Journal of Teaching in Physical Education
Subject Area and Category
- Physical Therapy, Sports Therapy and Rehabilitation
- Sports Science
- Orthopedics and Sports Medicine
Human Kinetics Publishers Inc.
Publication type
02735024, 15432769
Information
How to publish in this journal
The set of journals have been ranked according to their SJR and divided into four equal groups, four quartiles. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.
Category | Year | Quartile |
---|---|---|
Education | 1999 | Q2 |
Education | 2000 | Q2 |
Education | 2001 | Q1 |
Education | 2002 | Q2 |
Education | 2003 | Q2 |
Education | 2004 | Q2 |
Education | 2005 | Q2 |
Education | 2006 | Q1 |
Education | 2007 | Q1 |
Education | 2008 | Q2 |
Education | 2009 | Q1 |
Education | 2010 | Q2 |
Education | 2011 | Q1 |
Education | 2012 | Q1 |
Education | 2013 | Q2 |
Education | 2014 | Q2 |
Education | 2015 | Q2 |
Education | 2016 | Q2 |
Education | 2017 | Q1 |
Education | 2018 | Q1 |
Education | 2019 | Q1 |
Education | 2020 | Q1 |
Education | 2021 | Q1 |
Education | 2022 | Q1 |
Education | 2023 | Q1 |
Orthopedics and Sports Medicine | 1999 | Q2 |
Orthopedics and Sports Medicine | 2000 | Q2 |
Orthopedics and Sports Medicine | 2001 | Q2 |
Orthopedics and Sports Medicine | 2002 | Q2 |
Orthopedics and Sports Medicine | 2003 | Q2 |
Orthopedics and Sports Medicine | 2004 | Q2 |
Orthopedics and Sports Medicine | 2005 | Q2 |
Orthopedics and Sports Medicine | 2006 | Q2 |
Orthopedics and Sports Medicine | 2007 | Q2 |
Orthopedics and Sports Medicine | 2008 | Q2 |
Orthopedics and Sports Medicine | 2009 | Q2 |
Orthopedics and Sports Medicine | 2010 | Q2 |
Orthopedics and Sports Medicine | 2011 | Q2 |
Orthopedics and Sports Medicine | 2012 | Q1 |
Orthopedics and Sports Medicine | 2013 | Q2 |
Orthopedics and Sports Medicine | 2014 | Q2 |
Orthopedics and Sports Medicine | 2015 | Q2 |
Orthopedics and Sports Medicine | 2016 | Q2 |
Orthopedics and Sports Medicine | 2017 | Q2 |
Orthopedics and Sports Medicine | 2018 | Q2 |
Orthopedics and Sports Medicine | 2019 | Q1 |
Orthopedics and Sports Medicine | 2020 | Q1 |
Orthopedics and Sports Medicine | 2021 | Q1 |
Orthopedics and Sports Medicine | 2022 | Q1 |
Orthopedics and Sports Medicine | 2023 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 1999 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2000 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2001 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2002 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2003 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2004 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2005 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2006 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2007 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2008 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2009 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2010 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2011 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2012 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2013 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2014 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2015 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2016 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2017 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2018 | Q2 |
Physical Therapy, Sports Therapy and Rehabilitation | 2019 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2020 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2021 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2022 | Q1 |
Physical Therapy, Sports Therapy and Rehabilitation | 2023 | Q1 |
Sports Science | 1999 | Q2 |
Sports Science | 2000 | Q3 |
Sports Science | 2001 | Q2 |
Sports Science | 2002 | Q3 |
Sports Science | 2003 | Q3 |
Sports Science | 2004 | Q3 |
Sports Science | 2005 | Q3 |
Sports Science | 2006 | Q2 |
Sports Science | 2007 | Q2 |
Sports Science | 2008 | Q2 |
Sports Science | 2009 | Q2 |
Sports Science | 2010 | Q3 |
Sports Science | 2011 | Q2 |
Sports Science | 2012 | Q2 |
Sports Science | 2013 | Q2 |
Sports Science | 2014 | Q3 |
Sports Science | 2015 | Q3 |
Sports Science | 2016 | Q3 |
Sports Science | 2017 | Q2 |
Sports Science | 2018 | Q3 |
Sports Science | 2019 | Q1 |
Sports Science | 2020 | Q1 |
Sports Science | 2021 | Q2 |
Sports Science | 2022 | Q2 |
Sports Science | 2023 | Q2 |
The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.
Year | SJR |
---|---|
1999 | 0.509 |
2000 | 0.362 |
2001 | 0.558 |
2002 | 0.417 |
2003 | 0.343 |
2004 | 0.448 |
2005 | 0.428 |
2006 | 0.656 |
2007 | 0.676 |
2008 | 0.564 |
2009 | 0.617 |
2010 | 0.572 |
2011 | 0.766 |
2012 | 0.898 |
2013 | 0.639 |
2014 | 0.562 |
2015 | 0.611 |
2016 | 0.563 |
2017 | 0.757 |
2018 | 0.708 |
2019 | 1.239 |
2020 | 1.706 |
2021 | 1.145 |
2022 | 0.931 |
2023 | 0.797 |
Evolution of the number of published documents. All types of documents are considered, including citable and non citable documents.
Year | Documents |
---|---|
1999 | 19 |
2000 | 16 |
2001 | 16 |
2002 | 31 |
2003 | 29 |
2004 | 25 |
2005 | 20 |
2006 | 28 |
2007 | 25 |
2008 | 39 |
2009 | 27 |
2010 | 28 |
2011 | 28 |
2012 | 27 |
2013 | 36 |
2014 | 27 |
2015 | 43 |
2016 | 40 |
2017 | 43 |
2018 | 51 |
2019 | 33 |
2020 | 61 |
2021 | 74 |
2022 | 42 |
2023 | 79 |
This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric.
