunctionalPerform<---EthnicGroup0.0140.7090.478
Satisfaction<---Age0.0401.0980.272
FunctionalPerform<---Age−0.028−0.8410.400
Satisfaction<---Major0.0120.5130.608
FunctionalPerform<---Education0.0080.2130.831
AcademicPerform<---Age0.0120.3640.716
Satisfaction<---InteractiveLearning0.2725.782***
FunctionalPerform<---InteractiveLearning0.1723.942***
AcademicPerform<---InteractiveLearning0.2836.367***
Structure Model 4EstimateCRP
SelfRegLearning<---TechnologyEngag0.2394.026***
Satisfaction<---Education−0.045−1.0740.283
Satisfaction<---EthnicGroup−0.001−0.0630.950
AcademicPerform<---Education−0.011−0.3010.764
AcademicPerform<---EthnicGroup0.0070.3800.704
AcademicPerform<---Major−0.005−0.2580.797
FunctionalPerform<---Major0.0170.8090.418
FunctionalPerform<---EthnicGroup0.0130.6510.515
Satisfaction<---Age0.0481.3230.186
FunctionalPerform<---Age−0.018−0.5270.598
Satisfaction<---Major0.0180.7610.447
FunctionalPerform<---Education−0.003−0.0720.943
AcademicPerform<---Age0.0130.4080.683
Satisfaction<---TechnologyEngag0.1653.1470.002
FunctionalPerform<---TechnologyEngag−0.024−0.4990.618
AcademicPerform<---TechnologyEngag0.3547.829***
AcademicPerform<---SelfRegLearning0.1774.132***
Satisfaction<---SelfRegLearning0.1543.1180.002
FunctionalPerform<---SelfRegLearning0.1092.3660.018
InteractiveLearning<---TechnologyEngag0.3135.306***
Satisfaction<---Education−0.030−0.7290.466
Satisfaction<---EthnicGroup−0.002−0.0980.922
AcademicPerform<---Education0.0020.0640.949
AcademicPerform<---EthnicGroup0.0080.4030.687
AcademicPerform<---Major−0.009−0.4340.664
FunctionalPerform<---Major0.0160.7680.442
FunctionalPerform<---EthnicGroup0.0120.6230.533
Satisfaction<---Age0.0371.0440.296
FunctionalPerform<---Age−0.027−0.8120.417
Satisfaction<---Major0.0160.6880.492
FunctionalPerform<---Education0.0090.2320.817
AcademicPerform<---Age0.0060.2000.842
Satisfaction<---TechnologyEngag0.1262.4270.015
FunctionalPerform<---TechnologyEngag−0.057−1.1690.242
AcademicPerform<---TechnologyEngag0.3347.300***
AcademicPerform<---InteractiveLearning0.1944.522***
Satisfaction<---InteractiveLearning0.2384.892***
FunctionalPerform<---InteractiveLearning0.1884.111***
HypothesisDirect EffectIndirect EffectTotal Effect
SatisfactionTechnology engagement0.137 (0.019)0.081(0.000)0.218 (0.001)
Academic performanceTechnology engagement0.381 (0.001)0.074(0.000)0.455 (0.001)
Functional performanceTechnology engagement−0.068 (0.247)0.069(0.000)0.002 (0.991)
SatisfactionSelf-regulated learning0.006 (0.871)-0.006 (0.871)
Academic performanceSelf-regulated learning0.110 (0.049)-0.110 (0.049)
Functional performanceSelf-regulated learning−0.020 (0.773)-−0.020 (0.773)
Academic performanceInteractive learning0.168 (0.022)-0.168 (0.022)
SatisfactionInteractive learning0.273 (0.004)-0.273 (0.004)
Functional performanceInteractive learning0.253 (0.002)-0.253 (0.002)
Academic performanceAge0.017 (0.883)-0.017 (0.883)
SatisfactionAge0.090 (0.424)-0.090 (0.424)
Functional performanceAge−0.072 (0.411)-−0.072 (0.411)
Academic performanceEducation−0.005 (0.968)-−0.005 (0.968)
SatisfactionEducation−0.064 (0.545)-−0.064 (0.545)
Functional performanceEducation0.023 (0.771)-0.023 (0.771)
Academic performanceEthnic group0.018 (0.740)-0.018 (0.740)
SatisfactionEthnic group−0.005 (0.934)-−0.005 (0.934)
Functional performanceEthnic group0.035 (0.613)-0.035 (0.613)
Academic performanceMajor−0.016 (0.739)-−0.016 (0.739)
SatisfactionMajor0.038 (0.440)-0.038 (0.440)
Functional performanceMajor0.042 (0.515)-0.042 (0.515)
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Memon, M.Q.; Lu, Y.; Memon, A.R.; Memon, A.; Munshi, P.; Shah, S.F.A. Does the Impact of Technology Sustain Students’ Satisfaction, Academic and Functional Performance: An Analysis via Interactive and Self-Regulated Learning? Sustainability 2022 , 14 , 7226. https://doi.org/10.3390/su14127226

Memon MQ, Lu Y, Memon AR, Memon A, Munshi P, Shah SFA. Does the Impact of Technology Sustain Students’ Satisfaction, Academic and Functional Performance: An Analysis via Interactive and Self-Regulated Learning? Sustainability . 2022; 14(12):7226. https://doi.org/10.3390/su14127226

Memon, Muhammad Qasim, Yu Lu, Abdul Rehman Memon, Aasma Memon, Parveen Munshi, and Syed Farman Ali Shah. 2022. "Does the Impact of Technology Sustain Students’ Satisfaction, Academic and Functional Performance: An Analysis via Interactive and Self-Regulated Learning?" Sustainability 14, no. 12: 7226. https://doi.org/10.3390/su14127226

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

Inclusion criteriaExclusion criteria

• Published in 2005 or later

• Review and meta-analysis studies

• Formal education K-12

• Peer-reviewed articles

• Articles in English

• Reports from professional/international bodies

• Governmental reports

• Book chapters

• Ph.D. dissertations and theses

• Conference poster papers

• Conference papers without proceedings

• Resources on higher education

• Resources on pre-school education

• Individual studies

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

ImpactsReferences
Students
  Knowledge, skills, attitudes, and emotions
    • Learning gains from the use of ICTs across the curriculumEng, ; Balanskat et al., ; Liao et al., ; Tamim et al., ; Higgins et al., ; Chauhan, ; Sung et al., ; Schmid et al., ; Tamim et al., ; Zheng et al., ; Haßler et al., ; Kalati & Kim, ; Martinez et al., ; Talan et al., ; Panet al., ; Garzón & Acevedo, ; Garzón et al., ; Villena-Taranilla, et al., ; Coban et al.,
    • Positive learning gains from the use of ICTs in specific school subjects (e.g., mathematics, literacy, language, science)Arztmann et al., ; Villena-Taranilla, et al., ; Chen et al., ; Balanskat et al., ; Grgurović, et al., ; Friedel et al., ; Zheng et al., ; Savva et al., ; Kao, ; Higgins et al., ; Wen & Walters, ; Liao et al., ; Cheung & Slavin, ; Schwabe et al., ; Li & Ma, ; Verschaffel et al., ; Ran et al., ; Liao et al., ; Hillmayr et al., ; Kalemkuş & Kalemkuş, ; Lei et al., ; Condie & Munro, ; Chauhan, ; Bado, ; Wang et al., ; Pan et al.,
    • Positive learning gains for special needs students and low-achieving studentsEng, ; Balanskat et al., ; Punie et al., ; Koh,
    • Oportunities to develop a range of skills (e.g., subject-related skills, communication skills, negotiation skills, emotion control skills, organizational skills, critical thinking skills, creativity, metacognitive skills, life, and career skills)Balanskat et al., ; Fu, ; Tamim et al., ; Zheng et al., ; Higgins et al., ; Verschaffel et al., ; Su & Yang, ; Su et al., ; Lu et al., ; Liu et al., ; Quah & Ng, ; Fielding & Murcia, ; Tang et al., ; Haleem et al.,
    • Oportunities to develop digital skills (e.g., information skills, media skills, ICT skills)Zheng et al., ; Su & Yang, ; Lu et al., ; Su et al.,
    • Positive attitudes and behaviours towards ICTs, positive emotions (e.g., increased interest, motivation, attention, engagement, confidence, reduced anxiety, positive achievement emotions, reduction in bullying and cyberbullying)Balanskat et al., ; Schmid et al., ; Zheng et al., ; Fadda et al., ; Higgins et al., ; Chen et al., ; Lei et al., ; Arztmann et al., ; Su et al.,
  Learning experience
    • Enhance access to resourcesJewitt et al., ; Fu,
    • Opportunities to experience various learning practices (e.g., active learning, learner-centred learning, independent and personalized learning, collaborative learning, self-directed learning, self- and peer-review)Jewitt et al., ; Fu,
    • Improved access to teacher assessment and feedbackJewitt et al.,
Equality, inclusion, and social integration
    • Improved communication, functional skills, participation, self-esteem, and engagement of special needs studentsCondie & Munro, ; Baragash et al., ; Koh,
    • Enhanced social interaction for students in general and for students with learning difficultiesIstenic Starcic & Bagon,
    • Benefits for both girls and boysZheng et al., ; Arztmann et al.,
Teachers
  Professional practice
    • Development of digital competenceBalanskat et al.,
    • Positive attitudes and behaviours towards ICTs (e.g., increased confidence)Punie et al., ,
    • Formalized collaborative planning between teachersBalanskat et al.,
    • Improved reporting to parentsBalanskat et al.,
Teaching practice
    • Efficiency in lesson planning and preparationBalanskat et al.,
    • Facilitate assessment through the provision of immediate feedbackPunie et al.,
    • Improvements in the technical quality of testsPunie et al.,
    • New methods of testing specific skills (e.g., problem-solving skills, meta-cognitive skills)Punie et al.,
    • Successful content delivery and lessonsFriedel et al.,
    • Application of different instructional practices (e.g., scaffolding, synchronous collaborative learning, online learning, blended learning, hybrid learning)Friedel et al., ; Bado, ; Kazu & Yalçin, ; Ulum,
Administrators
  Data-based decision-making
    • Improved data-gathering processesBalanskat et al.,
    • Support monitoring and evaluation processes (e.g., attendance monitoring, financial management, assessment records)Condie & Munro,
Organizational processes
    • Access to learning resources via the creation of repositoriesCondie & Munro,
    • Information sharing between school staffCondie & Munro,
    • Smooth communications with external authorities (e.g., examination results)Punie et al.,
    • Efficient and successful examination management proceduresPunie et al.,
  Home-school communication
    • Support reporting to parentsCondie & Munro,
    • Improved flow of communication between the school and parents (e.g., customized and personalized communications)Escueta et al.,
School leaders
  Professional practice
    • Reduced headteacher isolationCondie & Munro,
    • Improved access to insights about practices for school improvementCondie & Munro,
Parents
  Home-school relationships
    • Improved home-school relationshipsZheng et al.,
    • Increased parental involvement in children’s school lifeEscueta et al.,

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Technologies/tools/practices/policiesReferences
ICT general – various types of technologies

Eng, (review)

Moran et al., (meta-analysis)

Balanskat et al., (report)

Punie et al., (review)

Fu, (review)

Higgins et al., (report)

Chauhan, (meta-analysis)

Schmid et al., (meta-analysis)

Grgurović et al., (meta-analysis)

Higgins et al., (meta-analysis)

Wen & Walters, (meta-analysis)

Cheung & Slavin, (meta-analysis)

Li & Ma, (meta-analysis)

Hillmayr et al., (meta-analysis)

Verschaffel et al., (systematic review)

Ran et al., (meta-analysis)

Fielding & Murcia, (systematic review)

Tang et al., (review)

Haleem et al., (review)

Condie & Munro, (review)

Underwood, (review)

Istenic Starcic & Bagon, (review)

Cussó-Calabuig et al., (systematic review)

Escueta et al. ( ) (review)

Archer et al., (meta-analysis)

Lee et al., (meta-analysis)

Delgado et al., (review)

Di Pietro et al., (report)

Practices/policies on schools’ digital transformation

Bingimlas, (review)

Hardman, (review)

Hattie, (synthesis of multiple meta-analysis)

Trucano, (book-Knowledge maps)

Ređep, (policy study)

Conrads et al, (report)

European Commission, (EU report)

Elkordy & Lovinelli, (book chapter)

Eurydice, (EU report)

Vuorikari et al., (JRC paper)

Sellar, (review)

European Commission, (EU report)

OECD, (international paper)

Computer-assisted instruction, computer simulations, activeboards, and web-based learning

Liao et al., (meta-analysis)

Tamim et al., (meta-analysis)

Çelik, (review)

Moran et al., (meta-analysis)

Eng, (review)

Learning platforms (LPs) (virtual learning environments, management information systems, communication technologies and information and resource sharing technologies)Jewitt et al., (report)
Mobile devices—touch screens (smart devices, tablets, laptops)

Sung et al., (meta-analysis and research synthesis)

Tamim et al., (meta-analysis)

Tamim et al., (systematic review and meta-analysis)

Zheng et al., (meta-analysis and research synthesis)

Haßler et al., (review)

Kalati & Kim, (systematic review)

Friedel et al., (meta-analysis and review)

Chen et al., (meta-analysis)

Schwabe et al., (meta-analysis)

Punie et al., (review)

