research skills for high school students pdf

• Research Skills

50 Mini-Lessons For Teaching Students Research Skills

Please note, I am no longer blogging and this post hasn’t updated since April 2020.

For a number of years, Seth Godin has been talking about the need to “ connect the dots” rather than “collect the dots” . That is, rather than memorising information, students must be able to learn how to solve new problems, see patterns, and combine multiple perspectives.

Solid research skills underpin this. Having the fluency to find and use information successfully is an essential skill for life and work.

Today’s students have more information at their fingertips than ever before and this means the role of the teacher as a guide is more important than ever.

You might be wondering how you can fit teaching research skills into a busy curriculum? There aren’t enough hours in the day! The good news is, there are so many mini-lessons you can do to build students’ skills over time.

This post outlines 50 ideas for activities that could be done in just a few minutes (or stretched out to a longer lesson if you have the time!).

Learn More About The Research Process

I have a popular post called Teach Students How To Research Online In 5 Steps. It outlines a five-step approach to break down the research process into manageable chunks.

This post shares ideas for mini-lessons that could be carried out in the classroom throughout the year to help build students’ skills in the five areas of: clarify, search, delve, evaluate , and cite . It also includes ideas for learning about staying organised throughout the research process.

Notes about the 50 research activities:

• These ideas can be adapted for different age groups from middle primary/elementary to senior high school.
• Many of these ideas can be repeated throughout the year.
• Depending on the age of your students, you can decide whether the activity will be more teacher or student led. Some activities suggest coming up with a list of words, questions, or phrases. Teachers of younger students could generate these themselves.
• Depending on how much time you have, many of the activities can be either quickly modelled by the teacher, or extended to an hour-long lesson.
• Some of the activities could fit into more than one category.
• Looking for simple articles for younger students for some of the activities? Try DOGO News or Time for Kids . Newsela is also a great resource but you do need to sign up for free account.
• Why not try a few activities in a staff meeting? Everyone can always brush up on their own research skills!

• Choose a topic (e.g. koalas, basketball, Mount Everest) . Write as many questions as you can think of relating to that topic.
• Make a mindmap of a topic you’re currently learning about. This could be either on paper or using an online tool like Bubbl.us .
• Read a short book or article. Make a list of 5 words from the text that you don’t totally understand. Look up the meaning of the words in a dictionary (online or paper).
• Look at a printed or digital copy of a short article with the title removed. Come up with as many different titles as possible that would fit the article.
• Come up with a list of 5 different questions you could type into Google (e.g. Which country in Asia has the largest population?) Circle the keywords in each question.
• Write down 10 words to describe a person, place, or topic. Come up with synonyms for these words using a tool like  Thesaurus.com .
• Write pairs of synonyms on post-it notes (this could be done by the teacher or students). Each student in the class has one post-it note and walks around the classroom to find the person with the synonym to their word.

• Explore how to search Google using your voice (i.e. click/tap on the microphone in the Google search box or on your phone/tablet keyboard) . List the pros and cons of using voice and text to search.
• Open two different search engines in your browser such as Google and Bing. Type in a query and compare the results. Do all search engines work exactly the same?
• Have students work in pairs to try out a different search engine (there are 11 listed here ). Report back to the class on the pros and cons.
• Think of something you’re curious about, (e.g. What endangered animals live in the Amazon Rainforest?). Open Google in two tabs. In one search, type in one or two keywords ( e.g. Amazon Rainforest) . In the other search type in multiple relevant keywords (e.g. endangered animals Amazon rainforest).  Compare the results. Discuss the importance of being specific.
• Similar to above, try two different searches where one phrase is in quotation marks and the other is not. For example, Origin of “raining cats and dogs” and Origin of raining cats and dogs . Discuss the difference that using quotation marks makes (It tells Google to search for the precise keywords in order.)
• Try writing a question in Google with a few minor spelling mistakes. What happens? What happens if you add or leave out punctuation ?
• Try the AGoogleADay.com daily search challenges from Google. The questions help older students learn about choosing keywords, deconstructing questions, and altering keywords.
• Explore how Google uses autocomplete to suggest searches quickly. Try it out by typing in various queries (e.g. How to draw… or What is the tallest…). Discuss how these suggestions come about, how to use them, and whether they’re usually helpful.
• Watch this video  from Code.org to learn more about how search works .
• Take a look at  20 Instant Google Searches your Students Need to Know  by Eric Curts to learn about “ instant searches ”. Try one to try out. Perhaps each student could be assigned one to try and share with the class.
• Experiment with typing some questions into Google that have a clear answer (e.g. “What is a parallelogram?” or “What is the highest mountain in the world?” or “What is the population of Australia?”). Look at the different ways the answers are displayed instantly within the search results — dictionary definitions, image cards, graphs etc.