Cites per document | Year | Value |
---|---|---|
Cites / Doc. (4 years) | 1999 | 0.795 |
Cites / Doc. (4 years) | 2000 | 0.608 |
Cites / Doc. (4 years) | 2001 | 0.880 |
Cites / Doc. (4 years) | 2002 | 0.974 |
Cites / Doc. (4 years) | 2003 | 0.512 |
Cites / Doc. (4 years) | 2004 | 0.793 |
Cites / Doc. (4 years) | 2005 | 0.970 |
Cites / Doc. (4 years) | 2006 | 2.067 |
Cites / Doc. (4 years) | 2007 | 1.010 |
Cites / Doc. (4 years) | 2008 | 1.592 |
Cites / Doc. (4 years) | 2009 | 1.071 |
Cites / Doc. (4 years) | 2010 | 1.235 |
Cites / Doc. (4 years) | 2011 | 2.109 |
Cites / Doc. (4 years) | 2012 | 1.770 |
Cites / Doc. (4 years) | 2013 | 1.591 |
Cites / Doc. (4 years) | 2014 | 1.277 |
Cites / Doc. (4 years) | 2015 | 1.458 |
Cites / Doc. (4 years) | 2016 | 1.617 |
Cites / Doc. (4 years) | 2017 | 1.856 |
Cites / Doc. (4 years) | 2018 | 2.118 |
Cites / Doc. (4 years) | 2019 | 2.458 |
Cites / Doc. (4 years) | 2020 | 3.826 |
Cites / Doc. (4 years) | 2021 | 3.894 |
Cites / Doc. (4 years) | 2022 | 3.521 |
Cites / Doc. (4 years) | 2023 | 2.824 |
Cites / Doc. (3 years) | 1999 | 0.795 |
Cites / Doc. (3 years) | 2000 | 0.618 |
Cites / Doc. (3 years) | 2001 | 0.885 |
Cites / Doc. (3 years) | 2002 | 0.824 |
Cites / Doc. (3 years) | 2003 | 0.476 |
Cites / Doc. (3 years) | 2004 | 0.737 |
Cites / Doc. (3 years) | 2005 | 0.906 |
Cites / Doc. (3 years) | 2006 | 1.865 |
Cites / Doc. (3 years) | 2007 | 1.096 |
Cites / Doc. (3 years) | 2008 | 1.247 |
Cites / Doc. (3 years) | 2009 | 0.902 |
Cites / Doc. (3 years) | 2010 | 1.121 |
Cites / Doc. (3 years) | 2011 | 2.053 |
Cites / Doc. (3 years) | 2012 | 1.578 |
Cites / Doc. (3 years) | 2013 | 1.193 |
Cites / Doc. (3 years) | 2014 | 1.099 |
Cites / Doc. (3 years) | 2015 | 1.256 |
Cites / Doc. (3 years) | 2016 | 1.462 |
Cites / Doc. (3 years) | 2017 | 1.745 |
Cites / Doc. (3 years) | 2018 | 1.825 |
Cites / Doc. (3 years) | 2019 | 2.396 |
Cites / Doc. (3 years) | 2020 | 3.787 |
Cites / Doc. (3 years) | 2021 | 3.524 |
Cites / Doc. (3 years) | 2022 | 2.714 |
Cites / Doc. (3 years) | 2023 | 2.633 |
Cites / Doc. (2 years) | 1999 | 0.895 |
Cites / Doc. (2 years) | 2000 | 0.600 |
Cites / Doc. (2 years) | 2001 | 0.371 |
Cites / Doc. (2 years) | 2002 | 0.781 |
Cites / Doc. (2 years) | 2003 | 0.447 |
Cites / Doc. (2 years) | 2004 | 0.683 |
Cites / Doc. (2 years) | 2005 | 0.704 |
Cites / Doc. (2 years) | 2006 | 1.622 |
Cites / Doc. (2 years) | 2007 | 0.646 |
Cites / Doc. (2 years) | 2008 | 1.189 |
Cites / Doc. (2 years) | 2009 | 0.781 |
Cites / Doc. (2 years) | 2010 | 1.045 |
Cites / Doc. (2 years) | 2011 | 1.491 |
Cites / Doc. (2 years) | 2012 | 1.411 |
Cites / Doc. (2 years) | 2013 | 0.745 |
Cites / Doc. (2 years) | 2014 | 1.000 |
Cites / Doc. (2 years) | 2015 | 1.063 |
Cites / Doc. (2 years) | 2016 | 1.243 |
Cites / Doc. (2 years) | 2017 | 1.386 |
Cites / Doc. (2 years) | 2018 | 1.807 |
Cites / Doc. (2 years) | 2019 | 1.979 |
Cites / Doc. (2 years) | 2020 | 3.750 |
Cites / Doc. (2 years) | 2021 | 2.606 |
Cites / Doc. (2 years) | 2022 | 2.333 |
Cites / Doc. (2 years) | 2023 | 2.595 |
Evolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years. Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal.
Cites | Year | Value |
---|---|---|
Self Cites | 1999 | 22 |
Self Cites | 2000 | 16 |
Self Cites | 2001 | 12 |
Self Cites | 2002 | 19 |
Self Cites | 2003 | 6 |
Self Cites | 2004 | 12 |
Self Cites | 2005 | 26 |
Self Cites | 2006 | 22 |
Self Cites | 2007 | 17 |
Self Cites | 2008 | 25 |
Self Cites | 2009 | 16 |
Self Cites | 2010 | 12 |
Self Cites | 2011 | 13 |
Self Cites | 2012 | 20 |
Self Cites | 2013 | 25 |
Self Cites | 2014 | 17 |
Self Cites | 2015 | 18 |
Self Cites | 2016 | 24 |
Self Cites | 2017 | 49 |
Self Cites | 2018 | 42 |
Self Cites | 2019 | 35 |
Self Cites | 2020 | 52 |
Self Cites | 2021 | 53 |
Self Cites | 2022 | 34 |
Self Cites | 2023 | 85 |
Total Cites | 1999 | 62 |
Total Cites | 2000 | 47 |
Total Cites | 2001 | 54 |
Total Cites | 2002 | 42 |
Total Cites | 2003 | 30 |
Total Cites | 2004 | 56 |
Total Cites | 2005 | 77 |
Total Cites | 2006 | 138 |
Total Cites | 2007 | 80 |
Total Cites | 2008 | 91 |
Total Cites | 2009 | 83 |
Total Cites | 2010 | 102 |
Total Cites | 2011 | 193 |
Total Cites | 2012 | 131 |
Total Cites | 2013 | 99 |
Total Cites | 2014 | 100 |
Total Cites | 2015 | 113 |
Total Cites | 2016 | 155 |
Total Cites | 2017 | 192 |
Total Cites | 2018 | 230 |
Total Cites | 2019 | 321 |
Total Cites | 2020 | 481 |
Total Cites | 2021 | 511 |
Total Cites | 2022 | 456 |
Total Cites | 2023 | 466 |
Evolution of the number of total citation per document and external citation per document (i.e. journal self-citations removed) received by a journal's published documents during the three previous years. External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents.
Cites | Year | Value |
---|---|---|
External Cites per document | 1999 | 0.513 |
External Cites per document | 2000 | 0.408 |
External Cites per document | 2001 | 0.689 |
External Cites per document | 2002 | 0.451 |
External Cites per document | 2003 | 0.381 |
External Cites per document | 2004 | 0.579 |
External Cites per document | 2005 | 0.600 |
External Cites per document | 2006 | 1.568 |
External Cites per document | 2007 | 0.863 |
External Cites per document | 2008 | 0.904 |
External Cites per document | 2009 | 0.728 |
External Cites per document | 2010 | 0.989 |
External Cites per document | 2011 | 1.915 |
External Cites per document | 2012 | 1.337 |
External Cites per document | 2013 | 0.892 |
External Cites per document | 2014 | 0.912 |
External Cites per document | 2015 | 1.056 |
External Cites per document | 2016 | 1.236 |
External Cites per document | 2017 | 1.300 |
External Cites per document | 2018 | 1.492 |
External Cites per document | 2019 | 2.134 |
External Cites per document | 2020 | 3.378 |
External Cites per document | 2021 | 3.159 |
External Cites per document | 2022 | 2.512 |
External Cites per document | 2023 | 2.153 |
Cites per document | 1999 | 0.795 |
Cites per document | 2000 | 0.618 |
Cites per document | 2001 | 0.885 |
Cites per document | 2002 | 0.824 |
Cites per document | 2003 | 0.476 |
Cites per document | 2004 | 0.737 |
Cites per document | 2005 | 0.906 |
Cites per document | 2006 | 1.865 |
Cites per document | 2007 | 1.096 |
Cites per document | 2008 | 1.247 |
Cites per document | 2009 | 0.902 |
Cites per document | 2010 | 1.121 |
Cites per document | 2011 | 2.053 |
Cites per document | 2012 | 1.578 |
Cites per document | 2013 | 1.193 |
Cites per document | 2014 | 1.099 |
Cites per document | 2015 | 1.256 |
Cites per document | 2016 | 1.462 |
Cites per document | 2017 | 1.745 |
Cites per document | 2018 | 1.825 |
Cites per document | 2019 | 2.396 |
Cites per document | 2020 | 3.787 |
Cites per document | 2021 | 3.524 |
Cites per document | 2022 | 2.714 |
Cites per document | 2023 | 2.633 |
International Collaboration accounts for the articles that have been produced by researchers from several countries. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address.