Digital games (various types e.g., adventure, serious; various domains e.g., history, science)

Wang et al., (meta-analysis)

Arztmann et al., (meta-analysis)

Martinez et al., (systematic review)

Talan et al., (meta-analysis)

Pan et al., (systematic review)

Chen et al., (meta-analysis)

Kao, (meta-analysis)

Fadda et al., (meta-analysis)

Lu et al., (meta-analysis)

Lei et al., (meta-analysis)

Koh, (meta-analysis)

Bado, (review)

Augmented reality (AR)

Garzón & Acevedo, (meta-analysis)

Garzón et al., (meta-analysis and research synthesis)

Kalemkuş & Kalemkuş, (meta-analysis)

Baragash et al., (meta-analysis)

Virtual reality (VR)

Immersive virtual reality (IVR)

Villena-Taranilla et al., (meta-analysis)

Chen et al., (meta-analysis)

Coban et al., (meta-analysis)

Artificial intelligence (AI) and robotics

Su & Yang, (review)

Su et al., (meta review)

Online learning/elearning

Ulum, (meta-analysis)

Cheok & Wong, (review)

Blended learningGrgurović et al., (meta-analysis)
Synchronous parallel participationFriedel et al., (meta-analysis and review)
Electronic books/digital storytelling

Savva et al., (meta-analysis)

Quah & Ng, (systematic review)

Multimedia technologyLiu et al., (meta-analysis)
Hybrid learningKazu & Yalçin, (meta-analysis)

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

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Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

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Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