• Watch the video How Does Google Know Everything About Me?  by Scientific American. Discuss the PageRank algorithm and how Google uses your data to customise search results.
• Brainstorm a list of popular domains   (e.g. .com, .com.au, or your country’s domain) . Discuss if any domains might be more reliable than others and why (e.g. .gov or .edu) .
• Discuss (or research) ways to open Google search results in a new tab to save your original search results  (i.e. right-click > open link in new tab or press control/command and click the link).
• Try out a few Google searches (perhaps start with things like “car service” “cat food” or “fresh flowers”). A re there advertisements within the results? Discuss where these appear and how to spot them.
• Look at ways to filter search results by using the tabs at the top of the page in Google (i.e. news, images, shopping, maps, videos etc.). Do the same filters appear for all Google searches? Try out a few different searches and see.
• Type a question into Google and look for the “People also ask” and “Searches related to…” sections. Discuss how these could be useful. When should you use them or ignore them so you don’t go off on an irrelevant tangent? Is the information in the drop-down section under “People also ask” always the best?
• Often, more current search results are more useful. Click on “tools” under the Google search box and then “any time” and your time frame of choice such as “Past month” or “Past year”.
• Have students annotate their own “anatomy of a search result” example like the one I made below. Explore the different ways search results display; some have more details like sitelinks and some do not.

• Find two articles on a news topic from different publications. Or find a news article and an opinion piece on the same topic. Make a Venn diagram comparing the similarities and differences.
• Choose a graph, map, or chart from The New York Times’ What’s Going On In This Graph series . Have a whole class or small group discussion about the data.
• Look at images stripped of their captions on What’s Going On In This Picture? by The New York Times. Discuss the images in pairs or small groups. What can you tell?
• Explore a website together as a class or in pairs — perhaps a news website. Identify all the advertisements .
• Have a look at a fake website either as a whole class or in pairs/small groups. See if students can spot that these sites are not real. Discuss the fact that you can’t believe everything that’s online. Get started with these four examples of fake websites from Eric Curts.
• Give students a copy of my website evaluation flowchart to analyse and then discuss as a class. Read more about the flowchart in this post.
• As a class, look at a prompt from Mike Caulfield’s Four Moves . Either together or in small groups, have students fact check the prompts on the site. This resource explains more about the fact checking process. Note: some of these prompts are not suitable for younger students.
• Practice skim reading — give students one minute to read a short article. Ask them to discuss what stood out to them. Headings? Bold words? Quotes? Then give students ten minutes to read the same article and discuss deep reading.

All students can benefit from learning about plagiarism, copyright, how to write information in their own words, and how to acknowledge the source. However, the formality of this process will depend on your students’ age and your curriculum guidelines.