Year | International Collaboration |
---|---|
1999 | 15.79 |
2000 | 6.25 |
2001 | 12.50 |
2002 | 6.45 |
2003 | 13.79 |
2004 | 24.00 |
2005 | 5.00 |
2006 | 32.14 |
2007 | 12.00 |
2008 | 87.18 |
2009 | 25.93 |
2010 | 14.29 |
2011 | 7.14 |
2012 | 7.41 |
2013 | 22.22 |
2014 | 37.04 |
2015 | 20.93 |
2016 | 30.00 |
2017 | 18.60 |
2018 | 37.25 |
2019 | 36.36 |
2020 | 18.03 |
2021 | 28.38 |
2022 | 23.81 |
2023 | 29.11 |
Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.
Documents | Year | Value |
---|---|---|
Non-citable documents | 1999 | 0 |
Non-citable documents | 2000 | 0 |
Non-citable documents | 2001 | 0 |
Non-citable documents | 2002 | 0 |
Non-citable documents | 2003 | 3 |
Non-citable documents | 2004 | 7 |
Non-citable documents | 2005 | 10 |
Non-citable documents | 2006 | 7 |
Non-citable documents | 2007 | 5 |
Non-citable documents | 2008 | 5 |
Non-citable documents | 2009 | 9 |
Non-citable documents | 2010 | 12 |
Non-citable documents | 2011 | 13 |
Non-citable documents | 2012 | 12 |
Non-citable documents | 2013 | 11 |
Non-citable documents | 2014 | 10 |
Non-citable documents | 2015 | 9 |
Non-citable documents | 2016 | 8 |
Non-citable documents | 2017 | 8 |
Non-citable documents | 2018 | 8 |
Non-citable documents | 2019 | 7 |
Non-citable documents | 2020 | 6 |
Non-citable documents | 2021 | 5 |
Non-citable documents | 2022 | 5 |
Non-citable documents | 2023 | 5 |
Citable documents | 1999 | 78 |
Citable documents | 2000 | 76 |
Citable documents | 2001 | 61 |
Citable documents | 2002 | 51 |
Citable documents | 2003 | 60 |
Citable documents | 2004 | 69 |
Citable documents | 2005 | 75 |
Citable documents | 2006 | 67 |
Citable documents | 2007 | 68 |
Citable documents | 2008 | 68 |
Citable documents | 2009 | 83 |
Citable documents | 2010 | 79 |
Citable documents | 2011 | 81 |
Citable documents | 2012 | 71 |
Citable documents | 2013 | 72 |
Citable documents | 2014 | 81 |
Citable documents | 2015 | 81 |
Citable documents | 2016 | 98 |
Citable documents | 2017 | 102 |
Citable documents | 2018 | 118 |
Citable documents | 2019 | 127 |
Citable documents | 2020 | 121 |
Citable documents | 2021 | 140 |
Citable documents | 2022 | 163 |
Citable documents | 2023 | 172 |
Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year.
Documents | Year | Value |
---|---|---|
Uncited documents | 1999 | 43 |
Uncited documents | 2000 | 48 |
Uncited documents | 2001 | 31 |
Uncited documents | 2002 | 22 |
Uncited documents | 2003 | 45 |
Uncited documents | 2004 | 43 |
Uncited documents | 2005 | 47 |
Uncited documents | 2006 | 27 |
Uncited documents | 2007 | 37 |
Uncited documents | 2008 | 27 |
Uncited documents | 2009 | 46 |
Uncited documents | 2010 | 42 |
Uncited documents | 2011 | 29 |
Uncited documents | 2012 | 32 |
Uncited documents | 2013 | 37 |
Uncited documents | 2014 | 41 |
Uncited documents | 2015 | 37 |
Uncited documents | 2016 | 41 |
Uncited documents | 2017 | 35 |
Uncited documents | 2018 | 38 |
Uncited documents | 2019 | 43 |
Uncited documents | 2020 | 14 |
Uncited documents | 2021 | 24 |
Uncited documents | 2022 | 40 |
Uncited documents | 2023 | 37 |
Cited documents | 1999 | 35 |
Cited documents | 2000 | 28 |
Cited documents | 2001 | 30 |
Cited documents | 2002 | 29 |
Cited documents | 2003 | 18 |
Cited documents | 2004 | 33 |
Cited documents | 2005 | 38 |
Cited documents | 2006 | 47 |
Cited documents | 2007 | 36 |
Cited documents | 2008 | 46 |
Cited documents | 2009 | 46 |
Cited documents | 2010 | 49 |
Cited documents | 2011 | 65 |
Cited documents | 2012 | 51 |
Cited documents | 2013 | 46 |
Cited documents | 2014 | 50 |
Cited documents | 2015 | 53 |
Cited documents | 2016 | 65 |
Cited documents | 2017 | 75 |
Cited documents | 2018 | 88 |
Cited documents | 2019 | 91 |
Cited documents | 2020 | 113 |
Cited documents | 2021 | 121 |
Cited documents | 2022 | 128 |
Cited documents | 2023 | 140 |
Evolution of the percentage of female authors.
Year | Female Percent |
---|---|
1999 | 43.18 |
2000 | 58.82 |
2001 | 46.67 |
2002 | 36.73 |
2003 | 55.32 |
2004 | 39.22 |
2005 | 62.79 |
2006 | 40.00 |
2007 | 66.00 |
2008 | 53.45 |
2009 | 42.11 |
2010 | 31.67 |
2011 | 41.67 |
2012 | 36.07 |
2013 | 50.56 |
2014 | 44.59 |
2015 | 43.52 |
2016 | 41.74 |
2017 | 51.38 |
2018 | 39.60 |
2019 | 49.47 |
2020 | 36.22 |
2021 | 39.90 |
2022 | 42.40 |
2023 | 39.32 |
Evolution of the number of documents cited by public policy documents according to Overton database.
Documents | Year | Value |
---|---|---|
Overton | 1999 | 2 |
Overton | 2000 | 3 |
Overton | 2001 | 1 |
Overton | 2002 | 1 |
Overton | 2003 | 3 |
Overton | 2004 | 5 |
Overton | 2005 | 1 |
Overton | 2006 | 2 |
Overton | 2007 | 5 |
Overton | 2008 | 4 |
Overton | 2009 | 2 |
Overton | 2010 | 4 |
Overton | 2011 | 1 |
Overton | 2012 | 1 |
Overton | 2013 | 2 |
Overton | 2014 | 2 |
Overton | 2015 | 3 |
Overton | 2016 | 4 |
Overton | 2017 | 0 |
Overton | 2018 | 3 |
Overton | 2019 | 2 |
Overton | 2020 | 0 |
Overton | 2021 | 0 |
Overton | 2022 | 0 |
Overton | 2023 | 0 |
Evoution of the number of documents related to Sustainable Development Goals defined by United Nations. Available from 2018 onwards.