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  • Archer K, Savage R, Sanghera-Sidhu S, Wood E, Gottardo A, Chen V. Examining the effectiveness of technology use in classrooms: A tertiary meta-analysis. Computers & Education. 2014; 78 :140–149. doi: 10.1016/j.compedu.2014.06.001. [ CrossRef ] [ Google Scholar ]
  • Aromatario O, Van Hoye A, Vuillemin A, Foucaut AM, Pommier J, Cambon L. Using theory of change to develop an intervention theory for designing and evaluating behavior change SDApps for healthy eating and physical exercise: The OCAPREV theory. BMC Public Health. 2019; 19 (1):1–12. doi: 10.1186/s12889-019-7828-4. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Arztmann, M., Hornstra, L., Jeuring, J., & Kester, L. (2022). Effects of games in STEM education: A meta-analysis on the moderating role of student background characteristics. Studies in Science Education , 1-37. 10.1080/03057267.2022.2057732
  • Bado N. Game-based learning pedagogy: A review of the literature. Interactive Learning Environments. 2022; 30 (5):936–948. doi: 10.1080/10494820.2019.1683587. [ CrossRef ] [ Google Scholar ]
  • Balanskat, A. (2009). Study of the impact of technology in primary schools – Synthesis Report. Empirica and European Schoolnet. Retrieved 30 June 2022 from: https://erte.dge.mec.pt/sites/default/files/Recursos/Estudos/synthesis_report_steps_en.pdf
  • Balanskat, A. (2006). The ICT Impact Report: A review of studies of ICT impact on schools in Europe, European Schoolnet. Retrieved 30 June 2022 from:  https://en.unesco.org/icted/content/ict-impact-report-review-studies-ict-impact-schools-europe
  • Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT impact report.  European Schoolnet . Retrieved from: http://colccti.colfinder.org/sites/default/files/ict_impact_report_0.pdf
  • Balyer, A., & Öz, Ö. (2018). Academicians’ views on digital transformation in education. International Online Journal of Education and Teaching (IOJET), 5 (4), 809–830. Retrieved 30 June 2022 from  http://iojet.org/index.php/IOJET/article/view/441/295
  • Baragash RS, Al-Samarraie H, Moody L, Zaqout F. Augmented reality and functional skills acquisition among individuals with special needs: A meta-analysis of group design studies. Journal of Special Education Technology. 2022; 37 (1):74–81. doi: 10.1177/0162643420910413. [ CrossRef ] [ Google Scholar ]
  • Bates, A. W. (2015). Teaching in a digital age: Guidelines for designing teaching and learning . Open Educational Resources Collection . 6. Retrieved 30 June 2022 from: https://irl.umsl.edu/oer/6
  • Bingimlas KA. Barriers to the successful integration of ICT in teaching and learning environments: A review of the literature. Eurasia Journal of Mathematics, Science and Technology Education. 2009; 5 (3):235–245. doi: 10.12973/ejmste/75275. [ CrossRef ] [ Google Scholar ]
  • Blaskó Z, Costa PD, Schnepf SV. Learning losses and educational inequalities in Europe: Mapping the potential consequences of the COVID-19 crisis. Journal of European Social Policy. 2022; 32 (4):361–375. doi: 10.1177/09589287221091687. [ CrossRef ] [ Google Scholar ]
  • Bocconi S, Lightfoot M. Scaling up and integrating the selfie tool for schools' digital capacity in education and training systems: Methodology and lessons learnt. European Training Foundation. 2021 doi: 10.2816/907029,JRC123936. [ CrossRef ] [ Google Scholar ]
  • Brooks, D. C., & McCormack, M. (2020). Driving Digital Transformation in Higher Education . Retrieved 30 June 2022 from: https://library.educause.edu/-/media/files/library/2020/6/dx2020.pdf?la=en&hash=28FB8C377B59AFB1855C225BBA8E3CFBB0A271DA
  • Cachia, R., Chaudron, S., Di Gioia, R., Velicu, A., & Vuorikari, R. (2021). Emergency remote schooling during COVID-19, a closer look at European families. Retrieved 30 June 2022 from  https://publications.jrc.ec.europa.eu/repository/handle/JRC125787
  • Çelik B. The effects of computer simulations on students’ science process skills: Literature review. Canadian Journal of Educational and Social Studies. 2022; 2 (1):16–28. doi: 10.53103/cjess.v2i1.17. [ CrossRef ] [ Google Scholar ]
  • Chapman, C., & Sammons, P. (2013). School Self-Evaluation for School Improvement: What Works and Why? . CfBT Education Trust. 60 Queens Road, Reading, RG1 4BS, England.
  • Chauhan S. A meta-analysis of the impact of technology on learning effectiveness of elementary students. Computers & Education. 2017; 105 :14–30. doi: 10.1016/j.compedu.2016.11.005. [ CrossRef ] [ Google Scholar ]
  • Chen, Q., Chan, K. L., Guo, S., Chen, M., Lo, C. K. M., & Ip, P. (2022a). Effectiveness of digital health interventions in reducing bullying and cyberbullying: a meta-analysis. Trauma, Violence, & Abuse , 15248380221082090. 10.1177/15248380221082090 [ PubMed ]
  • Chen B, Wang Y, Wang L. The effects of virtual reality-assisted language learning: A meta-analysis. Sustainability. 2022; 14 (6):3147. doi: 10.3390/su14063147. [ CrossRef ] [ Google Scholar ]
  • Cheok ML, Wong SL. Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction. 2015; 8 (1):75–90. doi: 10.12973/iji.2015.816a. [ CrossRef ] [ Google Scholar ]
  • Cheung, A. C., & Slavin, R. E. (2011). The Effectiveness of Education Technology for Enhancing Reading Achievement: A Meta-Analysis. Center for Research and reform in Education .
  • Coban, M., Bolat, Y. I., & Goksu, I. (2022). The potential of immersive virtual reality to enhance learning: A meta-analysis. Educational Research Review , 100452. 10.1016/j.edurev.2022.100452
  • Condie, R., & Munro, R. K. (2007). The impact of ICT in schools-a landscape review. Retrieved 30 June 2022 from: https://oei.org.ar/ibertic/evaluacion/sites/default/files/biblioteca/33_impact_ict_in_schools.pdf
  • Conrads, J., Rasmussen, M., Winters, N., Geniet, A., Langer, L., (2017). Digital Education Policies in Europe and Beyond: Key Design Principles for More Effective Policies. Redecker, C., P. Kampylis, M. Bacigalupo, Y. Punie (ed.), EUR 29000 EN, Publications Office of the European Union, Luxembourg, 10.2760/462941
  • Costa P, Castaño-Muñoz J, Kampylis P. Capturing schools’ digital capacity: Psychometric analyses of the SELFIE self-reflection tool. Computers & Education. 2021; 162 :104080. doi: 10.1016/j.compedu.2020.104080. [ CrossRef ] [ Google Scholar ]
  • Cussó-Calabuig R, Farran XC, Bosch-Capblanch X. Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: A systematic review. Education and Information Technologies. 2018; 23 (5):2111–2139. doi: 10.1007/s10639-018-9706-6. [ CrossRef ] [ Google Scholar ]
  • Daniel SJ. Education and the COVID-19 pandemic. Prospects. 2020; 49 (1):91–96. doi: 10.1007/s11125-020-09464-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Delcker J, Ifenthaler D. Teachers’ perspective on school development at German vocational schools during the Covid-19 pandemic. Technology, Pedagogy and Education. 2021; 30 (1):125–139. doi: 10.1080/1475939X.2020.1857826. [ CrossRef ] [ Google Scholar ]
  • Delgado, A., Wardlow, L., O’Malley, K., & McKnight, K. (2015). Educational technology: A review of the integration, resources, and effectiveness of technology in K-12 classrooms. Journal of Information Technology Education Research , 14, 397. Retrieved 30 June 2022 from  http://www.jite.org/documents/Vol14/JITEv14ResearchP397-416Delgado1829.pdf
  • De Silva MJ, Breuer E, Lee L, Asher L, Chowdhary N, Lund C, Patel V. Theory of change: A theory-driven approach to enhance the Medical Research Council's framework for complex interventions. Trials. 2014; 15 (1):1–13. doi: 10.1186/1745-6215-15-267. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Di Pietro G, Biagi F, Costa P, Karpiński Z, Mazza J. The likely impact of COVID-19 on education: Reflections based on the existing literature and recent international datasets. Publications Office of the European Union; 2020. [ Google Scholar ]
  • Elkordy A, Lovinelli J. Competencies, Culture, and Change: A Model for Digital Transformation in K12 Educational Contexts. In: Ifenthaler D, Hofhues S, Egloffstein M, Helbig C, editors. Digital Transformation of Learning Organizations. Springer; 2020. pp. 203–219. [ Google Scholar ]
  • Eng TS. The impact of ICT on learning: A review of research. International Education Journal. 2005; 6 (5):635–650. [ Google Scholar ]
  • European Commission. (2020). Digital Education Action Plan 2021 – 2027. Resetting education and training for the digital age. Retrieved 30 June 2022 from  https://ec.europa.eu/education/sites/default/files/document-library-docs/deap-communication-sept2020_en.pdf
  • European Commission. (2019). 2 nd survey of schools: ICT in education. Objective 1: Benchmark progress in ICT in schools . Retrieved 30 June 2022 from: https://data.europa.eu/euodp/data/storage/f/2019-03-19T084831/FinalreportObjective1-BenchmarkprogressinICTinschools.pdf
  • Eurydice. (2019). Digital Education at School in Europe , Luxembourg: Publications Office of the European Union. Retrieved 30 June 2022 from: https://eacea.ec.europa.eu/national-policies/eurydice/content/digital-education-school-europe_en
  • Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2017). Education technology: An evidence-based review. Retrieved 30 June 2022 from  https://ssrn.com/abstract=3031695
  • Fadda D, Pellegrini M, Vivanet G, Zandonella Callegher C. Effects of digital games on student motivation in mathematics: A meta-analysis in K-12. Journal of Computer Assisted Learning. 2022; 38 (1):304–325. doi: 10.1111/jcal.12618. [ CrossRef ] [ Google Scholar ]
  • Fernández-Gutiérrez M, Gimenez G, Calero J. Is the use of ICT in education leading to higher student outcomes? Analysis from the Spanish Autonomous Communities. Computers & Education. 2020; 157 :103969. doi: 10.1016/j.compedu.2020.103969. [ CrossRef ] [ Google Scholar ]
  • Ferrari, A., Cachia, R., & Punie, Y. (2011). Educational change through technology: A challenge for obligatory schooling in Europe. Lecture Notes in Computer Science , 6964 , 97–110. Retrieved 30 June 2022  https://link.springer.com/content/pdf/10.1007/978-3-642-23985-4.pdf
  • Fielding, K., & Murcia, K. (2022). Research linking digital technologies to young children’s creativity: An interpretive framework and systematic review. Issues in Educational Research , 32 (1), 105–125. Retrieved 30 June 2022 from  http://www.iier.org.au/iier32/fielding-abs.html
  • Friedel, H., Bos, B., Lee, K., & Smith, S. (2013). The impact of mobile handheld digital devices on student learning: A literature review with meta-analysis. In Society for Information Technology & Teacher Education International Conference (pp. 3708–3717). Association for the Advancement of Computing in Education (AACE).
  • Fu JS. ICT in education: A critical literature review and its implications. International Journal of Education and Development Using Information and Communication Technology (IJEDICT) 2013; 9 (1):112–125. [ Google Scholar ]
  • Gaol FL, Prasolova-Førland E. Special section editorial: The frontiers of augmented and mixed reality in all levels of education. Education and Information Technologies. 2022; 27 (1):611–623. doi: 10.1007/s10639-021-10746-2. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Garzón J, Acevedo J. Meta-analysis of the impact of Augmented Reality on students’ learning gains. Educational Research Review. 2019; 27 :244–260. doi: 10.1016/j.edurev.2019.04.001. [ CrossRef ] [ Google Scholar ]
  • Garzón, J., Baldiris, S., Gutiérrez, J., & Pavón, J. (2020). How do pedagogical approaches affect the impact of augmented reality on education? A meta-analysis and research synthesis. Educational Research Review , 100334. 10.1016/j.edurev.2020.100334
  • Grgurović M, Chapelle CA, Shelley MC. A meta-analysis of effectiveness studies on computer technology-supported language learning. ReCALL. 2013; 25 (2):165–198. doi: 10.1017/S0958344013000013. [ CrossRef ] [ Google Scholar ]
  • Haßler B, Major L, Hennessy S. Tablet use in schools: A critical review of the evidence for learning outcomes. Journal of Computer Assisted Learning. 2016; 32 (2):139–156. doi: 10.1111/jcal.12123. [ CrossRef ] [ Google Scholar ]
  • Haleem A, Javaid M, Qadri MA, Suman R. Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers. 2022; 3 :275–285. doi: 10.1016/j.susoc.2022.05.004. [ CrossRef ] [ Google Scholar ]
  • Hardman J. Towards a pedagogical model of teaching with ICTs for mathematics attainment in primary school: A review of studies 2008–2018. Heliyon. 2019; 5 (5):e01726. doi: 10.1016/j.heliyon.2019.e01726. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Hattie J, Rogers HJ, Swaminathan H. The role of meta-analysis in educational research. In: Reid AD, Hart P, Peters MA, editors. A companion to research in education. Springer; 2014. pp. 197–207. [ Google Scholar ]
  • Hattie J. Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge. 2008 doi: 10.4324/9780203887332. [ CrossRef ] [ Google Scholar ]
  • Higgins S, Xiao Z, Katsipataki M. The impact of digital technology on learning: A summary for the education endowment foundation. Education Endowment Foundation and Durham University; 2012. [ Google Scholar ]
  • Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research , 57(2), 283-319.
  • Hillmayr D, Ziernwald L, Reinhold F, Hofer SI, Reiss KM. The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education. 2020; 153 (1038):97. doi: 10.1016/j.compedu.2020.103897. [ CrossRef ] [ Google Scholar ]
  • Istenic Starcic A, Bagon S. ICT-supported learning for inclusion of people with special needs: Review of seven educational technology journals, 1970–2011. British Journal of Educational Technology. 2014; 45 (2):202–230. doi: 10.1111/bjet.12086. [ CrossRef ] [ Google Scholar ]
  • Jewitt C, Clark W, Hadjithoma-Garstka C. The use of learning platforms to organise learning in English primary and secondary schools. Learning, Media and Technology. 2011; 36 (4):335–348. doi: 10.1080/17439884.2011.621955. [ CrossRef ] [ Google Scholar ]
  • JISC. (2020). What is digital transformation?.  Retrieved 30 June 2022 from: https://www.jisc.ac.uk/guides/digital-strategy-framework-for-university-leaders/what-is-digital-transformation
  • Kalati, A. T., & Kim, M. S. (2022). What is the effect of touchscreen technology on young children’s learning?: A systematic review. Education and Information Technologies , 1-19. 10.1007/s10639-021-10816-5
  • Kalemkuş, J., & Kalemkuş, F. (2022). Effect of the use of augmented reality applications on academic achievement of student in science education: Meta-analysis review. Interactive Learning Environments , 1-18. 10.1080/10494820.2022.2027458
  • Kao C-W. The effects of digital game-based learning task in English as a foreign language contexts: A meta-analysis. Education Journal. 2014; 42 (2):113–141. [ Google Scholar ]
  • Kampylis P, Punie Y, Devine J. Promoting effective digital-age learning - a European framework for digitally competent educational organisations. JRC Technical Reports. 2015 doi: 10.2791/54070. [ CrossRef ] [ Google Scholar ]
  • Kazu IY, Yalçin CK. Investigation of the effectiveness of hybrid learning on academic achievement: A meta-analysis study. International Journal of Progressive Education. 2022; 18 (1):249–265. doi: 10.29329/ijpe.2022.426.14. [ CrossRef ] [ Google Scholar ]
  • Koh C. A qualitative meta-analysis on the use of serious games to support learners with intellectual and developmental disabilities: What we know, what we need to know and what we can do. International Journal of Disability, Development and Education. 2022; 69 (3):919–950. doi: 10.1080/1034912X.2020.1746245. [ CrossRef ] [ Google Scholar ]
  • König J, Jäger-Biela DJ, Glutsch N. Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education. 2020; 43 (4):608–622. doi: 10.1080/02619768.2020.1809650. [ CrossRef ] [ Google Scholar ]
  • Lawrence JE, Tar UA. Factors that influence teachers’ adoption and integration of ICT in teaching/learning process. Educational Media International. 2018; 55 (1):79–105. doi: 10.1080/09523987.2018.1439712. [ CrossRef ] [ Google Scholar ]
  • Lee, S., Kuo, L. J., Xu, Z., & Hu, X. (2020). The effects of technology-integrated classroom instruction on K-12 English language learners’ literacy development: A meta-analysis. Computer Assisted Language Learning , 1-32. 10.1080/09588221.2020.1774612
  • Lei, H., Chiu, M. M., Wang, D., Wang, C., & Xie, T. (2022a). Effects of game-based learning on students’ achievement in science: a meta-analysis. Journal of Educational Computing Research . 10.1177/07356331211064543
  • Lei H, Wang C, Chiu MM, Chen S. Do educational games affect students' achievement emotions? Evidence from a meta-analysis. Journal of Computer Assisted Learning. 2022; 38 (4):946–959. doi: 10.1111/jcal.12664. [ CrossRef ] [ Google Scholar ]
  • Liao YKC, Chang HW, Chen YW. Effects of computer application on elementary school student's achievement: A meta-analysis of students in Taiwan. Computers in the Schools. 2007; 24 (3–4):43–64. doi: 10.1300/J025v24n03_04. [ CrossRef ] [ Google Scholar ]
  • Li Q, Ma X. A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review. 2010; 22 (3):215–243. doi: 10.1007/s10648-010-9125-8. [ CrossRef ] [ Google Scholar ]
  • Liu, M., Pang, W., Guo, J., & Zhang, Y. (2022). A meta-analysis of the effect of multimedia technology on creative performance. Education and Information Technologies , 1-28. 10.1007/s10639-022-10981-1
  • Lu Z, Chiu MM, Cui Y, Mao W, Lei H. Effects of game-based learning on students’ computational thinking: A meta-analysis. Journal of Educational Computing Research. 2022 doi: 10.1177/07356331221100740. [ CrossRef ] [ Google Scholar ]
  • Martinez L, Gimenes M, Lambert E. Entertainment video games for academic learning: A systematic review. Journal of Educational Computing Research. 2022 doi: 10.1177/07356331211053848. [ CrossRef ] [ Google Scholar ]
  • Mayne J. Useful theory of change models. Canadian Journal of Program Evaluation. 2015; 30 (2):119–142. doi: 10.3138/cjpe.230. [ CrossRef ] [ Google Scholar ]
  • Moran J, Ferdig RE, Pearson PD, Wardrop J, Blomeyer RL., Jr Technology and reading performance in the middle-school grades: A meta-analysis with recommendations for policy and practice. Journal of Literacy Research. 2008; 40 (1):6–58. doi: 10.1080/10862960802070483. [ CrossRef ] [ Google Scholar ]
  • OECD. (2015). Students, Computers and Learning: Making the Connection . PISA, OECD Publishing, Paris. Retrieved from: 10.1787/9789264239555-en
  • OECD. (2021). OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. Retrieved from: https://www.oecd-ilibrary.org/education/oecd-digital-education-outlook-2021_589b283f-en
  • Pan Y, Ke F, Xu X. A systematic review of the role of learning games in fostering mathematics education in K-12 settings. Educational Research Review. 2022; 36 :100448. doi: 10.1016/j.edurev.2022.100448. [ CrossRef ] [ Google Scholar ]
  • Pettersson F. Understanding digitalization and educational change in school by means of activity theory and the levels of learning concept. Education and Information Technologies. 2021; 26 (1):187–204. doi: 10.1007/s10639-020-10239-8. [ CrossRef ] [ Google Scholar ]
  • Pihir, I., Tomičić-Pupek, K., & Furjan, M. T. (2018). Digital transformation insights and trends. In Central European Conference on Information and Intelligent Systems (pp. 141–149). Faculty of Organization and Informatics Varazdin. Retrieved 30 June 2022 from https://www.proquest.com/conference-papers-proceedings/digital-transformation-insights-trends/docview/2125639934/se-2
  • Punie, Y., Zinnbauer, D., & Cabrera, M. (2006). A review of the impact of ICT on learning. Working Paper prepared for DG EAC. Retrieved 30 June 2022 from: http://www.eurosfaire.prd.fr/7pc/doc/1224678677_jrc47246n.pdf
  • Quah CY, Ng KH. A systematic literature review on digital storytelling authoring tool in education: January 2010 to January 2020. International Journal of Human-Computer Interaction. 2022; 38 (9):851–867. doi: 10.1080/10447318.2021.1972608. [ CrossRef ] [ Google Scholar ]
  • Ran H, Kim NJ, Secada WG. A meta-analysis on the effects of technology's functions and roles on students' mathematics achievement in K-12 classrooms. Journal of computer assisted learning. 2022; 38 (1):258–284. doi: 10.1111/jcal.12611. [ CrossRef ] [ Google Scholar ]
  • Ređep, N. B. (2021). Comparative overview of the digital preparedness of education systems in selected CEE countries. Center for Policy Studies. CEU Democracy Institute .
  • Rott, B., & Marouane, C. (2018). Digitalization in schools–organization, collaboration and communication. In Digital Marketplaces Unleashed (pp. 113–124). Springer, Berlin, Heidelberg.
  • Savva M, Higgins S, Beckmann N. Meta-analysis examining the effects of electronic storybooks on language and literacy outcomes for children in grades Pre-K to grade 2. Journal of Computer Assisted Learning. 2022; 38 (2):526–564. doi: 10.1111/jcal.12623. [ CrossRef ] [ Google Scholar ]
  • Schmid RF, Bernard RM, Borokhovski E, Tamim RM, Abrami PC, Surkes MA, Wade CA, Woods J. The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education. 2014; 72 :271–291. doi: 10.1016/j.compedu.2013.11.002. [ CrossRef ] [ Google Scholar ]
  • Schuele CM, Justice LM. The importance of effect sizes in the interpretation of research: Primer on research: Part 3. The ASHA Leader. 2006; 11 (10):14–27. doi: 10.1044/leader.FTR4.11102006.14. [ CrossRef ] [ Google Scholar ]
  • Schwabe, A., Lind, F., Kosch, L., & Boomgaarden, H. G. (2022). No negative effects of reading on screen on comprehension of narrative texts compared to print: A meta-analysis. Media Psychology , 1-18. 10.1080/15213269.2022.2070216
  • Sellar S. Data infrastructure: a review of expanding accountability systems and large-scale assessments in education. Discourse: Studies in the Cultural Politics of Education. 2015; 36 (5):765–777. doi: 10.1080/01596306.2014.931117. [ CrossRef ] [ Google Scholar ]
  • Stock WA. Systematic coding for research synthesis. In: Cooper H, Hedges LV, editors. The handbook of research synthesis, 236. Russel Sage; 1994. pp. 125–138. [ Google Scholar ]
  • Su, J., Zhong, Y., & Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence , 100065. 10.1016/j.caeai.2022.100065
  • Su J, Yang W. Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence. 2022; 3 :100049. doi: 10.1016/j.caeai.2022.100049. [ CrossRef ] [ Google Scholar ]
  • Sung YT, Chang KE, Liu TC. The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis. Computers & Education. 2016; 94 :252–275. doi: 10.1016/j.compedu.2015.11.008. [ CrossRef ] [ Google Scholar ]
  • Talan T, Doğan Y, Batdı V. Efficiency of digital and non-digital educational games: A comparative meta-analysis and a meta-thematic analysis. Journal of Research on Technology in Education. 2020; 52 (4):474–514. doi: 10.1080/15391523.2020.1743798. [ CrossRef ] [ Google Scholar ]
  • Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational research, 81 (1), 4–28. Retrieved 30 June 2022 from 10.3102/0034654310393361
  • Tamim, R. M., Borokhovski, E., Pickup, D., Bernard, R. M., & El Saadi, L. (2015). Tablets for teaching and learning: A systematic review and meta-analysis. Commonwealth of Learning. Retrieved from: http://oasis.col.org/bitstream/handle/11599/1012/2015_Tamim-et-al_Tablets-for-Teaching-and-Learning.pdf
  • Tang C, Mao S, Xing Z, Naumann S. Improving student creativity through digital technology products: A literature review. Thinking Skills and Creativity. 2022; 44 :101032. doi: 10.1016/j.tsc.2022.101032. [ CrossRef ] [ Google Scholar ]
  • Tolani-Brown, N., McCormac, M., & Zimmermann, R. (2011). An analysis of the research and impact of ICT in education in developing country contexts. In ICTs and sustainable solutions for the digital divide: Theory and perspectives (pp. 218–242). IGI Global.
  • Trucano, M. (2005). Knowledge Maps: ICTs in Education. Washington, DC: info Dev / World Bank. Retrieved 30 June 2022 from  https://files.eric.ed.gov/fulltext/ED496513.pdf
  • Ulum H. The effects of online education on academic success: A meta-analysis study. Education and Information Technologies. 2022; 27 (1):429–450. doi: 10.1007/s10639-021-10740-8. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Underwood, J. D. (2009). The impact of digital technology: A review of the evidence of the impact of digital technologies on formal education. Retrieved 30 June 2022 from: http://dera.ioe.ac.uk/id/eprint/10491
  • Verschaffel, L., Depaepe, F., & Mevarech, Z. (2019). Learning Mathematics in metacognitively oriented ICT-Based learning environments: A systematic review of the literature. Education Research International , 2019 . 10.1155/2019/3402035
  • Villena-Taranilla R, Tirado-Olivares S, Cózar-Gutiérrez R, González-Calero JA. Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis. Educational Research Review. 2022; 35 :100434. doi: 10.1016/j.edurev.2022.100434. [ CrossRef ] [ Google Scholar ]
  • Voogt J, Knezek G, Cox M, Knezek D, ten Brummelhuis A. Under which conditions does ICT have a positive effect on teaching and learning? A call to action. Journal of Computer Assisted Learning. 2013; 29 (1):4–14. doi: 10.1111/j.1365-2729.2011.00453.x. [ CrossRef ] [ Google Scholar ]
  • Vuorikari, R., Punie, Y., & Cabrera, M. (2020). Emerging technologies and the teaching profession: Ethical and pedagogical considerations based on near-future scenarios  (No. JRC120183). Joint Research Centre. Retrieved 30 June 2022 from: https://publications.jrc.ec.europa.eu/repository/handle/JRC120183
  • Wang LH, Chen B, Hwang GJ, Guan JQ, Wang YQ. Effects of digital game-based STEM education on students’ learning achievement: A meta-analysis. International Journal of STEM Education. 2022; 9 (1):1–13. doi: 10.1186/s40594-022-00344-0. [ CrossRef ] [ Google Scholar ]
  • Wen X, Walters SM. The impact of technology on students’ writing performances in elementary classrooms: A meta-analysis. Computers and Education Open. 2022; 3 :100082. doi: 10.1016/j.caeo.2022.100082. [ CrossRef ] [ Google Scholar ]
  • Zheng B, Warschauer M, Lin CH, Chang C. Learning in one-to-one laptop environments: A meta-analysis and research synthesis. Review of Educational Research. 2016; 86 (4):1052–1084. doi: 10.3102/0034654316628645. [ CrossRef ] [ Google Scholar ]
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New Educational Technologies and Their Impact on Students' Well-being and Inclusion Process