• Watch the video Citation for Beginners for an introduction to citation. Discuss the key points to remember.
• Look up the definition of plagiarism using a variety of sources (dictionary, video, Wikipedia etc.). Create a definition as a class.
• Find an interesting video on YouTube (perhaps a “life hack” video) and write a brief summary in your own words.
• Have students pair up and tell each other about their weekend. Then have the listener try to verbalise or write their friend’s recount in their own words. Discuss how accurate this was.
• Read the class a copy of a well known fairy tale. Have them write a short summary in their own words. Compare the versions that different students come up with.
• Try out MyBib — a handy free online tool without ads that helps you create citations quickly and easily.
• Give primary/elementary students a copy of Kathy Schrock’s Guide to Citation that matches their grade level (the guide covers grades 1 to 6). Choose one form of citation and create some examples as a class (e.g. a website or a book).
• Make a list of things that are okay and not okay to do when researching, e.g. copy text from a website, use any image from Google images, paraphrase in your own words and cite your source, add a short quote and cite the source. 
• Have students read a short article and then come up with a summary that would be considered plagiarism and one that would not be considered plagiarism. These could be shared with the class and the students asked to decide which one shows an example of plagiarism .
• Older students could investigate the difference between paraphrasing and summarising . They could create a Venn diagram that compares the two.
• Write a list of statements on the board that might be true or false ( e.g. The 1956 Olympics were held in Melbourne, Australia. The rhinoceros is the largest land animal in the world. The current marathon world record is 2 hours, 7 minutes). Have students research these statements and decide whether they’re true or false by sharing their citations.

Staying Organised

• Make a list of different ways you can take notes while researching — Google Docs, Google Keep, pen and paper etc. Discuss the pros and cons of each method.
• Learn the keyboard shortcuts to help manage tabs (e.g. open new tab, reopen closed tab, go to next tab etc.). Perhaps students could all try out the shortcuts and share their favourite one with the class.
• Find a collection of resources on a topic and add them to a Wakelet .
• Listen to a short podcast or watch a brief video on a certain topic and sketchnote ideas. Sylvia Duckworth has some great tips about live sketchnoting
• Learn how to use split screen to have one window open with your research, and another open with your notes (e.g. a Google spreadsheet, Google Doc, Microsoft Word or OneNote etc.) .

All teachers know it’s important to teach students to research well. Investing time in this process will also pay off throughout the year and the years to come. Students will be able to focus on analysing and synthesizing information, rather than the mechanics of the research process.

By trying out as many of these mini-lessons as possible throughout the year, you’ll be really helping your students to thrive in all areas of school, work, and life.

Also remember to model your own searches explicitly during class time. Talk out loud as you look things up and ask students for input. Learning together is the way to go!

You Might Also Enjoy Reading:

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8 Ways Teachers And Schools Can Communicate With Parents

10 Replies to “50 Mini-Lessons For Teaching Students Research Skills”

Loving these ideas, thank you

This list is amazing. Thank you so much!

So glad it’s helpful, Alex! 🙂

Hi I am a student who really needed some help on how to reasearch thanks for the help.

So glad it helped! 🙂

seriously seriously grateful for your post. 🙂

So glad it’s helpful! Makes my day 🙂

How do you get the 50 mini lessons. I got the free one but am interested in the full version.

Hi Tracey, The link to the PDF with the 50 mini lessons is in the post. Here it is . Check out this post if you need more advice on teaching students how to research online. Hope that helps! Kathleen

Best wishes to you as you face your health battler. Hoping you’ve come out stronger and healthier from it. Your website is so helpful.

Comments are closed.

How to teach research skills to high school students: 12 tips

by mindroar | Oct 10, 2021 | blog | 0 comments

Teachers often find it difficult to decide how to teach research skills to high school students. You probably feel students should know how to do research by high school. But often students’ skills are lacking in one or more areas.

Today we’re not going to give you research skills lesson plans for high school. But we will give you 12 tips for how to teach research skills to high school students. Bonus, the tips will make it quick, fun, and easy.

One of my favorite ways of teaching research skills to high school students is to use the Crash Course Navigating Digital Information series.

The videos are free and short (between ten and fifteen minutes each). They cover information such as evaluating the trustworthiness of sources, using Wikipedia, lateral reading, and understanding how the source medium can affect the message.