Documents | Year | Value |
---|---|---|
SDG | 2018 | 4 |
SDG | 2019 | 9 |
SDG | 2020 | 23 |
SDG | 2021 | 20 |
SDG | 2022 | 14 |
SDG | 2023 | 24 |
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Journal of Teaching in Physical Education
Number of papers | 359 |
H4-Index | |
TQCC | |
Average citations | 3.056 |
Median citations | |
Impact Factor | 1.800 (based on 2023) |
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Twitter : @ JTPEjournal (1212 followers as of 2023-11-01)
Impact Factor : 1.800 (based on Web of Science 2023)
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Can Practicum Teaching Change Preservice Physical Education Teacher Value Orientations? Qiao Zhu, Hejun Shen, Ang Chen Page: 450–459 DOI: 10.1123/jtpe.2019-0295
Open Access Affective Learning in Physical Education: A Systematic Review Eishin Teraoka, Heidi Jancer Ferreira, David Kirk, Farid Bardid Page: 460–473 DOI: 10.1123/jtpe.2019-0164
The Missing Link? Middle School Students’ Procedural Knowledge on Fitness Tan Zhang, Anqi Deng, Ang Chen Page: 474–483 DOI: 10.1123/jtpe.2019-0237
Changes in Psychosocial Perspectives Among Physical Activity Leaders: Teacher Efficacy, Work Engagement, and Affective Commitment Ann Pulling Kuhn, Russell L. Carson, Aaron Beighle, Darla M. Castelli Page: 484–492 DOI: 10.1123/jtpe.2019-0274
Barriers to Implementation of Physical Activity in Danish Public Schools Sofie Koch, Jens Troelsen, Samuel Cassar, Charlotte Skau Pawlowski Page: 493–502 DOI: 10.1123/jtpe.2019-0158
Special Series
Open Access #HealthyKidsQuarantined : Supporting Schools and Families With Virtual Physical Activity, Physical Education, and Nutrition Education During the Coronavirus Pandemic Laurel Whalen, Jeanne Barcelona, Erin Centeio, Nathan McCaughtry Page: 503–507 DOI: 10.1123/jtpe.2020-0299
Open Access Implementation and Effectiveness of a CSPAP-Informed, Online Secondary Methods Course With Virtual Field Experiences During the COVID-19 Pandemic Collin A. Webster, Jongho Moon, Hayes Bennett, Stephen Griffin Page: 508–515 DOI: 10.1123/jtpe.2020-0298
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- Published: 10 August 2024
The role of physical activity and fitness for children’s wellbeing and academic achievement
- Julia Jaekel ORCID: orcid.org/0000-0001-6123-3375 1 , 2 , 3 , 4
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It is well known that physiological, psychological, and cognitive factors contribute to children’s wellbeing and school success, but studies assessing these domains simultaneously are surprisingly rare. Visier-Alfonso et al. expand on our existing knowledge base and report different pathways to academic achievement for girls and boys. Specifically, girls with higher cardiorespiratory fitness had better psychological wellbeing, and this was associated with higher academic achievement. Boys were more academically successful if they had higher cognitive flexibility. Boys with higher cardiorespiratory fitness also had better psychological wellbeing. According to this current evidence, cardiorespiratory fitness has both direct and indirect beneficial effects beyond physical health on psychological wellbeing and academic achievement. Health practitioners, education professionals, and parents should focus on increasing opportunities for daily physical activities that will benefit children’s cardiorespiratory fitness.
In today’s world, finding a good balance between screen time and physical activity is key to child health, wellbeing, and school performance. At least that is what most health practitioners, education professionals, and parents will likely agree on. However, despite the real-life importance of these domains, there is surprisingly little scientific evidence on how they are independently and simultaneously associated with each other. Study findings of how screen time affects child development and academic outcomes at school age have been mixed, 1 , 2 especially when adjusted for families’ socio-cultural backgrounds and level of education. Visier-Alfonso et al. do not only expand on our existing knowledge base of how physiological, psychological, and cognitive factors contribute to children’s school success, they also provide new details on the strength (or their absence) of underlying associations. In their observational study of 519 school-aged children in Spain, the different domains were operationalised via well-established, reliable, multi-informant measures, e.g. cardiorespiratory fitness (CRF) was assessed with the 20-metre shuttle run test, recreational screen time use was reported by parents, psychological well-being was assessed from children themselves with the Kidscreen-27, 3 and cognitive flexibility via the computerised Dimensional Change Card Sort Test. 4 The selection and intentional combination of these measures allows a comparison of the current findings with other previous studies from different settings and world regions – a precondition for meaningful contributions to understanding developmental mechanisms.
Human development is shaped by complex multidirectional cascades over time. 5 , 6 , 7 In research, it is important to design studies that allow us to include relevant variables and constructs in one model, in order to estimate and test hypothesised associations that mirror the true complexity of development. On the contrary, if relevant constructs and their associations are not included in statistical models, researchers risk overestimating certain direct associations by neglecting others. With regard to these methodological aspects, Visier-Alfonso et al.’s study is a step forward. They demonstrate how to apply fit indices provided by structural equation and path modelling to adapt hypothesised associations to a collected data sample. This data-based model fitting process is especially helpful when a sample is large enough to provide sufficient statistical power and assumed to be representative of a population.
Accordingly, Visier-Alfonso et al. report different pathways from CRF to academic achievement by biological sex, suggesting intriguing differences between girls and boys. Specifically, girls with higher CRF reported better psychological wellbeing, and this was associated with higher academic achievement. Boys, on the other hand, were more academically successful if they had higher cognitive flexibility. In addition, the authors report a total negative effect of screen time on academic achievement among boys, however it is small and only marginally significant. Boys with higher CRF also had better psychological wellbeing, but there were no associations of these variables with their academic achievement. These sex differences in associations between domains may be partly influenced by the current sample’s descriptive differences: on average, boys used screens more often and were more fit, but they had lower cognitive flexibility than girls. While these sex differences in mean values are in line with many other studies worldwide, the current results of different mechanisms still need replication in other samples and populations.
The oldest participants in the sample were 11 years at the time of data collection - on the cusp of adolescence. The fundamental hormonal and neurodevelopmental changes they will be undergoing throughout puberty will shape their physiological, psychological, and cognitive characteristics, and indirectly affect their future academic performance. Because of these changes, puberty represents a critical time of transition with a window of risk but also of opportunity: to set individuals on healthy trajectories of wellbeing and academic success. Visier-Alfonso et al.’s study provides pointers for some of the underlying mechanisms that may be changed through intervention during late childhood. The primary years of formal schooling trigger challenges for all children across multiple areas, including the expectation to pay attention and sit still for long periods of time, inhibit unwanted behaviours, and to self-regulate their own emotions, for example. 8 , 9 In educational and developmental psychology research, children’s CRF, physical activity, and motor skills have traditionally been paid little attention to. 10 , 11 However, these domains play an important role as part of the typical developmental cascades shaping preschool and early school age. 12 , 13 Accordingly, in recent years, there has been a growing awareness of the critical role of visual-motor coordination and circumscribed motor coordination disorders, referred to as Developmental Coordination Disorder (DCD), 14 , 15 , 16 as well as childhood obesity. 17 Motor skills develop along a continuum in close association with other domains such as executive functions and social behaviour. For instance, coordination, balance, and handwriting involve complex skills 15 , 18 , 19 and are part of everyday activities at school. Difficulties with holding and moving a pencil, putting on shoes during lesson breaks, or clumsiness in group-based games can impact school performance and social participation. Not surprisingly, children’s motor abilities have been found to affect their self-esteem, well-being, acceptance by peers, and academic achievement. 18 , 20 , 21 In the context of the current findings, CRF may be an indicator of children’s day-to-day levels of physical activity, which are not only paramount for motor skills and overall health but also play an important role in social interactions and inclusion in games among children. In Visier-Alfonso et al.’s models, the one and only stable and significant association across both sexes is the path from CRF to psychological wellbeing. This underscores that physical activity is universally foundational for participation and peer acceptance at school age, and thereby affects trajectories of long-term academic success and wellbeing.
After a close look at Visier-Alfonso et al.’s findings, the main takeaway is perhaps that health practitioners, education professionals, and parents should stress less about limiting screen time and instead focus on increasing opportunities for daily physical activities that will benefit children’s CRF. According to the current evidence, better CRF then has both direct and indirect beneficial effects beyond physical health on today’s children’s psychological wellbeing and academic achievement.