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In the new millennium, education is rapidly changing due to the more and more pervasive use of technology to support teaching and learning. New Information and Communication Technologies (ICTs), such as internet, wikis, blogs, search engines, emails and instant messaging require new literacy frameworks and ...

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New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

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Technology can close achievement gaps, improve learning.

The report recommends one-to-one computer access for students for more effective learning (Photo: iStock)

As school districts around the country consider investments in technology in an effort to improve student outcomes, a new report from the Alliance for Excellent Education and the Stanford Center for Opportunity Policy in Education (SCOPE) finds that technology - when implemented properly -can produce significant gains in student achievement and boost engagement, particularly among students most at risk.

“This report makes clear that districts must have a plan in place for how they will use technology before they make a purchase,” said Bob Wise, president of the Alliance for Excellent Education and former governor of West Virginia. “It also underscores that replacing teachers with technology is not a successful formula. Instead, strong gains in achievement occur by pairing technology with classroom teachers who provide real-time support and encouragement to underserved students.”

Written by Professors Linda Darling-Hammond and Shelley Goldman at the Stanford Graduate School of Education and doctoral student Molly B. Zielezinski, the report is based on a review of more than 70 recent research studies and provides concrete examples of classroom environments in which technology has made a positive difference in the learning outcomes of students at risk of failing courses and dropping out.

Specifically, it identifies three important components to successfully using technology with at-risk students: interactive learning, use of technology to explore and create rather than to “drill and kill,” and the right blend of teachers and technology.

The report, Using Technology to Support At-Risk Students’ Learning , also identifies significant disparities in technology access and implementation between affluent and low-income schools. First, low-income teens and students of color are noticeably less likely to own computers and use the internet than their peers. Because of their students’ lack of access, teachers in high-poverty schools were more than twice likely (56 percent versus 21 percent) to say that their students’ lack of access to technology was a challenge in their classrooms. More dramatically, only 3 percent of teachers in high-poverty schools said that their students have the digital tools necessary to complete homework assignments, compared to 52 percent of teachers in more affluent schools.

Secondly, applications of technology in low-income schools typically involves a “drill and kill” approach in which computers take over for teachers and students are presented with information they are expected to memorize and are then tested on with multiple-choice questions. In more affluent schools, however, students tend to be immersed in more interactive environments in which material is customized based on students’ learning needs and teachers supplement instruction with technology to explain concepts, coordinate student discussion, and stimulate high-level thinking.

“When given access to appropriate technology used in thoughtful ways, all students—regardless of their respective backgrounds—can make substantial gains in learning and technological readiness,” said Darling-Hammond, the faculty director of SCOPE. “Unfortunately, applications of technology in schools serving the most disadvantaged students are frequently compromised by the same disparities in dollars, teachers, and instructional services that typically plague these schools. These disparities are compounded by the lack of access to technology in these students’ homes.”

The report includes several recommendations that could expand the use and impact of technology among at-risk high school youth:

  • Technology access policies should aim for one-to-one computer access;
  • Technology access policies should ensure that speedy internet connections are available;
  • States, districts, and schools should favor technology designed to promote high levels of interactivity and engagement and make data available in multiple forms;
  • Curriculum and instruction plans should enable students to use technology to create content as well as learn material; and
  • Policymakers and educators should plan for “blended” learning environments, characterized by significant levels of teacher support and opportunities for interactions among students, as companions to technology use.

The report cautions that its recommendations must be accompanied by adequate professional learning opportunities for teachers on how to use the technology and pedagogies that are recommended, including technical assistance to help educators manage the hardware, software and connections to the Internet.

Darling-Hammond and Zielezinski joined Tom Murray, the Alliance’s state and district digital learning director, for a video webinar to discuss the report’s findings on Sept. 10. For archived video, please visit:   http://all4ed.org/webinar-event/sep-10-2014/ .

This story was written by the communications staff at the Alliance for Excellent Education in Washington, DC, and is also posted at  www.all4ed.org .

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How to Investigate the Impact of Technology on Student Learning

The classroom, once a static space defined by chalkboards and textbooks, is undergoing a dramatic transformation. Technology, with its boundless potential, has infiltrated every corner of education, sparking both excitement and debate about its true impact on student learning. This comprehensive guide aims to equip educators, researchers, and policymakers with the tools and knowledge to critically investigate this complex landscape, moving beyond simplistic narratives of “good” or “bad” to uncover nuanced insights.

Section 1: Framing the Inquiry – Key Considerations and Methodological Approaches

Before embarking on an investigation, it’s crucial to establish a solid foundation:

1.1 Defining the Scope: Specificity is Key

“Technology” is a vast umbrella term encompassing everything from simple calculators to immersive virtual reality. Narrowing down your focus is essential for a meaningful investigation.

  • Instead of “Impact of Technology on Literacy,” consider “The Effect of Digital Storytelling Software on Narrative Writing Skills in Grade 5 Students.”
  • Rather than “Technology and Student Engagement,” delve into “The Relationship Between Gamified Math Apps and Motivation in Middle School Algebra Classes.”

1.2 Identifying Relevant Variables

Consider the multitude of factors that can influence your findings:

  • Technological Variables: Type of technology, frequency of use, mode of integration (supplemental vs. core), access and digital equity issues.
  • Student Variables: Age, grade level, prior experience with technology, learning styles, socioeconomic background.
  • Teacher Variables: Technological proficiency, pedagogical approaches, attitudes towards technology integration, professional development opportunities.
  • Contextual Variables: School demographics, technological infrastructure, curriculum alignment, community support.

1.3 Selecting Appropriate Methodologies

Your research questions should dictate your methodological choices. Consider a mixed-methods approach to capture both quantitative and qualitative data:

  • Standardized tests: Measure academic achievement in specific subject areas (e.g., comparing pre- and post-test scores after implementing a math learning software).
  • Surveys: Gather large-scale data on student perceptions, attitudes, and technology use habits (e.g., surveying students on their confidence levels using online research databases).
  • Usage data analysis: Track student interactions with educational software or platforms to understand learning patterns and engagement (e.g., analyzing time spent on different modules, frequency of feedback requests).
  • Observations: Conduct classroom observations to capture authentic student-technology interactions, teacher practices, and the overall learning environment.
  • Interviews: Gather in-depth perspectives from students, teachers, and administrators about their experiences, challenges, and perceived benefits of technology use (e.g., interviewing students about how they use technology for collaborative projects).
  • Focus groups: Facilitate discussions among stakeholders to explore shared experiences and gather diverse viewpoints.
  • Case studies: Conduct in-depth investigations of specific classrooms or schools to provide rich, contextualized insights into the impact of technology.

Section 2: Exploring Key Areas of Impact – A Framework for Investigation

This section outlines key areas where technology’s influence on student learning is particularly pronounced:

2.1 Academic Achievement and Skill Development

  • Research Focus: Does technology use lead to improved academic performance? Are there specific technologies or pedagogical approaches that yield greater gains in certain subject areas or skill sets?
  • Compare standardized test scores of students using digital literacy programs to those using traditional methods.
  • Analyze student writing samples for evidence of improved grammar, vocabulary, and critical thinking skills after using online writing tools.
  • Assess problem-solving abilities in STEM fields by examining student performance on simulations or game-based learning platforms.

2.2 Student Engagement and Motivation

  • Research Focus: Does technology enhance student engagement and motivation in the learning process? Can it create more interactive and personalized learning experiences?

Investigative Examples:

  • Observe student participation levels, on-task behavior, and enthusiasm in classrooms using different technology-integrated approaches.
  • Survey students on their perceptions of enjoyment, interest, and relevance of technology-enhanced lessons compared to traditional methods.
  • Track student login frequency, time spent on learning platforms, and completion rates for assignments using educational software.

2.3 Development of 21st-Century Skills

  • Research Focus: How does technology foster the development of essential skills for the future, such as critical thinking, collaboration, communication, creativity, and digital literacy?
  • Analyze student projects involving multimedia creation, coding, or robotics for evidence of problem-solving, creativity, and technical skills.
  • Observe and assess online collaborative projects for indicators of effective communication, teamwork, and digital citizenship.
  • Evaluate student research projects conducted using online databases and resources for information literacy, critical evaluation of sources, and ethical digital practices.

2.4 Equity and Access in Education

  • Research Focus: Does technology bridge or widen the achievement gap? Does it provide equitable access to learning opportunities for all students, regardless of background or ability?
  • Analyze data on technology access, use, and performance across different student subgroups (e.g., socioeconomic status, ethnicity, special needs) to identify potential disparities.
  • Investigate the effectiveness of assistive technologies in supporting students with disabilities and promoting inclusive learning environments.
  • Examine how technology can be leveraged to personalize learning and address the diverse needs of all learners.

Section 3: Navigating Challenges and Ethical Considerations

The integration of technology in education is not without its challenges and ethical dilemmas:

3.1 Ensuring Effective Implementation

  • Challenge: Simply providing access to technology is not enough. Effective integration requires careful planning, teacher training, ongoing support, and alignment with curriculum goals.
  • Evaluate the quality of professional development opportunities provided to teachers on technology integration.
  • Assess the extent to which technology use is aligned with curriculum standards and learning objectives.
  • Investigate the availability of technical support and resources for both teachers and students.

3.2 Addressing the Digital Divide

  • Challenge: Inequitable access to technology and digital literacy skills can exacerbate existing achievement gaps and create new barriers for underprivileged students.

Investigative Focus:

  • Analyze data on home technology access, internet connectivity, and digital literacy levels among different student populations.
  • Evaluate the effectiveness of programs designed to bridge the digital divide, such as providing devices, internet subsidies, or digital literacy training for students and families.

3.3 Promoting Responsible and Ethical Use

  • Challenge: The digital age presents new challenges related to online safety, privacy, cyberbullying, digital citizenship, and the ethical use of information and technology.
  • Evaluate the effectiveness of school policies and programs aimed at promoting digital citizenship and responsible online behavior.
  • Investigate student and teacher awareness of privacy concerns and ethical considerations related to data collection and use in educational technology.

Section 4: Translating Findings into Actionable Insights

The ultimate goal of investigating the impact of technology on student learning is to inform practical improvements:

4.1 Data-Driven Decision Making

  • Action: Use research findings to guide evidence-based decisions about technology adoption, implementation strategies, and resource allocation.
  • If research shows that a specific math learning software is effective in improving student scores, schools might consider adopting it and providing adequate teacher training.
  • If data reveals a digital divide within a school, efforts can be directed towards providing equitable access and support.

4.2 Continuous Improvement and Innovation

  • Action: Foster a culture of ongoing reflection, evaluation, and refinement of technology use in education based on data and best practices.
  • Regularly collect student and teacher feedback on technology integration and use it to make adjustments.
  • Stay informed about emerging technologies and explore their potential to enhance student learning.