Another thing I like to integrate into my lessons are the Crash Course Study Skills videos . Again, they’re free and short. Plus they are an easy way to refresh study skills such as:

• note-taking
• writing papers
• editing papers
• getting organized
• and studying for tests and exams.

If you’re ready to get started, we’ll give you links to great resources that you can integrate into your lessons. Because often students just need a refresh on a particular skill and not a whole semester-long course.

1. Why learn digital research skills?

Tip number one of how to teach research skills to high school students. Address the dreaded ‘why?’ questions upfront. You know the questions: Why do we have to do this? When am I ever going to use this?

If your students understand why they need good research skills and know that you will show them specific strategies to improve their skills, they are far more likely to buy into learning about how to research effectively.

An easy way to answer this question is that students spend so much time online. Some people spend almost an entire day online each week.

It’s amazing to have such easy access to information, unlike the pre-internet days. But there is far more misinformation and disinformation online.

A webpage, Facebook post, Instagram post, YouTube video, infographic, meme, gif, TikTok video (etc etc) can be created by just about anyone with a phone. And it’s easy to create them in a way that looks professional and legitimate.

This can make it hard for people to know what is real, true, evidence-based information and what is not.

The first Crash Course Navigating Digital Information video gets into the nitty-gritty of why we should learn strategies for evaluating the information we find (online or otherwise!).

An easy way to answer the ‘why’ questions your high schoolers will ask, the video is an excellent resource.

2. Teaching your students to fact check

Tip number two for teaching research skills to high school students is to teach your students concrete strategies for how to check facts.

It’s surprising how many students will hand in work with blatant factual errors. Errors they could have avoided had they done a quick fact check.

An easy way to broach this research skill in high school is to watch the second video in the Crash Course Navigating Digital Information series. It explains what fact-checking is, why people should do it, and how to make it a habit.

You can explain to your students that they’ll write better papers if they learn to fact-check. But they’ll also make better decisions if they make fact-checking a habit.

The video looks at why people are more likely to believe mis- or disinformation online. And it shows students a series of questions they can use to identify mis- or disinformation.

The video also discusses why it’s important to find a few generally reliable sources of information and to use those as a way to fact-check other online sources.

3. Teaching your students how and why to read laterally

This ties in with tip number 2 – teach concrete research strategies – but it is more specific. Fact-checking tends to be checking what claim sources are making, who is making the claim, and corroborating the claim with other sources.

But lateral reading is another concrete research skills strategy that you can teach to students. This skill helps students spot inaccurate information quickly and avoid wasting valuable research time.

One of the best (and easiest!) research skills for high school students to learn is how to read laterally. And teachers can demonstrate it so, so easily. As John Green says in the third Crash Course Navigating Digital Information video , just open another tab!

The video also shows students good websites to use to check hoaxes and controversial information.

Importantly, John Green also explains that students need a “toolbox” of strategies to assess sources of information. There’s not one magic source of information that is 100% accurate.

4. Teaching your students how to evaluate trustworthiness

Deciding who to trust online can be difficult even for those of us with lots of experience navigating online. And it is made even more difficult by how easy it now is to create a professional-looking websites.

This video shows students what to look for when evaluating trustworthiness. It also explains how to take bias, opinion, and political orientations into account when using information sources.

The video explains how reputable information sources gather reliable information (versus disreputable sources). And shows how reputable information sources navigate the situation when they discover their information is incorrect or misleading.

Students can apply the research skills from this video to news sources, novel excerpts, scholarly articles, and primary sources. Teaching students to look for bias, political orientation, and opinions within all sources is one of the most valuable research skills for high school students.

5. Teaching your students to use Wikipedia

Now, I know that Wikipedia can be the bane of your teacherly existence when you are reading essays. I know it can make you want to gouge your eyes out with a spoon when you read the same recycled article in thirty different essays. But, teaching students how to use Wikipedia as a jumping-off point is a useful skill.

Wikipedia is no less accurate than other online encyclopedia-type sources. And it often includes hyperlinks and references that students can check or use for further research. Plus it has handy-dandy warnings for inaccurate and contentious information.