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Julia Jaekel
Department of Psychology, University of Copenhagen, Copenhagen, Denmark
Department of Paediatrics I, Neonatology, Paediatric Intensive Care, Paediatric Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
Department of Psychology, University of Warwick, Coventry, UK
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Jaekel, J. The role of physical activity and fitness for children’s wellbeing and academic achievement. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03467-y
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The role of the physical education and sports teacher in selecting newly transferred sports talents from the primary level and directing them (A field study in the middle schools of the southern Sétif province)
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This study examines the essential role of physical education and sports teachers in identifying and nurturing young sports talents. Using both theoretical research and a field survey, the findings reveal that these educators play a crucial role in directing young athletes towards specific sports, thanks to their specialized skills and observational acumen. The immediate and early guidance provided by these teachers significantly enhances the development of young talents.
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‘Are You Man Or A Woman?’: Physical Education Teacher In Tamil Nadu Beats Up Students Over Poor Show In Football Match; Viral Video
The teacher, identified as annamalai, was caught on camera slapping, kicking, and pulling the hair of players..
A disturbing visual from Salem district in Tamil Nadu is making rounds on social media in which physical education was caught beating football players after being dissatisfied with their performance in the match. The incident occurred at a government-aided school near Mettur in the Salem district. The football team from NHSS took part in the competition but did not meet expectations.
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The teacher, identified as Annamalai, was caught on camera slapping, kicking, and pulling the hair of players. A parent of one of the players reported that Annamalai reacted angrily by striking the boys.
In the video, Annamalai can be heard asking to one of the students in the video, apparently the goalkeeper of the team, "Are you a man or a woman? How can you let him score,How did you let the ball get past you,". He questioned another student, adding, "Can't you play under pressure. Why was there no communication," . Here's how netizens reacted to the action of physical teacher
Following the video's circulation, the Sangagiri District Education Officer launched an investigation Subsequently, the DEO submitted his findings to both the department and the district collector. Annamalai was suspended for his action.
Disclaimer: The translation is not verbatim
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Physical Education Teachers’ Experiences With Remote Instruction During the Initial Phase of the COVID-19 Pandemic
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This study investigated physical education (PE) teachers’ experiences with remote instruction in the United States during the initial outbreak of COVID-19. PE teachers ( n = 4,362) from all 50 states completed a survey identifying their experiences with remote instruction in May, 2020. Survey responses were analyzed by geographic region, district type, and school level. Teachers reported having students submit assignments (51% yes), using video instruction (37% yes), being less effective when instructing remotely (20% yes), and emphasizing student outcomes focused on health-related fitness (32% yes), and physical activity value/enjoyment (43% yes). Access to technology (40% yes) and required student assignments (43% yes) were lowest among teachers from the South. Rural teachers reported the least access to technology (37% yes) and rated themselves as least effective (24% yes). Secondary level teachers reported the highest percentage of required assignments (84% yes). Teachers’ responses identify unique challenges to delivering equitable and effective remote PE instruction.
In spring 2020, the COVID-19 pandemic forced the majority of school instruction, including physical education (PE) to be delivered remotely. Prior to COVID-19, quality PE programs, whether in-person or remote, exhibited certain characteristics designed to promote student learning outcomes. SHAPE America sees these characteristics as the essential components of PE, which include policy and environment, curriculum, appropriate instruction, and student assessment ( SHAPE America, 2015 ). Research on effective or quality instruction in PE, aligned with student learning outcomes and promoting achievement of standards has been presented (i.e., Rink, 2013 ). In the United States, National Standards for PE guide programs in helping students meet SHAPE America’s stated goal of assisting students in gaining the knowledge, skills, and confidence to enjoy a lifetime of healthful physical activity (PA; SHAPE America, 2013 ). In-person PE is the context for the overwhelming majority of the research and commentary on effective teaching to promote student learning outcomes.
During the almost overnight switch to remote instruction resulting from the COVID-19 pandemic, in many cases, teachers used trial and error methods in implementing remote instruction ( Jeong & So, 2020 ). As a marginalized subject area, PE teachers are often left alone to figure out how to implement quality PE without support ( Richards, Gaudreault, Starck, & Woods, 2018 ). It is reasonable to assume that the pandemic further isolated PE teachers and forced them to make decisions influencing student learning outcomes.
The PE has long been touted as an ideal setting to address public health concerns ( Sallis & McKenzie, 1991 ; Sallis et al., 2012 ). Shelter-at-home measures, the closures of gyms and public spaces, and physical distancing measures created new challenges, especially for children, to remain physically active and acquire health-related fitness benefits ( Dunton, Do, & Wang, 2020 ) aligned with SHAPE America National Standard 3—knowledge and skills to achieve and maintain a health-enhancing level of PA and fitness. PA aids in the prevention of many chronic conditions, including obesity and Type 2 diabetes, that lead to an increased risk of severe infections or mortality associated with COVID-19 ( Centers for Disease Control and Prevention, 2020a ; Jordan, Adab, & Cheng, 2020 ; Sallis, Adlakha, Oyeyemi, & Salvo, 2020 ; World Health Organization, 2020 ). It is important to combat the negative health consequences of physical inactivity and strengthen the immune system by engaging in regular moderate to vigorous PA ( Nieman, 2020 ).
Several of the first reported studies examining the impact of the COVID-19 pandemic on children’s PA levels present interesting findings. Short-term studies in the United States and China documented decreased levels of PA during stay-at-home orders and school closures ( Dunton et al., 2020 ; Xiang, Zhang, & Kuwahara, 2020 ). A simulation study assessing the impact of school closures and lost PA time in PE projected increases in childhood obesity, with significant race and gender differences, and called for public health interventions ( An, 2020 ). Collectively, these studies, along with the identified benefits of regular PA, strongly suggest a public health need for a focus on children’s PA during the COVID-19 pandemic.
As an often less prioritized subject area ( Kougioumtzis, Patriksson, & Stråhlman, 2011 ), planning and implementing PE during this pandemic most likely fell to the PE teachers themselves. Though eager to deliver positive experiences, PE teachers indicated they felt unprepared and desired assistance in learning about best practices for delivering remote instruction ( SHAPE America, 2020 ). Little is known, however, regarding how PE teachers experienced the COVID-19 pandemic-initiated national switch to remote instruction and how these experiences affected PE programs’ attempts to deliver effective instruction aimed at positive student learning outcomes.
The purpose of this study was to understand PE teachers’ experiences with remote instruction in PE across the United States during the initial outbreak of the COVID-19 pandemic. Specifically, this study investigated whether teachers used assignments, whether students’ had access to technology for learning, whether teachers used video for instruction, how effective teachers perceived their remote teaching to be in comparison with their in-person instruction, and which national content standards teachers prioritized. A secondary purpose of the study was to explore associations between these elements of remote instruction and school context characteristics, including grade level, urbanicity, and region of the United States. The term remote instruction will be used in this paper to describe teacher-led PE experiences including virtual lecture or activity classes (synchronous or asynchronous), online assignments (through e-mail or platforms, such as Google Classroom or Blackboard), or hard copy lessons/assignments that were mailed home or picked-up at school.
A total of 4,362 PE teachers participated in the study with 52% representing elementary, 25% secondary, and 23% reported teaching multilevel. Multilevel was any combination that spanned across both the elementary (K–5) and secondary (6–12) grade bands. A strong, varied representation of the type of districts that teachers’ taught in was reported (urban 42%, suburban 35%, and rural 23%). Finally, 23% of teachers taught in the Northeast region of the United States, 25% in the Midwest, 32% in the South, and 20% from the West.