4.3 Collaboration and Knowledge Sharing

  • Action: Encourage collaboration among educators, researchers, policymakers, and technology developers to share best practices, address challenges, and promote innovation.
  • Host professional development workshops and conferences focused on technology integration and research findings.
  • Create online platforms or communities of practice for educators to connect, share resources, and learn from one another.

Conclusion: Embracing Complexity, Shaping the Future of Learning

Investigating the impact of technology on student learning is not about finding easy answers or declaring winners and losers. It’s about embracing the inherent complexity of this dynamic relationship and approaching it with criticality, curiosity, and a commitment to equity. By engaging in rigorous research and thoughtful reflection, we can harness the power of technology to create truly transformative learning experiences that equip all students with the knowledge, skills, and dispositions to thrive in the 21st century and beyond.

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research questions about impact of technology to students

Navigating AI-Powered Personalized Learning in Special Education: A Guide for Preservice Teacher Faculty

  • Kenneth Holman University of Central Florida

Integrating Artificial Intelligence-Powered Personalized Learning (AI-PPL) in special education teacher preparation represents a shift toward tailoring educational experiences to meet the unique needs of preservice teachers and students with disabilities. This article explores the implementation of AI-PPL tools in teacher preparation programs, highlighting their potential to customize learning experiences, provide adaptive feedback, and enhance engagement through interactive content. This review of current AI-PPL functionalities, such as adaptive learning environments and customized feedback mechanisms, demonstrates how AI-PPL can impact teaching practices and student learning outcomes. The article introduces critical attributes for successful AI-PPL integration, such as ensuring accessibility and inclusivity. It calls for further professional development to enhance educator competency and skills. By presenting real-world examples and guiding questions for special education faculty, the authors offer practical insights for educators and faculty members to effectively navigate the complexities of adopting AI technologies in teacher preparation programs.

  • Holman et al. (2024)

How to Cite

  • Endnote/Zotero/Mendeley (RIS)

Copyright (c) 2024 Kenneth Holman

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .

The Journal of Special Education Preparation ( JOSEP ) is an open-access, peer-reviewed journal that features research-to-practice information and materials for special education faculty in higher education settings. JOSEP brings its readers the latest on evidence-based instructional strategies, technologies, procedures, and techniques to prepare special education teachers and leaders. The focus of its practical content is on immediate application.

ISSN: 2768-1432

JOSEP is published in partnership with and funded by Ball State University Libraries and the Teacher Education Division of the Council for Exceptional Children.

research questions about impact of technology to students

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Kindness in the Classroom: Evaluating the Impact of Direct Kindness Instruction on School and Emotional Outcomes in Second-Grade Students

  • Braelyn Verba Kearney Public Schools, Nebraska, USA
  • Phu Vu University of Nebraska at Kearney

This study explores the effects of direct kindness instruction on second-grade students' social and emotional well-being. Amidst the growing integration of Social and Emotional Learning (SEL) into educational curricula, this research specifically focuses on the aspect of kindness, a vital yet often under-explored component of SEL. Conducted in a diverse second-grade classroom in a small Midwestern U.S. town, this study employs an action research methodology, using the Second Step curriculum and weekly kindness missions as interventions. The research is guided by two primary questions: the influence of direct kindness instruction on students' social behavior and its impact on their emotional well-being. The effectiveness of the interventions is evaluated using the Social Academic and Emotional Behavior Risk Screener (SABERS). Findings indicate significant improvements in students' academic, social, and emotional behaviors, underscoring the effectiveness of kindness instruction in enhancing the overall educational environment. The study highlights the need for incorporating structured SEL components, particularly kindness and empathy, in early education, and suggests future research directions for exploring long-term impacts of SEL interventions.

Author Biographies

Braelyn verba , kearney public schools, nebraska, usa.

Braelyn Verba is a 2nd grade teacher with Kearney Public Schools. Focused on continuing her professional learning to better support students, her topics of academic interest include STEM education, the benefits of kindness instruction and social/emotional learning, as well as incorporating play into the classroom.

Phu Vu, University of Nebraska at Kearney

Phu Vu is an associate professor in the Teacher Education department at the University of Nebraska at Kearney. He is interested in supporting teacher development at all levels. His research interests include technology- enhanced learning and teaching, game- based learning, gifted education and ESL.

research questions about impact of technology to students

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Making a measurable economic impact

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Saeed Miganeh poses standing in a hallway. A street scene is visible through windows in the background

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How do you measure the value of an economic policy? Of an aid organization’s programming? For Saeed Miganeh, who completed an  MITx MicroMasters in Data, Economics, and Development Policy and is now enrolled in MIT’s master’s program in Data, Economics, and Design of Policy (DEDP), these are key questions he is determined to answer.

“Enrolling at MIT fed my interest in investigating the political economy questions surrounding the development of African countries,” he says. “It boils down to promoting pro-poor, evidence-based policymaking in the developing world.”

Miganeh earned a bachelor of business administration from the  University of Hargeisa and completed coursework in  Open University Malaysia’s master of business administration program. Before enrolling at MIT full time, he spent 14 years as an accountant with the United Nations’  International Organization for Migration . His work with the IOM fed his curiosity about intent and impact, particularly how political agendas can affect policy adoption, how safeguarding human rights strengthens peace and prevents conflict, how climate change adaptation policies affect the poor, and how promoting intra-African trade spurs economic growth in the continent.

“My journey to DEDP began when I earned a certificate in Monitoring and Evaluation offered by the International Training Center of the  International Labour Organization ,” he recalls. “Our course coach recommended taking MITx courses, which led me to the MicroMasters program.”

Saeed grew up and completed his early education in the self-declared Republic of Somaliland during the reconstruction period after a decade-long civil war with Somalia. He was inspired by his country’s development of a functioning democracy and economy after conflict. Miganeh’s work is all the more impressive for someone who has lived almost exclusively there — with the exception of four years as a child spent in Ethiopia due to the civil war in Somalia — and whose studies have taken place entirely in the republic.

“Africa is the new battleground for fighting global poverty in the 21st century,” he says.

Practices and progress toward measurable improvement

Before pursuing graduate study at MIT, Miganeh worked in youth development programs with the  Somaliland National Youth Organization . “I was the coordinator for one of their youth networks that worked on health,” he says. “After completing my undergraduate study, I assumed the position of finance officer for the organization.”

Later during his tenure with IOM, Miganeh learned that, while the organization has a central evaluation function that evaluates projects and programs, Somaliland’s governmental institutions lacked the capacity to effectively evaluate public policies and programs effectively. His work with the IOM helped him discover the practice areas where he might benefit from partnering with others possessing expertise he’d need to make a difference. “During my work with IOM, I was involved in development projects’ administrative and accounting functions,” he remembers. “I was interested in knowing how projects were impacting beneficiaries’ lives.

Miganeh wants to dig deeper into understanding and answering developing African countries’ political economy questions, noting that “development projects can consume lots of resources from design through implementation.” Ensuring these programs’ effectiveness is crucial to maximizing their impact and societal benefit. “Every country needs to have the necessary human capital to undertake evidence-based policy design to avoid wasting resources,” he says.

He returned to Somaliland to complete a capstone project that will allow him to put his newly acquired skills and knowledge to work. The project is an important part of his master’s program. “I’m [working] with the  Somaliland Ministry of Education & Science , assisting in institutionalizing evidence-based policymaking in the education sector,”  he says.

A unique vision to drive effective change

Miganeh is already planning to use the skills he’s acquiring at MIT to facilitate change at home. “I must discover and produce policy insights using my research and, with the guidance of the top academics and professionals at MIT and other institutions, translate them into effective policies that can make a demonstrable impact,” he says.

Miganeh reports that MITx’s MicroMasters and DEDP master’s programs help students develop the unique blend of skills — including the ability to leverage data-driven insights to design, implement, and evaluate public policies that improve societal outcomes — that can help them become effective agents of social change.

“My early enthusiasm for mathematics in high school and my later work in development organizations gave me the right combination to excel in the rigorous developmental economics coursework at MIT,” he says. “Once I’ve completed the program, I will establish a consultancy to advise government agencies, nonprofits, and the private sector’s corporate social responsibility departments on designing, implementing, and evaluating policies and programs.”

Miganeh lauded the faculty and students he encountered while continuing his studies. “I have developed professionally and personally,” he reports. He saved his highest praise for the Institute, however.

“Pursuing this master’s degree at MIT, where modern economics education has been reinvented and is home to faculty including Nobel laureates and other distinguished professors and scholars, was an enriching lifetime experience, personally and professionally,” he says. 

“Looking back on discussions of how to tackle the world’s development challenges is a memory that will stay with me for the rest of my life.”

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

  • Published: 21 November 2022
  • Volume 28 , pages 6695–6726, ( 2023 )

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research questions about impact of technology to students

  • Stella Timotheou 1 ,
  • Ourania Miliou 1 ,
  • Yiannis Dimitriadis 2 ,
  • Sara Villagrá Sobrino 2 ,
  • Nikoleta Giannoutsou 2 ,
  • Romina Cachia 3 ,
  • Alejandra Martínez Monés 2 &
  • Andri Ioannou   ORCID: orcid.org/0000-0002-3570-6578 1  

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Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

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1 Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

2 Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table 1 .

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

3.1 Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

3.2 Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

3.3 Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

3.4 Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

3.5 Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

3.5.1 Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

3.5.2 Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

3.5.3 School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

3.5.4 Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

3.5.5 Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

3.5.6 Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

3.5.7 Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

figure 1

Factors that affect the impact of ICTs on education

4 Discussion

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

figure 2

Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

5 Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

6 Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Data availability statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Archer, K., Savage, R., Sanghera-Sidhu, S., Wood, E., Gottardo, A., & Chen, V. (2014). Examining the effectiveness of technology use in classrooms: A tertiary meta-analysis. Computers & Education, 78 , 140–149. https://doi.org/10.1016/j.compedu.2014.06.001

Article   Google Scholar  

Aromatario, O., Van Hoye, A., Vuillemin, A., Foucaut, A. M., Pommier, J., & Cambon, L. (2019). Using theory of change to develop an intervention theory for designing and evaluating behavior change SDApps for healthy eating and physical exercise: The OCAPREV theory. BMC Public Health, 19 (1), 1–12. https://doi.org/10.1186/s12889-019-7828-4

Arztmann, M., Hornstra, L., Jeuring, J., & Kester, L. (2022). Effects of games in STEM education: A meta-analysis on the moderating role of student background characteristics. Studies in Science Education , 1-37. https://doi.org/10.1080/03057267.2022.2057732

Bado, N. (2022). Game-based learning pedagogy: A review of the literature. Interactive Learning Environments, 30 (5), 936–948. https://doi.org/10.1080/10494820.2019.1683587

Balanskat, A. (2009). Study of the impact of technology in primary schools – Synthesis Report. Empirica and European Schoolnet. Retrieved 30 June 2022 from: https://erte.dge.mec.pt/sites/default/files/Recursos/Estudos/synthesis_report_steps_en.pdf

Balanskat, A. (2006). The ICT Impact Report: A review of studies of ICT impact on schools in Europe, European Schoolnet. Retrieved 30 June 2022 from:  https://en.unesco.org/icted/content/ict-impact-report-review-studies-ict-impact-schools-europe

Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT impact report.  European Schoolnet . Retrieved from: http://colccti.colfinder.org/sites/default/files/ict_impact_report_0.pdf

Balyer, A., & Öz, Ö. (2018). Academicians’ views on digital transformation in education. International Online Journal of Education and Teaching (IOJET), 5 (4), 809–830. Retrieved 30 June 2022 from  http://iojet.org/index.php/IOJET/article/view/441/295

Baragash, R. S., Al-Samarraie, H., Moody, L., & Zaqout, F. (2022). Augmented reality and functional skills acquisition among individuals with special needs: A meta-analysis of group design studies. Journal of Special Education Technology, 37 (1), 74–81. https://doi.org/10.1177/0162643420910413

Bates, A. W. (2015). Teaching in a digital age: Guidelines for designing teaching and learning . Open Educational Resources Collection . 6. Retrieved 30 June 2022 from: https://irl.umsl.edu/oer/6

Bingimlas, K. A. (2009). Barriers to the successful integration of ICT in teaching and learning environments: A review of the literature. Eurasia Journal of Mathematics, Science and Technology Education, 5 (3), 235–245. https://doi.org/10.12973/ejmste/75275

Blaskó, Z., Costa, P. D., & Schnepf, S. V. (2022). Learning losses and educational inequalities in Europe: Mapping the potential consequences of the COVID-19 crisis. Journal of European Social Policy, 32 (4), 361–375. https://doi.org/10.1177/09589287221091687

Bocconi, S., & Lightfoot, M. (2021). Scaling up and integrating the selfie tool for schools’ digital capacity in education and training systems: Methodology and lessons learnt. European Training Foundation . https://doi.org/10.2816/907029,JRC123936 . Accessed 30 June 2022.

Brooks, D. C., & McCormack, M. (2020). Driving Digital Transformation in Higher Education . Retrieved 30 June 2022 from: https://library.educause.edu/-/media/files/library/2020/6/dx2020.pdf?la=en&hash=28FB8C377B59AFB1855C225BBA8E3CFBB0A271DA

Cachia, R., Chaudron, S., Di Gioia, R., Velicu, A., & Vuorikari, R. (2021). Emergency remote schooling during COVID-19, a closer look at European families. Retrieved 30 June 2022 from  https://publications.jrc.ec.europa.eu/repository/handle/JRC125787

Çelik, B. (2022). The effects of computer simulations on students’ science process skills: Literature review. Canadian Journal of Educational and Social Studies, 2 (1), 16–28. https://doi.org/10.53103/cjess.v2i1.17

Chapman, C., & Sammons, P. (2013). School Self-Evaluation for School Improvement: What Works and Why? . CfBT Education Trust. 60 Queens Road, Reading, RG1 4BS, England.