Part of how to teach research skills to high school students is teaching them how to use general reference material such as encyclopedias for broad information. And then following up with how to use more detailed information such as primary and secondary sources.

The Crash Course video about Wikipedia is an easy way to show students how to use it more effectively.

6. Teaching your students to evaluate evidence

Another important research skill to teach high school students is how to evaluate evidence. This skill is important, both in their own and in others’ work.

An easy way to do this is the Crash Course video about evaluating evidence video. The short video shows students how to evaluate evidence using authorship, the evidence provided, and the relevance of the evidence.

It also gives examples of ways that evidence can be used to mislead. For example, it shows that simply providing evidence doesn’t mean that the evidence is quality evidence that supports the claim being made.

The video shows examples of evidence that is related to a topic, but irrelevant to the claim. Having an example of irrelevant evidence helps students understand the difference between related but irrelevant evidence and evidence that is relevant to the claim.

Finally, the video gives students questions that they can use to evaluate evidence.

7. Teaching your students to evaluate photos and videos

While the previous video about evidence looked at how to evaluate evidence in general, this video looks specifically at video and photographic evidence.

The video looks at how videos and photos can be manipulated to provide evidence for a claim. It suggests that seeking out the context for photos and videos is especially important as a video or photo is easy to misinterpret. This is especially the case if a misleading caption or surrounding information is provided.

The video also gives tools that students can use to discover hoaxes or fakes. Similarly, it encourages people to look for the origin of the photo or video to find the creator. And to then use that with contextual information to decide whether the photo or video is reliable evidence for a claim.

8. Teaching your students to evaluate data and infographics

Other sources of evidence that students (and adults!) often misinterpret or are misled by are data and infographics. Often people take the mere existence of statistics or other data as evidence for a claim instead of investigating further.

Again the Crash Course video suggests seeking out the source and context for data and infographics. It suggests that students often see data as neutral and irrefutable, but that data is inherently biased as it is created by humans.

The video gives a real-world example of how data can be manipulated as a source of evidence by showing how two different news sources represented global warming data.

9. Teaching your students how search engines work and why to use click restraint

Another video from the Crash Course Navigating Digital Information series is the video about how search engines work and click restraint . This video shows how search engines decide which information to list at the top of the search results. It also shows how search engines decide what information is relevant and of good quality.

The video gives search tips for using search engines to encourage the algorithms to return more reliable and accurate results.

This video is important when you are want to know how to teach research skills to high school students. This is because many students don’t understand why the first few results on a search are not necessarily the best information available.

10. Teach your students how to evaluate social media sources

One of the important research skills high school students need is to evaluate social media posts. Many people now get news and information from social media sites that have little to no oversight or editorial control. So, being able to evaluate posts for accuracy is key.

This video in the Crash Course Navigating Digital Information series also explains that social media sites are free to use because they make money from advertising. The advertising money comes from keeping people on the platform (and looking at the ads).

How do they keep people on the platform? By using algorithms that gather information about how long people spend on or react to different photos, posts and videos. Then, the algorithms will send viewers more content that is similar to the content that they view or interact with.

This prioritizes content that is controversial, shocking, engaging, attractive. It also reinforces the social norms of the audience members using the platform.

By teaching students how to combat the way that social media algorithms work, you can show them how to gather more reliable and relevant information in their everyday lives. Further, you help students work out if social media posts are relevant to (reliable for) their academic work.

11. Teaching your students how to cite sources

Another important research skill high school students need is how to accurately cite sources. A quick Google search turned up a few good free ideas:

• This lesson plan from the Brooklyn Library for grades 4-11. It aligns with the common core objectives and provides worksheets for students to learn to use MLA citation.
• This blog post about middle-school teacher Jody Passanini’s experiences trying to teach students in English and History how to cite sources both in-text and at the end with a reference list.
• This scavenger hunt lesson by 8th grade teacher on ReadWriteThink. It has a free printout asking students to prove assertions (which could be either student- or teacher-generated) with quotes from the text and a page number. It also has an example answer using the Catching Fire (Hunger Games) novel.
• The Chicago Manual of Style has this quick author-date citation guide .
• This page by Purdue Online Writing Lab has an MLA citation guide , as well as links to other citation guides such as APA.