- Data Collection
Secondary data analysis was conducted using data from the Online Physical Education Network (OPEN) www.openphyed.org. Established in March, 2015, OPEN provides free online standards-based PE curricula to meet the needs of physical educators. During the emergence of COVID-19 in the United States, in spring 2020, OPEN provided free weekly PE content for teachers that focused on getting children active while at home. As part of a desire to better understand the needs of the teachers who were using their free resources, OPEN conducted a needs assessment survey in order to guide their content development planning for the start of the school year in the fall. As of May 31, 2020, the OPEN database indicated 83,988 registered users (people who sign up for free access to content and e-mail notices).
Using Google Forms, a link to the survey was distributed in the weekly newsletters with the header “Tell us what you need: Together we will get through this.” The link was included in the newsletter for a 2-week period in May, 2020. The users on the OPEN platform consisted of teachers, parents, administrators, higher education faculty, preservice teachers, as well as other groups, but only teachers who identified as teaching PE remotely in a K–12 setting were included for the current study.
The survey did not collect basic demographic data of teachers (i.e., age, gender), as it was developed to better understand how teachers were currently using the curriculum and how OPEN could make improvements in their resources for the future. The survey consisted of items, such as grade level taught, state, type of district, level of teaching, as well as questions that focused on their current remote instruction teaching situation and environment, school’s plan for fall 2020, along with teaching and planning priorities. Survey items not aligned with the identified variables of interest were not included in data analysis. Survey items included several types of response options including Likert-type scales, multiple selection, yes/no, and open-ended responses.
Institutional review board approval was received to conduct secondary data analysis from State University of New York at Cortland. Initial deidentified data were downloaded from Google Forms and supplied to the researchers in Google Sheets. Cleaning of data was conducted using gspread (a python application programming interface for google Sheets) and consisted of removing survey responses from those individuals who were not K–12 PE teachers as well as those who started, but did not complete surveys. Data were then downloaded and transferred into Excel. Variables were coded (i.e., categorical or binary) based on purpose and research question. For example, access to technology was given a binary code. Data for the state in which participants taught were categorized by state using the two-letter abbreviation, and then further categorized into four regions based on the Centers for Disease Control and Prevention information for COVID-19 ( Centers for Disease Control and Prevention, 2020b ).
- Data Analysis
Descriptive statistics were used to provide basic information on independent variables including district type, region, and grade level taught and dependent variables including learning standard priority, submission of assignments, access to technology, use of video, and self-rating of effectiveness. All independent variables were categorical in nature. District type had three levels including rural, suburban, and urban. Region had four levels including Northeast, Midwest, South, and West. Grade level taught had three levels including elementary, secondary, and multilevel (e.g., K–12, K–8, 6–12). Dependent variables were binary except for learning standard priority, which had five classifications (i.e., SHAPE America Standards 1–5) and asked which standards do you prioritize in your remote instruction. Binary codes were as follows: (a) Are your students required to submit any assignments or artifacts of learning? (yes = 1, no = 0), (b) Do all of your students have access to the technology required to effectively learn in a distance learning environment? (yes = 1, no = 0), (c) Do you use live or recorded video in your remote teaching? (yes = 1, no = 0), and (d) How effective has your remote PE teaching been? (1 = less effective, 0 = as/more effective).
We performed chi-square tests in order to test for associations between levels of each independent variable and teachers who prioritized specific national learning standards. Binary logistic regression models were used for the remaining dependent variables. All independent variables were included as predictors using a dummy variable approach in each model ( Tabachnick & Fidell, 2019 ). We used the Wald test (i.e., unstandardized beta/ SE ) with an alpha level of .05 to determine statistical significance ( Forthofer, Lee, & Hernandez, 2007 ). Odds ratios with 95% confidence intervals were used to describe relationships between independent and dependent variables.
The percentage of “yes” responses for the outcome variables by geographic region, type of school, and level of teaching are presented in Table 1 . Nation content standards of priority by region, type, and level are presented in Table 2 . Just over half of the teachers suggested they required assignments from their students during the COVID-19 stay-at-home period. Teachers also reported that approximately half of their students had “access to the technology required to effectively learn in a distance learning environment.” Only 37% of teachers reported that students were required to use video for teaching and learning purposes. Despite these barriers, 80% of the teachers reported their teaching as being “as effective or more effective” during the COVID-19 stay at home period. Finally, a majority of teachers prioritized getting students to value and enjoy PA (SHAPE America Standard 5, 43%) or develop skills and knowledge related to health-related fitness and health-enhancing PA (SHAPE America Standard 3, 32%).
Descriptive Statistics for Binary Outcome Variables
Variable | Assignments, yes (%) | Technology, yes (%) | Video, yes (%) | Less effective, yes (%) |
---|---|---|---|---|
Grade level | ||||
Elementary | 34 | 45 | 35 | 21 |
Secondary | 84 | 52 | 38 | 17 |
Multilevel | 55 | 55 | 42 | 21 |
Total | 51 | 49 | 37 | 20 |
Region | ||||
Northeast | 62 | 61 | 41 | 16 |
Midwest | 52 | 49 | 33 | 24 |
South | 43 | 40 | 38 | 17 |
West | 50 | 53 | 36 | 26 |
Total | 51 | 49 | 37 | 20 |
District type | ||||
Rural | 50 | 37 | 29 | 24 |
Suburban | 50 | 63 | 40 | 20 |
Urban | 53 | 45 | 40 | 18 |
Total | 51 | 49 | 37 | 20 |
Note. Assignments = percentage of teachers who required students to turn in assignments; technology = percentage of teachers who suggested their students had access to technology; video = percentage of teachers who required students to use video for PE; less effective = percentage of teachers who reported they were less effective at teaching their PE classes; PE = physical education.
Descriptive Statistics for Physical Education National Content Standard Prioritization
Variable | Standard 1 (%) | Standard 2 (%) | Standard 3 (%) | Standard 4 (%) | Standard 5 (%) |
---|---|---|---|---|---|
Grade level | |||||
Elementary | 13 | 3 | 28 | 14 | 42 |
Secondary | 3 | 3 | 42 | 9 | 43 |
Multilevel | 10 | 4 | 31 | 11 | 44 |
Total | 10 | 3 | 32 | 12 | 43 |
Region | |||||
Northeast | 9 | 3 | 30 | 15 | 43 |
Midwest | 11 | 3 | 33 | 11 | 42 |
South | 10 | 3 | 32 | 13 | 42 |
West | 10 | 3 | 33 | 10 | 44 |
Total | 10 | 3 | 32 | 12 | 43 |
District type | |||||
Rural | 11 | 2 | 31 | 11 | 45 |
Suburban | 9 | 4 | 32 | 11 | 44 |
Urban | 10 | 3 | 33 | 13 | 41 |
Total | 10 | 3 | 32 | 12 | 43 |
Results from the chi-square tests revealed associations between content standards and district type, χ 2 (8) = 16.39, p = .04, grade level taught, χ 2 (8) = 156.59, p = .001, but not region χ 2 (12) = 17.21, p = .14. Urban teachers were more likely than rural and suburban teachers to prioritize Standard 4. Rural teachers were more likely than urban and suburban teachers to prioritize Standard 1 and more likely than urban teachers to prioritize Standard 5. Elementary teachers were more likely than secondary teachers to prioritize Standards 1 and 4; whereas, secondary teachers were more likely than elementary teachers to prioritize Standard 3.