Chauhan, S. (2017). A meta-analysis of the impact of technology on learning effectiveness of elementary students. Computers & Education, 105 , 14–30. https://doi.org/10.1016/j.compedu.2016.11.005

Chen, Q., Chan, K. L., Guo, S., Chen, M., Lo, C. K. M., & Ip, P. (2022a). Effectiveness of digital health interventions in reducing bullying and cyberbullying: a meta-analysis. Trauma, Violence, & Abuse , 15248380221082090. https://doi.org/10.1177/15248380221082090

Chen, B., Wang, Y., & Wang, L. (2022b). The effects of virtual reality-assisted language learning: A meta-analysis. Sustainability, 14 (6), 3147. https://doi.org/10.3390/su14063147

Cheok, M. L., & Wong, S. L. (2015). Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction, 8 (1), 75–90.

Cheung, A. C., & Slavin, R. E. (2011). The Effectiveness of Education Technology for Enhancing Reading Achievement: A Meta-Analysis. Center for Research and reform in Education .

Coban, M., Bolat, Y. I., & Goksu, I. (2022). The potential of immersive virtual reality to enhance learning: A meta-analysis. Educational Research Review , 100452. https://doi.org/10.1016/j.edurev.2022.100452

Condie, R., & Munro, R. K. (2007). The impact of ICT in schools-a landscape review. Retrieved 30 June 2022 from: https://oei.org.ar/ibertic/evaluacion/sites/default/files/biblioteca/33_impact_ict_in_schools.pdf

Conrads, J., Rasmussen, M., Winters, N., Geniet, A., Langer, L., (2017). Digital Education Policies in Europe and Beyond: Key Design Principles for More Effective Policies. Redecker, C., P. Kampylis, M. Bacigalupo, Y. Punie (ed.), EUR 29000 EN, Publications Office of the European Union, Luxembourg, https://doi.org/10.2760/462941

Costa, P., Castaño-Muñoz, J., & Kampylis, P. (2021). Capturing schools’ digital capacity: Psychometric analyses of the SELFIE self-reflection tool. Computers & Education, 162 , 104080. https://doi.org/10.1016/j.compedu.2020.104080

Cussó-Calabuig, R., Farran, X. C., & Bosch-Capblanch, X. (2018). Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: A systematic review. Education and Information Technologies, 23 (5), 2111–2139. https://doi.org/10.1007/s10639-018-9706-6

Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49 (1), 91–96.

Delcker, J., & Ifenthaler, D. (2021). Teachers’ perspective on school development at German vocational schools during the Covid-19 pandemic. Technology, Pedagogy and Education, 30 (1), 125–139. https://doi.org/10.1080/1475939X.2020.1857826 . Accessed 30 June 2022.

Delgado, A., Wardlow, L., O’Malley, K., & McKnight, K. (2015). Educational technology: A review of the integration, resources, and effectiveness of technology in K-12 classrooms. Journal of Information Technology Education Research , 14, 397. Retrieved 30 June 2022 from  http://www.jite.org/documents/Vol14/JITEv14ResearchP397-416Delgado1829.pdf

De Silva, M. J., Breuer, E., Lee, L., Asher, L., Chowdhary, N., Lund, C., & Patel, V. (2014). Theory of change: A theory-driven approach to enhance the Medical Research Council’s framework for complex interventions. Trials, 15 (1), 1–13. https://doi.org/10.1186/1745-6215-15-267

Di Pietro, G., Biagi, F., Costa, P., Karpiński, Z., & Mazza, J. (2020). The likely impact of COVID-19 on education: Reflections based on the existing literature and recent international datasets (Vol. 30275). Publications Office of the European Union.

Google Scholar  

Elkordy, A., & Lovinelli, J. (2020). Competencies, Culture, and Change: A Model for Digital Transformation in K12 Educational Contexts. In D. Ifenthaler, S. Hofhues, M. Egloffstein, & C. Helbig (Eds.), Digital Transformation of Learning Organizations (pp. 203–219). Springer.

Eng, T. S. (2005). The impact of ICT on learning: A review of research. International Education Journal, 6 (5), 635–650.

European Commission. (2020). Digital Education Action Plan 2021 – 2027. Resetting education and training for the digital age. Retrieved 30 June 2022 from  https://ec.europa.eu/education/sites/default/files/document-library-docs/deap-communication-sept2020_en.pdf

European Commission. (2019). 2 nd survey of schools: ICT in education. Objective 1: Benchmark progress in ICT in schools . Retrieved 30 June 2022 from: https://data.europa.eu/euodp/data/storage/f/2019-03-19T084831/FinalreportObjective1-BenchmarkprogressinICTinschools.pdf

Eurydice. (2019). Digital Education at School in Europe , Luxembourg: Publications Office of the European Union. Retrieved 30 June 2022 from: https://eacea.ec.europa.eu/national-policies/eurydice/content/digital-education-school-europe_en

Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2017). Education technology: An evidence-based review. Retrieved 30 June 2022 from  https://ssrn.com/abstract=3031695

Fadda, D., Pellegrini, M., Vivanet, G., & Zandonella Callegher, C. (2022). Effects of digital games on student motivation in mathematics: A meta-analysis in K-12. Journal of Computer Assisted Learning, 38 (1), 304–325. https://doi.org/10.1111/jcal.12618

Fernández-Gutiérrez, M., Gimenez, G., & Calero, J. (2020). Is the use of ICT in education leading to higher student outcomes? Analysis from the Spanish Autonomous Communities. Computers & Education, 157 , 103969. https://doi.org/10.1016/j.compedu.2020.103969 . Accessed 30 June 2022.

Ferrari, A., Cachia, R., & Punie, Y. (2011). Educational change through technology: A challenge for obligatory schooling in Europe. Lecture Notes in Computer Science , 6964 , 97–110. Retrieved 30 June 2022  https://link.springer.com/content/pdf/10.1007/978-3-642-23985-4.pdf

Fielding, K., & Murcia, K. (2022). Research linking digital technologies to young children’s creativity: An interpretive framework and systematic review. Issues in Educational Research , 32 (1), 105–125. Retrieved 30 June 2022 from  http://www.iier.org.au/iier32/fielding-abs.html

Friedel, H., Bos, B., Lee, K., & Smith, S. (2013). The impact of mobile handheld digital devices on student learning: A literature review with meta-analysis. In Society for Information Technology & Teacher Education International Conference (pp. 3708–3717). Association for the Advancement of Computing in Education (AACE).

Fu, J. S. (2013). ICT in education: A critical literature review and its implications. International Journal of Education and Development Using Information and Communication Technology (IJEDICT), 9 (1), 112–125.

Gaol, F. L., & Prasolova-Førland, E. (2022). Special section editorial: The frontiers of augmented and mixed reality in all levels of education. Education and Information Technologies, 27 (1), 611–623.

Garzón, J., & Acevedo, J. (2019). Meta-analysis of the impact of Augmented Reality on students’ learning gains. Educational Research Review, 27 , 244–260. https://doi.org/10.1016/j.edurev.2019.04.001

Garzón, J., Baldiris, S., Gutiérrez, J., & Pavón, J. (2020). How do pedagogical approaches affect the impact of augmented reality on education? A meta-analysis and research synthesis. Educational Research Review , 100334. https://doi.org/10.1016/j.edurev.2020.100334

Grgurović, M., Chapelle, C. A., & Shelley, M. C. (2013). A meta-analysis of effectiveness studies on computer technology-supported language learning. ReCALL, 25 (2), 165–198. https://doi.org/10.1017/S0958344013000013

Haßler, B., Major, L., & Hennessy, S. (2016). Tablet use in schools: A critical review of the evidence for learning outcomes. Journal of Computer Assisted Learning, 32 (2), 139–156. https://doi.org/10.1111/jcal.12123

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3 , 275–285.

Hardman, J. (2019). Towards a pedagogical model of teaching with ICTs for mathematics attainment in primary school: A review of studies 2008–2018. Heliyon, 5 (5), e01726. https://doi.org/10.1016/j.heliyon.2019.e01726

Hattie, J., Rogers, H. J., & Swaminathan, H. (2014). The role of meta-analysis in educational research. In A. D. Reid, P. Hart, & M. A. Peters (Eds.), A companion to research in education (pp. 197–207). Springer.

Chapter   Google Scholar  

Hattie, J. (2008). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge . https://doi.org/10.4324/9780203887332

Higgins, S., Xiao, Z., & Katsipataki, M. (2012). The impact of digital technology on learning: A summary for the education endowment foundation . Education Endowment Foundation and Durham University.

Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research , 57(2), 283-319.

Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153 (1038), 97. https://doi.org/10.1016/j.compedu.2020.103897

Istenic Starcic, A., & Bagon, S. (2014). ICT-supported learning for inclusion of people with special needs: Review of seven educational technology journals, 1970–2011. British Journal of Educational Technology, 45 (2), 202–230. https://doi.org/10.1111/bjet.12086 . Accessed 30 June 2022.

Jewitt, C., Clark, W., & Hadjithoma-Garstka, C. (2011). The use of learning platforms to organise learning in English primary and secondary schools. Learning, Media and Technology, 36 (4), 335–348. https://doi.org/10.1080/17439884.2011.621955

JISC. (2020). What is digital transformation?.  Retrieved 30 June 2022 from: https://www.jisc.ac.uk/guides/digital-strategy-framework-for-university-leaders/what-is-digital-transformation

Kalati, A. T., & Kim, M. S. (2022). What is the effect of touchscreen technology on young children’s learning?: A systematic review. Education and Information Technologies , 1-19. https://doi.org/10.1007/s10639-021-10816-5

Kalemkuş, J., & Kalemkuş, F. (2022). Effect of the use of augmented reality applications on academic achievement of student in science education: Meta-analysis review. Interactive Learning Environments , 1-18. https://doi.org/10.1080/10494820.2022.2027458

Kao, C.-W. (2014). The effects of digital game-based learning task in English as a foreign language contexts: A meta-analysis. Education Journal, 42 (2), 113–141.

Kampylis, P., Punie, Y., & Devine, J. (2015). Promoting effective digital-age learning - a European framework for digitally competent educational organisations. JRC Technical Reports . https://doi.org/10.2791/54070

Kazu, I. Y., & Yalçin, C. K. (2022). Investigation of the effectiveness of hybrid learning on academic achievement: A meta-analysis study. International Journal of Progressive Education, 18 (1), 249–265. https://doi.org/10.29329/ijpe.2022.426.14

Koh, C. (2022). A qualitative meta-analysis on the use of serious games to support learners with intellectual and developmental disabilities: What we know, what we need to know and what we can do. International Journal of Disability, Development and Education, 69 (3), 919–950.

König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43 (4), 608–622. https://doi.org/10.1080/02619768.2020.1809650

Lawrence, J. E., & Tar, U. A. (2018). Factors that influence teachers’ adoption and integration of ICT in teaching/learning process. Educational Media International, 55 (1), 79–105. https://doi.org/10.1080/09523987.2018.1439712

Lee, S., Kuo, L. J., Xu, Z., & Hu, X. (2020). The effects of technology-integrated classroom instruction on K-12 English language learners’ literacy development: A meta-analysis. Computer Assisted Language Learning , 1-32. https://doi.org/10.1080/09588221.2020.1774612

Lei, H., Chiu, M. M., Wang, D., Wang, C., & Xie, T. (2022a). Effects of game-based learning on students’ achievement in science: a meta-analysis. Journal of Educational Computing Research . https://doi.org/10.1177/07356331211064543

Lei, H., Wang, C., Chiu, M. M., & Chen, S. (2022b). Do educational games affect students’ achievement emotions? Evidence from a meta-analysis. Journal of Computer Assisted Learning., 38 (4), 946–959. https://doi.org/10.1111/jcal.12664

Liao, Y. K. C., Chang, H. W., & Chen, Y. W. (2007). Effects of computer application on elementary school student’s achievement: A meta-analysis of students in Taiwan. Computers in the Schools, 24 (3–4), 43–64. https://doi.org/10.1300/J025v24n03_04

Li, Q., & Ma, X. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review, 22 (3), 215–243.

Liu, M., Pang, W., Guo, J., & Zhang, Y. (2022). A meta-analysis of the effect of multimedia technology on creative performance. Education and Information Technologies , 1-28. https://doi.org/10.1007/s10639-022-10981-1

Lu, Z., Chiu, M. M., Cui, Y., Mao, W., & Lei, H. (2022). Effects of game-based learning on students’ computational thinking: A meta-analysis. Journal of Educational Computing Research . https://doi.org/10.1177/07356331221100740

Martinez, L., Gimenes, M., & Lambert, E. (2022). Entertainment video games for academic learning: A systematic review. Journal of Educational Computing Research . https://doi.org/10.1177/07356331211053848

Mayne, J. (2015). Useful theory of change models. Canadian Journal of Program Evaluation, 30 (2), 119–142. https://doi.org/10.3138/cjpe.230

Moran, J., Ferdig, R. E., Pearson, P. D., Wardrop, J., & Blomeyer, R. L., Jr. (2008). Technology and reading performance in the middle-school grades: A meta-analysis with recommendations for policy and practice. Journal of Literacy Research, 40 (1), 6–58. https://doi.org/10.1080/10862960802070483

OECD. (2015). Students, Computers and Learning: Making the Connection . PISA, OECD Publishing, Paris. Retrieved from: https://doi.org/10.1787/9789264239555-en

OECD. (2021). OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. Retrieved from: https://www.oecd-ilibrary.org/education/oecd-digital-education-outlook-2021_589b283f-en

Pan, Y., Ke, F., & Xu, X. (2022). A systematic review of the role of learning games in fostering mathematics education in K-12 settings. Educational Research Review, 36 , 100448. https://doi.org/10.1016/j.edurev.2022.100448

Pettersson, F. (2021). Understanding digitalization and educational change in school by means of activity theory and the levels of learning concept. Education and Information Technologies, 26 (1), 187–204.