Results from the four binary logistical regression models are presented in Table 3 including unstandardized beta coefficients and odds ratios with 95% confidence intervals. In Model 1, teachers from secondary schools were 10 times more likely to require assignments compared with elementary teachers. Teachers from the Northeast and from urban schools were also more likely to require their students to turn in assignments. In terms of students having access to technology, suburban school districts, teaching secondary students, or teaching in the Northeast increased the odds of increased access to technology. Urban and suburban teachers were more likely to require use of video. Increased odds of requiring students to use video as part of their PE during the remote instruction was also present for teachers teaching multiple grade levels. Finally, teachers from rural school districts, elementary teachers, and those from Midwest and West regions had greater odds of self-reporting their teaching to be less effective during the stay-at-home period.
Results From Binary Logistic Regression Models
Mode 1: Assignments | Model 2: Technology | Model 3: Video | Model 4: Less effective | |||||
---|---|---|---|---|---|---|---|---|
Variable | ( ) | OR [95% CIs] | ( ) | OR [95% CIs] | ( ) | OR [95% CIs] | ( ) | OR [95% CIs] |
District type | ||||||||
Urban | 0.18 (0.09)* | 1.20 [1.01, 1.42] | 0.39 (0.08)** | 1.47 [1.25, 1.73] | 0.48 (0.08)** | 1.61 [1.36, 1.91] | −0.10 (0.09) | 0.90 [0.76, 1.08] |
Suburban | 0.03 (0.09) | 1.03 [0.86, 1.23] | 1.13 (0.09)** | 3.08 [2.60, 3.65] | 0.48 (0.09)** | 1.62 [1.36, 1.91] | CG | 1.24 [1.02, 1.51] |
Rural | CG | CG | CG | 0.22 (0.10)* | ||||
Region | ||||||||
Northeast | 0.67 (0.09)** | 1.96 [1.64, 2.35] | 0.78 (0.09)** | 2.18 [1.84, 2.59] | 0.09 (0.08) | 1.09 [0.93, 1.30] | −0.05 (0.11) | 0.95 [0.76, 1.19] |
Midwest | 0.27 (0.09)** | 1.32 [1.10, 1.57] | 0.38 (0.08)** | 1.46 [1.23, 1.72] | −0.22 (0.08)* | 0.81 [0.68, 0.95] | 0.42 (0.10)** | 1.53 [1.25, 1.87] |
South | CG | CG | CG | CG | ||||
West | 0.01 (0.10) | 1.01 [0.84, 1.22] | 0.47 (0.09)** | 1.60 [1.34, 1.91] | −0.14 (0.09) | 0.87 [0.73, 1.04] | 0.59 (0.11)** | 1.80 [1.46, 2.22] |
Grade level | ||||||||
Elementary | CG | CG | CG | 0.27 (0.10)** | 1.31 [1.08, 1.60] | |||
Secondary | 2.31 (0.09)** | 10.05 [8.36, 12.09] | 0.22 (0.08)** | 1.25 [1.07, 1.45] | 0.13 (0.08) | 1.13 [0.97, 1.32] | CG | |
Multilevel | 0.84 (0.08)** | 2.31 [1.98, 2.70] | 0.41 (0.08)** | 1.51 [1.30, 1.76] | 0.38 (0.08)** | 1.46 [1.25, 1.70] | 0.19 (0.11) | 1.21 [0.97, 1.51] |
Note. b = unstandardized beta coefficient; OR = odds ratio; CIs = confidence intervals; CG = independent variable used as the comparison group in dummy variable coding system.
* p < .05. ** p < .01.
The current investigation examined the experiences with remote instruction of PE teachers in the United States during the initial outbreak of COVID-19. The robust and diverse study sample provides information describing how teachers from different types of schools, in different regions, and at different school levels dealt with the challenges of switching to remote instruction during the COVID-19 pandemic while attempting to still deliver quality PE. Understanding PE teachers’ remote instruction is crucial because it is unclear how long these practices will be in place. Our findings revealed that teachers’ remote PE instruction experiences varied by the types of schools they worked in, regions of the United States their schools were located, and the school level they taught. These differences are important to acknowledge and address when attempting to help teachers deliver equitable and effective remote PE instruction.
The PE teachers reported having students submit assignments (51% yes) and using video in their instruction (37% yes). Online assignment submissions and video instruction within our sample indicate the use of technology in PE during the onset of the pandemic. Research prior to the COVID-19 pandemic suggests many PE teachers feel unprepared to use technology ( Casey, Goodyear, & Armour, 2017 ). In spring 2020, use of technology for remote instruction was, in essence, required for all PE teachers, with little to no time for training. The large number of responses to the OPEN survey, combined with the SHAPE America survey results, where teachers wanted assistance with remote instruction ( SHAPE America, 2020 ) strongly suggests a desire by PE teachers for additional training to become more effective remote instructors. It is important for future research to identify what types of professional development prove successful in training teachers in delivering quality remote PE instruction. This study begins to shed light on the areas in which teachers need additional training as well as where current inequities by school type, region, and level, exist.
Teachers were asked to self-rate their effectiveness when teaching remotely, with the intent of trying to better understand their efficacy toward implementing PE during the pandemic. Only about 20% of teachers reported that they were less effective teaching students online during the pandemic. We expected this number to be quite higher given the lack of preparedness teachers had in teaching online, coupled with the abruptness of the transition to a remote learning environment. Since this was a self-rated scale item on the survey, it is unknown what criteria teachers were using to measure their own effectiveness. Some interesting and possibly alarming questions, however, remain regarding the goals of PE teachers while teaching remotely. If half of the sample did not use assignments to measure student learning and well over half of the teachers did not use video instruction, what actually occurred in these remote PE classes? A larger, and potentially more concerning question is, with little documented instruction and less identified learning, how did 80% of these teachers rate themselves as being as effective or more effective? Documenting student learning outcomes through assessments is a staple of effective in-person PE teaching ( Rink, 2013 ) and apparently a largely missing component to PE during the onset of the pandemic.
Rural PE teachers reported the least access for their students to technology and rated themselves as least effective in their remote PE teaching. Apparent inequities in these settings led us to believe that children in rural areas received lower quality PE instruction than students in urban or suburban settings. Helping teachers, specifically those in rural settings, develop self-efficacy could aid in improving effective teaching. Teacher efficacy is linked to increased PA for children in PE ( Ernst & Pangrazi, 1999 ). With a call for public health interventions aimed at increasing PA levels of children during the pandemic ( An, 2020 ) and teachers in the current study identifying SHAPE America National Standard 3 (knowledge and skills to achieve and maintain a health-enhancing level of PA and fitness) as a focus area, it would seem appropriate to develop teacher efficacy to help teachers become more effective in achieving their identified area of focus. Observed decreases in children’s PA levels ( Dunton et al., 2020 ; Xiang et al., 2020 ), the relationship between PA and the severity of COVID-19 complications ( Centers for Disease Control and Prevention, 2020a ; World Health Organization, 2020 ), and PE’s position as a place to address public health concerns ( Sallis et al., 2012 ) further support increased work on promoting PA levels through remote PE instruction.
Access to technology and the amount of student assignments were the lowest among teachers from the South. In addition, secondary level teachers reported the highest student access to teaching and learning technology and the most student document submissions. Student assessment is a key component of quality PE programs ( SHAPE America, 2015 ) and was not highly documented within our sample, especially at the elementary level. Disparities among these variables, specifically in the South and in rural communities were identified among specific groups. Support, through training and resources, is needed so that all students receive access to quality remote PE instruction. One idea for providing this support would be to make grant funding from state or national associations available for specific groups where disparities were identified. In addition, organizations, such as OPEN, could provide professional development sessions for groups disproportionately affected by changes in PE instruction.