Pihir, I., Tomičić-Pupek, K., & Furjan, M. T. (2018). Digital transformation insights and trends. In Central European Conference on Information and Intelligent Systems (pp. 141–149). Faculty of Organization and Informatics Varazdin. Retrieved 30 June 2022 from https://www.proquest.com/conference-papers-proceedings/digital-transformation-insights-trends/docview/2125639934/se-2

Punie, Y., Zinnbauer, D., & Cabrera, M. (2006). A review of the impact of ICT on learning. Working Paper prepared for DG EAC. Retrieved 30 June 2022 from: http://www.eurosfaire.prd.fr/7pc/doc/1224678677_jrc47246n.pdf

Quah, C. Y., & Ng, K. H. (2022). A systematic literature review on digital storytelling authoring tool in education: January 2010 to January 2020. International Journal of Human-Computer Interaction, 38 (9), 851–867. https://doi.org/10.1080/10447318.2021.1972608

Ran, H., Kim, N. J., & Secada, W. G. (2022). A meta-analysis on the effects of technology’s functions and roles on students’ mathematics achievement in K-12 classrooms. Journal of computer assisted learning, 38 (1), 258–284. https://doi.org/10.1111/jcal.12611

Ređep, N. B. (2021). Comparative overview of the digital preparedness of education systems in selected CEE countries. Center for Policy Studies. CEU Democracy Institute .

Rott, B., & Marouane, C. (2018). Digitalization in schools–organization, collaboration and communication. In Digital Marketplaces Unleashed (pp. 113–124). Springer, Berlin, Heidelberg.

Savva, M., Higgins, S., & Beckmann, N. (2022). Meta-analysis examining the effects of electronic storybooks on language and literacy outcomes for children in grades Pre-K to grade 2. Journal of Computer Assisted Learning, 38 (2), 526–564. https://doi.org/10.1111/jcal.12623

Schmid, R. F., Bernard, R. M., Borokhovski, E., Tamim, R. M., Abrami, P. C., Surkes, M. A., Wade, C. A., & Woods, J. (2014). The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education, 72 , 271–291. https://doi.org/10.1016/j.compedu.2013.11.002

Schuele, C. M., & Justice, L. M. (2006). The importance of effect sizes in the interpretation of research: Primer on research: Part 3. The ASHA Leader, 11 (10), 14–27. https://doi.org/10.1044/leader.FTR4.11102006.14

Schwabe, A., Lind, F., Kosch, L., & Boomgaarden, H. G. (2022). No negative effects of reading on screen on comprehension of narrative texts compared to print: A meta-analysis. Media Psychology , 1-18. https://doi.org/10.1080/15213269.2022.2070216

Sellar, S. (2015). Data infrastructure: a review of expanding accountability systems and large-scale assessments in education. Discourse: Studies in the Cultural Politics of Education, 36 (5), 765–777. https://doi.org/10.1080/01596306.2014.931117

Stock, W. A. (1994). Systematic coding for research synthesis. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis, 236 (pp. 125–138). Russel Sage.

Su, J., Zhong, Y., & Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence , 100065. https://doi.org/10.1016/j.caeai.2022.100065

Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3 , 100049. https://doi.org/10.1016/j.caeai.2022.100049

Sung, Y. T., Chang, K. E., & Liu, T. C. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, 94 , 252–275. https://doi.org/10.1016/j.compedu.2015.11.008

Talan, T., Doğan, Y., & Batdı, V. (2020). Efficiency of digital and non-digital educational games: A comparative meta-analysis and a meta-thematic analysis. Journal of Research on Technology in Education, 52 (4), 474–514. https://doi.org/10.1080/15391523.2020.1743798

Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational research, 81 (1), 4–28. Retrieved 30 June 2022 from  https://doi.org/10.3102/0034654310393361

Tamim, R. M., Borokhovski, E., Pickup, D., Bernard, R. M., & El Saadi, L. (2015). Tablets for teaching and learning: A systematic review and meta-analysis. Commonwealth of Learning. Retrieved from: http://oasis.col.org/bitstream/handle/11599/1012/2015_Tamim-et-al_Tablets-for-Teaching-and-Learning.pdf

Tang, C., Mao, S., Xing, Z., & Naumann, S. (2022). Improving student creativity through digital technology products: A literature review. Thinking Skills and Creativity, 44 , 101032. https://doi.org/10.1016/j.tsc.2022.101032

Tolani-Brown, N., McCormac, M., & Zimmermann, R. (2011). An analysis of the research and impact of ICT in education in developing country contexts. In ICTs and sustainable solutions for the digital divide: Theory and perspectives (pp. 218–242). IGI Global.

Trucano, M. (2005). Knowledge Maps: ICTs in Education. Washington, DC: info Dev / World Bank. Retrieved 30 June 2022 from  https://files.eric.ed.gov/fulltext/ED496513.pdf

Ulum, H. (2022). The effects of online education on academic success: A meta-analysis study. Education and Information Technologies, 27 (1), 429–450.

Underwood, J. D. (2009). The impact of digital technology: A review of the evidence of the impact of digital technologies on formal education. Retrieved 30 June 2022 from: http://dera.ioe.ac.uk/id/eprint/10491

Verschaffel, L., Depaepe, F., & Mevarech, Z. (2019). Learning Mathematics in metacognitively oriented ICT-Based learning environments: A systematic review of the literature. Education Research International , 2019 . https://doi.org/10.1155/2019/3402035

Villena-Taranilla, R., Tirado-Olivares, S., Cózar-Gutiérrez, R., & González-Calero, J. A. (2022). Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis. Educational Research Review, 35 , 100434. https://doi.org/10.1016/j.edurev.2022.100434

Voogt, J., Knezek, G., Cox, M., Knezek, D., & ten Brummelhuis, A. (2013). Under which conditions does ICT have a positive effect on teaching and learning? A call to action. Journal of Computer Assisted Learning, 29 (1), 4–14. https://doi.org/10.1111/j.1365-2729.2011.00453.x

Vuorikari, R., Punie, Y., & Cabrera, M. (2020). Emerging technologies and the teaching profession: Ethical and pedagogical considerations based on near-future scenarios  (No. JRC120183). Joint Research Centre. Retrieved 30 June 2022 from: https://publications.jrc.ec.europa.eu/repository/handle/JRC120183

Wang, L. H., Chen, B., Hwang, G. J., Guan, J. Q., & Wang, Y. Q. (2022). Effects of digital game-based STEM education on students’ learning achievement: A meta-analysis. International Journal of STEM Education, 9 (1), 1–13. https://doi.org/10.1186/s40594-022-00344-0

Wen, X., & Walters, S. M. (2022). The impact of technology on students’ writing performances in elementary classrooms: A meta-analysis. Computers and Education Open, 3 , 100082. https://doi.org/10.1016/j.caeo.2022.100082

Zheng, B., Warschauer, M., Lin, C. H., & Chang, C. (2016). Learning in one-to-one laptop environments: A meta-analysis and research synthesis. Review of Educational Research, 86 (4), 1052–1084. https://doi.org/10.3102/0034654316628645

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This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

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Timotheou, S., Miliou, O., Dimitriadis, Y. et al. Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review. Educ Inf Technol 28 , 6695–6726 (2023). https://doi.org/10.1007/s10639-022-11431-8

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The University of Chicago The Law School

Abrams environmental law clinic—significant achievements for 2023-24, protecting our great lakes, rivers, and shorelines.

The Abrams Clinic represents Friends of the Chicago River and the Sierra Club in their efforts to hold Trump Tower in downtown Chicago accountable for withdrawing water illegally from the Chicago River. To cool the building, Trump Tower draws water at high volumes, similar to industrial factories or power plants, but Trump Tower operated for more than a decade without ever conducting the legally required studies to determine the impact of those operations on aquatic life or without installing sufficient equipment to protect aquatic life consistent with federal regulations. After the Clinic sent a notice of intent to sue Trump Tower, the State of Illinois filed its own case in the summer of 2018, and the Clinic moved successfully to intervene in that case. In 2023-24, motions practice and discovery continued. Working with co-counsel at Northwestern University’s Pritzker Law School’s Environmental Advocacy Center, the Clinic moved to amend its complaint to include Trump Tower’s systematic underreporting each month of the volume of water that it intakes from and discharges to the Chicago River. The Clinic and co-counsel addressed Trump Tower’s motion to dismiss some of our clients’ claims, and we filed a motion for summary judgment on our claim that Trump Tower has committed a public nuisance. We also worked closely with our expert, Dr. Peter Henderson, on a supplemental disclosure and on defending an additional deposition of him. In summer 2024, the Clinic is defending its motion for summary judgment and challenging Trump Tower’s own motion for summary judgment. The Clinic is also preparing for trial, which could take place as early as fall 2024.

Since 2016, the Abrams Clinic has worked with the Chicago chapter of the Surfrider Foundation to protect water quality along the Lake Michigan shoreline in northwest Indiana, where its members surf. In April 2017, the U. S. Steel plant in Portage, Indiana, spilled approximately 300 pounds of hexavalent chromium into Lake Michigan. In January 2018, the Abrams Clinic filed a suit on behalf of Surfrider against U. S. Steel, alleging multiple violations of U. S. Steel’s discharge permits; the City of Chicago filed suit shortly after. When the US government and the State of Indiana filed their own, separate case, the Clinic filed extensive comments on the proposed consent decree. In August 2021, the court entered a revised consent decree which included provisions advocated for by Surfrider and the City of Chicago, namely a water sampling project that alerts beachgoers as to Lake Michigan’s water quality conditions, better notifications in case of future spills, and improvements to U. S. Steel’s operations and maintenance plans. In the 2023-24 academic year, the Clinic successfully litigated its claims for attorneys’ fees as a substantially prevailing party. Significantly, the court’s order adopted the “Fitzpatrick matrix,” used by the US Attorney’s Office for the District of Columbia to determine appropriate hourly rates for civil litigants, endorsed Chicago legal market rates as the appropriate rates for complex environmental litigation in Northwest Indiana, and allowed for partially reconstructed time records. The Clinic’s work, which has received significant media attention, helped to spawn other litigation to address pollution by other industrial facilities in Northwest Indiana and other enforcement against U. S. Steel by the State of Indiana.

In Winter Quarter 2024, Clinic students worked closely with Dr. John Ikerd, an agricultural economist and emeritus professor at the University of Missouri, to file an amicus brief in Food & Water Watch v. U.S. Environmental Protection Agency . In that case pending before the Ninth Circuit, Food & Water Watch argues that US EPA is illegally allowing Concentrated Animal Feeding Operations, more commonly known as factory farms, to pollute waterways significantly more than is allowable under the Clean Water Act. In the brief for Dr. Ikerd and co-amici Austin Frerick, Crawford Stewardship Project, Family Farm Defenders, Farm Aid, Missouri Rural Crisis Center, National Family Farm Coalition, National Sustainable Agriculture Coalition, and Western Organization of Resource Councils, we argued that EPA’s refusal to regulate CAFOs effectively is an unwarranted application of “agricultural exceptionalism” to industrial agriculture and that EPA effectively distorts the animal production market by allowing CAFOs to externalize their pollution costs and diminishing the ability of family farms to compete. Attorneys for the litigants will argue the case in September 2024.

Energy and Climate

Energy justice.

The Abrams Clinic supported grassroots organizations advocating for energy justice in low-income communities and Black, Indigenous, and People of Color (BIPOC) communities in Michigan. With the Clinic’s representation, these organizations intervened in cases before the Michigan Public Service Commission (MPSC), which regulates investor-owned utilities. Students conducted discovery, drafted written testimony, cross-examined utility executives, participated in settlement discussions, and filed briefs for these projects. The Clinic’s representation has elevated the concerns of these community organizations and forced both the utilities and regulators to consider issues of equity to an unprecedented degree. This year, on behalf of Soulardarity (Highland Park, MI), We Want Green, Too (Detroit, MI), and Urban Core Collective (Grand Rapids, MI), Clinic students engaged in eight contested cases before the MPSC against DTE Electric, DTE Gas, and Consumers Energy, as well as provided support for our clients’ advocacy in other non-contested MPSC proceedings.