Teachers identified a focus on SHAPE America National Content Standard 3 (maintain a health-enhancing level of PA and fitness) and Standard 5 (recognizes the value of PA for health, enjoyment, challenge, self-expression, and/or social interaction). It appears these two national PE standards were pushed to the forefront and served as prioritized student outcomes. Though the benefits of a focus on Standards 3 and 5 are clear, a sole objective of promoting PA could be too narrow for PE. It is possible that teachers found it easier to have students complete activity logs, report their PA beliefs, and rate their PA affect compared with providing motor skill instruction. As the pandemic, and remote instruction continue, ways to meet all PE goals should be pursued.
- Limitations
One limitation of this study is that the variables measured were collected at one time point during the onset of the pandemic. With a summer to prepare, teachers and schools may have different responses to the questions posed on this survey. It would be beneficial to conduct a follow-up study to see how responses and teachers’ experiences changed with more preparation for remote instruction.
Another limitation is that results from the current study rely on the accuracy of teacher self-reporting. Future studies should look to include fidelity measures, such as a student or administrative element, to confirm the presence of findings. A final limitation is that the survey did not ask teachers to identify the types of technology used and needed for student effective remote instruction. Even with the presented limitations and suggestions for future research, the findings from this investigation yield important insights on the initial response to the pandemic from a PE teacher perspective.
The experiences of PE teachers as they switched to remote instruction during the onset of COVID-19 yielded important insights on the short and possibly long-term landscape of PE. Without the ability for physical educators to teach as they had been allowed to teach (i.e., face-to-face, shared equipment, consistent scheduled time), it is essential for teachers to identify alternative strategies to support students’ standards-based learning. Without the physical presence of the PE teacher, challenges in guiding students to engage in healthy levels of PA and fitness while fostering student enjoyment of those activities remain. Continued support for PE teachers, through professional development sessions and additional resources, especially among groups where inequities were identified, is needed as teachers adapt to leading students on a new path toward facilitating student learning in PE.
- Acknowledgments
The authors thank OPEN (openphysed.org) for supporting PE teachers and schools throughout the COVID-19 pandemic, collecting data for content development purposes, and sharing the data for this study.
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* Mercier is with Adelphi University, Garden City, NY, USA. Centeio is with the University of Hawai‘i at Mānoa, Honolulu, HI, USA. Garn is with Louisiana State University, Baton Rouge, LA, USA. Erwin is with the University of Kentucky, Lexington, KY, USA. Marttinen is with George Mason University, Fairfax, VA, USA. Foley is with the State University of New York at Cortland, Cortland, NY, USA.
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A peer-reviewed journal that publishes research and practice on physical education teaching and learning. Find the latest issue, editorial board, author guidelines, and free access articles on the web page.
The latest issue of JTPE features articles on various topics in physical education teacher education, such as professional learning communities, content knowledge, value orientations, and queer pedagogy. Read the abstracts and access the full texts of the invited paper and the research notes.
The latest issue of JTPE features articles on topics such as physical culture, learning physical activity knowledge, inclusion and diversity, flipped classroom, motor skill competence, and online professional development. It also includes a special series on the success and struggles of physical education teachers during the COVID-19 pandemic.
Scimago Journal Rankings provides information and metrics for the Journal of Teaching in Physical Education, a peer-reviewed journal endorsed by two professional associations. See the journal's scope, coverage, H-index, and quartile rankings in different categories and years.
Abstract. In Physical Education Teacher Education programs, we argue that a focus on fewer models to be taught and learned would provide time for higher competence to be attained by preservice teachers in a curriculum limited in terms of contact hours.
» In order to submit a manuscript to this journal, please read the guidelines for authors in the journal's homepage. ... » JOURNAL OF TEACHING IN PHYSICAL EDUCATION. Abbreviation: J TEACH PHYS EDUC ISSN: 0273-5024 eISSN: 1543-2769 Category: EDUCATION & EDUCATIONAL RESEARCH - SSCI
Research in physical education pedagogy has increased each year since 1995, including a small presence in education and social science journals as well as health education and medical journals ...
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MIAR provides information on the journal of teaching in physical education, such as ISSN, title, subject, indexing, evaluation and metrics. It also shows the diffusion of the journal in different citation databases and sources.
Journal of Teaching in Physical Education 40(2): 256-266. Crossref. Google Scholar. Lamb P, King G (2021) Developing the practice of preservice physical education teachers through a dyad model of lesson study. European Physical Education Review 27(4): 944-960. Crossref. ISI.
Journal of Teaching in Physical Education 33(3): 422-431. Crossref. Web of Science. Google Scholar. Kretchmar RS (2005) Teaching games for understanding and the delights of human activity. In: Griffin LL, Butler JI (Eds.), Teaching Games for Understanding, Theory, Research and Practice (pp. 119-212). Champaign, IL: Human Kinetics.
This issue features a special issue on research and development perspectives for American physical education in the 21st century, as well as articles on topics such as sport education, gender equity, and COVID-19. Read the abstracts and access the full texts of the articles online.
OOIR provides information on the impact factor, H-Index, TQCC, and other metrics of Journal of Teaching in Physical Education, a peer-reviewed journal in the field of sport sciences. See the most cited papers, impactful papers, and categories and ranks of this journal.
About this journal The purpose of the Journal of Teaching in Physical Education is to communicate national and international research and stimulate discussion, study, and critique of teaching, teacher education, and curriculum as these fields relate to physical activity in schools, communities, higher education, and sport.The journal publishes original reports of empirical studies in physical ...
Armour KM, Yelling M (2007). Effective professional development for physical education teachers: The role of informal, collaborative learning. Journal of Teaching in Physical Education. 26(2): 177-200.
About this journal The purpose of the Journal of Teaching in Physical Education is to communicate national and international research and stimulate discussion, study, and critique of teaching, teacher education, and curriculum as these fields relate to physical activity in schools, communities, higher education, and sport.The journal publishes original reports of empirical studies in physical ...
This article provides a platform for physical education teacher educators and researchers to advance OLPE in its support of both the educational and public health benefits of high-quality physical education programs. ... Citation: Journal of Teaching in Physical Education 40, 2; 10.1123/jtpe.2020-0182.
Health practitioners, education professionals, and parents should focus on increasing opportunities for daily physical activities that will benefit children's cardiorespiratory fitness.
The quality of physical education teaching is directly related to the physical and mental health of students and also related to the professional growth and development of teachers. It is an important educational practice link in the school education system. Both the implementers and participants in teaching activities are driven by the power ...
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Due to its focus on the prioritisation of personal significance of movement experiences, the promotion of meaningfulness in Physical Education (PE) has the potential to strengthen pedagogy and encourage a lifelong pursuit of physical activity (Kretchmar, 2006).This perspective comes at a time when many students cite current versions of PE as lacking relevance to their lived experiences (Ladwig ...
Background: Teacher education is a complex endeavor designed to prepare preservice teachers for the task of teaching physical education to students in K-12 schools. Yet, there is widespread criticism of teacher education outcomes within the United States and around the world. Consequently, teacher educators have been increasingly called upon to use evidence-based approaches in teacher ...
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This study investigated physical education (PE) teachers' experiences with remote instruction in the United States during the initial outbreak of COVID-19. PE teachers (n = 4,362) from all 50 states completed a survey identifying their experiences with remote instruction in May, 2020. Survey responses were analyzed by geographic region, district type, and school level. Teachers reported ...
The staffing and outsourcing of the marginalised curriculum area Health and Physical Education (HPE) has been an area of growing concern, alongside rising concerns for the decline of students' health due to increased sedentary behaviour and mental health problems, yet there has been little research attention to the staffing and delivery of HPE in Australian schools.