The Clinic started this past fall with wins in three cases. First, the Clinic’s clients settled with DTE Electric in its Integrated Resource Plan case. The settlement included an agreement to close the second dirtiest coal power plant in Michigan three years early, $30 million from DTE’s shareholders to assist low-income customers in paying their bills, and $8 million from DTE’s shareholders toward a community fund that assists low-income customers with installing energy efficiency improvements, renewable energy, and battery technology. Second, in DTE Electric’s 2023 request for a rate hike (a “rate case”), the Commission required DTE Electric to develop a more robust environmental justice analysis and rejected the Company’s second attempt to waive consumer protections through a proposed electric utility prepayment program with a questionable history of success during its pilot run. The final Commission order and the administrative law judge’s proposal for final decision cited the Clinic’s testimony and briefs. Third, in Consumers Electric’s 2023 rate case, the Commission rejected the Company’s request for a higher ratepayer-funded return on its investments and required the Company to create a process that will enable intervenors to obtain accurate GIS data. The Clinic intends to use this data to map the disparate impact of infrastructure investment in low-income and BIPOC communities.

In the winter, the Clinic filed public comments regarding DTE Electric and Consumers Energy’s “distribution grid plans” (DGP) as well as supported interventions in two additional cases: Consumers Energy’s voluntary green pricing (VGP) case and the Clinic’s first case against the gas utility DTE Gas. Beginning with the DGP comments, the Clinic first addressed Consumers’s 2023 Electric Distribution Infrastructure Investment Plan (EDIIP), which detailed current distribution system health and the utility’s approximately $7 billion capital project planning ($2 billion of which went unaccounted for in the EDIIP) over 2023–2028. The Clinic then commented on DTE Electric’s 2023 DGP, which outlined the utility’s opaque project prioritization and planned more than $9 billion in capital investments and associated maintenance over 2024–2028. The comments targeted four areas of deficiencies in both the EDIIP and DGP: (1) inadequate consideration of distributed energy resources (DERs) as providing grid reliability, resiliency, and energy transition benefits; (2) flawed environmental justice analysis, particularly with respect to the collection of performance metrics and the narrow implementation of the Michigan Environmental Justice Screen Tool; (3) inequitable investment patterns across census tracts, with emphasis on DTE Electric’s skewed prioritization for retaining its old circuits rather than upgrading those circuits; and (4) failing to engage with community feedback.

For the VGP case against Consumers, the Clinic supported the filing of both an initial brief and reply brief requesting that the Commission reject the Company’s flawed proposal for a “community solar” program. In a prior case, the Clinic advocated for the development of a community solar program that would provide low-income, BIPOC communities with access to clean energy. As a result of our efforts, the Commission approved a settlement agreement requiring the Company “to evaluate and provide a strawman recommendation on community solar in its Voluntary Green Pricing Program.” However, the Company’s subsequent proposal in its VGP case violated the Commission’s order because it (1) was not consistent with the applicable law, MCL 460.1061; (2) was not a true community solar program; (3) lacked essential details; (4) failed to compensate subscribers sufficiently; (5) included overpriced and inflexible subscriptions; (6) excessively limited capacity; and (7) failed to provide a clear pathway for certain participants to transition into other VGP programs. For these reasons, the Clinic argued that the Commission should reject the Company’s proposal.

In DTE Gas’s current rate case, the Clinic worked with four witnesses to develop testimony that would rebut DTE Gas’s request for a rate hike on its customers. The testimony advocated for a pathway to a just energy transition that avoids dumping the costs of stranded gas assets on the low-income and BIPOC communities that are likely to be the last to electrify. Instead, the testimony proposed that the gas and electric utilities undertake integrated planning that would prioritize electric infrastructure over gas infrastructure investment to ensure that DTE Gas does not over-invest in gas infrastructure that will be rendered obsolete in the coming decades. The Clinic also worked with one expert witness to develop an analysis of DTE Gas’s unaffordable bills and inequitable shutoff, deposit, and collections practices. Lastly, the Clinic offered testimony on behalf of and from community members who would be directly impacted by the Company’s rate hike and lack of affordable and quality service. Clinic students have spent the summer drafting an approximately one-hundred-page brief making these arguments formally. We expect the Commission’s decision this fall.

Finally, both DTE Electric and Consumers Energy have filed additional requests for rate increases after the conclusion of their respective rate cases filed in 2023. On behalf of our Clients, the Clinic has intervened in these cases, and clinic students have already reviewed thousands of pages of documents and started to develop arguments and strategies to protect low-income and BIPOC communities from the utility’s ceaseless efforts to increase the cost of energy.

Corporate Climate Greenwashing

The Abrams Environmental Law Clinic worked with a leading international nonprofit dedicated to using the law to protect the environment to research corporate climate greenwashing, focusing on consumer protection, green financing, and securities liability. Clinic students spent the year examining an innovative state law, drafted a fifty-page guide to the statute and relevant cases, and examined how the law would apply to a variety of potential cases. Students then presented their findings in a case study and oral presentation to members of ClientEarth, including the organization’s North American head and members of its European team. The project helped identify the strengths and weaknesses of potential new strategies for increasing corporate accountability in the fight against climate change.

Land Contamination, Lead, and Hazardous Waste

The Abrams Clinic continues to represent East Chicago, Indiana, residents who live or lived on or adjacent to the USS Lead Superfund site. This year, the Clinic worked closely with the East Chicago/Calumet Coalition Community Advisory Group (CAG) to advance the CAG’s advocacy beyond the Superfund site and the adjacent Dupont RCRA site. Through multiple forms of advocacy, the clinics challenged the poor performance and permit modification and renewal attempts of Tradebe Treatment and Recycling, LLC (Tradebe), a hazardous waste storage and recycling facility in the community. Clinic students sent letters to US EPA and Indiana Department of Environmental Management officials about how IDEM has failed to assess meaningful penalties against Tradebe for repeated violations of the law and how IDEM has allowed Tradebe to continue to threaten public and worker health and safety by not improving its operations. Students also drafted substantial comments for the CAG on the US EPA’s Lead and Copper Rule improvements, the Suppliers’ Park proposed cleanup, and Sims Metal’s proposed air permit revisions. The Clinic has also continued working with the CAG, environmental experts, and regulators since US EPA awarded $200,000 to the CAG for community air monitoring. The Clinic and its clients also joined comments drafted by other environmental organizations about poor operations and loose regulatory oversight of several industrial facilities in the area.

Endangered Species

The Abrams Clinic represented the Center for Biological Diversity (CBD) and the Hoosier Environmental Council (HEC) in litigation regarding the US Fish and Wildlife Service’s (Service) failure to list the Kirtland’s snake as threatened or endangered under the Endangered Species Act. The Kirtland’s snake is a small, secretive, non-venomous snake historically located across the Midwest and the Ohio River Valley. Development and climate change have undermined large portions of the snake’s habitat, and populations are declining. Accordingly, the Clinic sued the Service in the US District Court for the District of Columbia last summer over the Service’s denial of CBD’s request to have the Kirtland’s snake protected. This spring, the Clinic was able to reach a settlement with the Service that requires the Service to reconsider its listing decision for the Kirtland’s snake and to pay attorney fees.

The Clinic also represented CBD in preparation for litigation regarding the Service’s failure to list another species as threatened or endangered. Threats from land development and climate change have devastated this species as well, and the species has already been extirpated from two of the sixteen US states in its range. As such, the Clinic worked this winter and spring to prepare a notice of intent (NOI) to sue the Service. The Team poured over hundreds of FOIA documents and dug into the Service’s supporting documentation to create strong arguments against the Service in the imminent litigation. The Clinic will send the NOI and file a complaint in the next few months.

Students and Faculty

Twenty-four law school students from the classes of 2024 and 2025 participated in the Clinic, performing complex legal research, reviewing documents obtained through discovery, drafting legal research memos and briefs, conferring with clients, conducting cross-examination, participating in settlement conferences, and arguing motions. Students secured nine clerkships, five were heading to private practice after graduation, and two are pursuing public interest work. Sam Heppell joined the Clinic from civil rights private practice, bringing the Clinic to its full complement of three attorneys.

IMAGES

  1. THE EFFECT OF TECHNOLOGY TO THE STUDENTS LEARNING.docx

    research questions about impact of technology to students

  2. Part II: The Mixed Impact of Digital Technologies on Student Research

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  3. (PDF) Impact of Technology on Education

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  4. Technology and Its Impact on Society Essay Example

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  5. The Impact of Technology Questionnaire edited

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  6. (PDF) The impact of modern technology in the teaching and learning process

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VIDEO

  1. How Technology Has Affected Education?

  2. Technology in Education: Opportunities, Challenges, Limits

  3. The Impact of Technology On Academics

  4. Student Voices: Impact of Tech on Education

  5. The Importance of Modern Technology in Schools

  6. Technology in the K-12 Classroom

COMMENTS

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  2. PDF The Impact of Digital Technology on Learning: A Summary for the ...

    Variables analyzed included characteristics of students, teachers, physical settings, and instructional formats. Glass' Δ 40 studies 58 effects Mean 0.309 Median 0.296 range -0.482 to 1.226 Effect sizes higher with more than 10 hours training or CPD (0.40) Teacher written software 0.82 higher than commercial 0.29.

  3. (PDF) The Effects of Technology-Integrated Curriculum on Student

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  4. PDF THE IMPACT OF TECHNOLOGY INTEGRATION ON STUDENT LEARNING ...

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  5. What 126 studies say about education technology

    J-PAL North America's recently released publication summarizes 126 rigorous evaluations of different uses of education technology and their impact on student learning. In recent years, there has been widespread excitement around the transformative potential of technology in education. In the United States alone, spending on education technology ...

  6. PDF Effects of Technology on Student Learning

    the classroom, the benefits and drawbacks of the use of technology in education, and particularly the impact on students' learning. For the purpose of this study, technology included only educational technology, i.e. internet and computer-mediated tools. It is important to understand the impact of technology on student learning because

  7. The Effects Of Technology On Student Motivation And Engagement In

    technology was introduced. One of the key findings in the literature on technology implementation is the power of. technology to engage students in relevant learning, in that the use of technology increases. student motivation and engagement (Godzicki, Godzicki, Krofel, & Michaels, 2013).

  8. Understanding the role of digital technologies in education: A review

    Students can ask questions about the classroom and receive extra help with the challenging subject matter. ... Examining the impact of digital technologies on students' higher education outcomes: the case of the virtual learning environment and social media ... Educational Technology Research and Development, 55 (3) (2007), pp. 301-314.

  9. Does the Impact of Technology Sustain Students' Satisfaction, Academic

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    To answer the research questions, a path analyses was conducted to test the model involving technology use, student engagement, self-directed learning and academic performance. The model comprised of one exogenous (technology use) and three endogenous (student engagement, self-directed learning and academic performance) variables.

  11. Students' use of technology and their ...

    In light of the global technology usage by students all over the world, previous studies have probed the impact of students' cultural background on technology acceptance and its use (He & Li, 2019). Research across cultures and countries has shown that culture can influence university students' behavioural intention to adopt online learning ...

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  13. PDF Student Perspectives on the Importance and Use of Technology in Learning

    from their colleges in the use of technology, how technology impacts educational outcomes, and how these factors differ for different student populations. Our general purpose in this study was to investigate students' perceptions and uses of technology. Specifically, the following research questions guided this study: 1.

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  15. Impacts of digital technologies on education and factors influencing

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    In the new millennium, education is rapidly changing due to the more and more pervasive use of technology to support teaching and learning. New Information and Communication Technologies (ICTs), such as internet, wikis, blogs, search engines, emails and instant messaging require new literacy frameworks and new contexts for learning and life. A digital approach to education implies pursuing new ...

  17. How technology is reinventing K-12 education

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  19. Effects of Technology on Student Learning and Behavior

    participated in a 17- question survey that collected data on their confidence, engagement, and. comfort when using technology for learning. Results of the study showed that 92% of students. felt confident using technology for their own learning, while 88% were more engaged when their.

  20. Technology can close achievement gaps, improve learning

    Technology can close achievement gaps, improve learning. In a new report, GSE researchers identify secrets to successful technology implementation, particularly with students at risk of dropping out. As school districts around the country consider investments in technology in an effort to improve student outcomes, a new report from the Alliance ...

  21. How to Investigate the Impact of Technology on Student Learning

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  22. PDF The impact of ICT on learning: A review of research

    636 The impact of ICT on learning: A review of research research in this field has been more consistent and well documented. Two periods of research have been suggested in this review. (a) Research findings and their implications from 1960s to 1980s; (b) Research findings and their implications from1990s to 2000s, and future research.

  23. Navigating AI-Powered Personalized Learning in Special Education: A

    Integrating Artificial Intelligence-Powered Personalized Learning (AI-PPL) in special education teacher preparation represents a shift toward tailoring educational experiences to meet the unique needs of preservice teachers and students with disabilities. This article explores the implementation of AI-PPL tools in teacher preparation programs, highlighting their potential to customize learning ...

  24. Kindness in the Classroom: Evaluating the Impact of Direct Kindness

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  25. Making a measurable economic impact

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  26. Impacts of digital technologies on education and factors influencing

    The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g ...

  27. 2024 Most Valuable Engineering Degree Programs Ranking ...

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  28. Abrams Environmental Law Clinic—Significant Achievements for 2023-24

    Students and Faculty Twenty-four law school students from the classes of 2024 and 2025 participated in the Clinic, performing complex legal research, reviewing documents obtained through discovery, drafting legal research memos and briefs, conferring with clients, conducting cross-examination, participating in settlement conferences, and ...

  29. PDF The Positive Effects of Technology on Teaching and Student ...

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  30. Forrester's 2024 Technology Strategy Impact Award Winners

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