If you are wanting other activities, a quick search of TPT showed these to be popular and well-received by other teachers:

• Laura Randazzo’s 9th edition MLA in-text and end-of-text citation activities
• Tracee Orman 8th edition MLA cheet sheet
• The Daring English Teacher’s MLA 8th edition citation powerpoint

12. Teaching your students to take notes

Another important skill to look at when considering how to teach research skills to high school students is whether they know how to take effective notes.

The Crash Course Study Skills note-taking video is great for this. It outlines three note-taking styles – the outline method, the Cornell method, and the mind map method. And it shows students how to use each of the methods.

This can help you start a conversation with your students about which styles of note-taking are most effective for different tasks.

For example, mind maps are great for seeing connections between ideas and brain dumps. The outline method is great for topics that are hierarchical. And the Cornell method is great for topics with lots of specific vocabulary.

Having these types of metacognitive discussions with your students helps them identify study and research strategies. It also helps them to learn which strategies are most effective in different situations.

Teaching research skills to high school students . . .

Doesn’t have to be

• time-consuming

The fantastic Crash Course Navigating Digital Information videos are a great way to get started if you are wondering how to teach research skills to high school students.

If you decide to use the videos in your class, you can buy individual worksheets if you have specific skills in mind. Or you can buy the full bundle if you think you’ll end up watching all of the videos.

Got any great tips for teaching research skills to high school students?

Head over to our Facebook or Instagram pages and let us know!

Empowering students to develop research skills

February 8, 2021

This post is republished from   Into Practice ,  a biweekly communication of Harvard’s  Office of the Vice Provost for Advances in Learning

Terence D. Capellini, Richard B Wolf Associate Professor of Human Evolutionary Biology, empowers students to grow as researchers in his Building the Human Body course through a comprehensive, course-long collaborative project that works to understand the changes in the genome that make the human skeleton unique. For instance, of the many types of projects, some focus on the genetic basis of why human beings walk on two legs. This integrative “Evo-Devo” project demands high levels of understanding of biology and genetics that students gain in the first half of class, which is then applied hands-on in the second half of class. Students work in teams of 2-3 to collect their own morphology data by measuring skeletons at the Harvard Museum of Natural History and leverage statistics to understand patterns in their data. They then collect and analyze DNA sequences from humans and other animals to identify the DNA changes that may encode morphology. Throughout this course, students go from sometimes having “limited experience in genetics and/or morphology” to conducting their own independent research. This project culminates in a team presentation and a final research paper.

The benefits: Students develop the methodological skills required to collect and analyze morphological data. Using the UCSC Genome browser  and other tools, students sharpen their analytical skills to visualize genomics data and pinpoint meaningful genetic changes. Conducting this work in teams means students develop collaborative skills that model academic biology labs outside class, and some student projects have contributed to published papers in the field. “Every year, I have one student, if not two, join my lab to work on projects developed from class to try to get them published.”

“The beauty of this class is that the students are asking a question that’s never been asked before and they’re actually collecting data to get at an answer.”

The challenges:  Capellini observes that the most common challenge faced by students in the course is when “they have a really terrific question they want to explore, but the necessary background information is simply lacking. It is simply amazing how little we do know about human development, despite its hundreds of years of study.” Sometimes, for instance, students want to learn about the evolution, development, and genetics of a certain body part, but it is still somewhat a mystery to the field. In these cases, the teaching team (including co-instructor Dr. Neil Roach) tries to find datasets that are maximally relevant to the questions the students want to explore. Capellini also notes that the work in his class is demanding and hard, just by the nature of the work, but students “always step up and perform” and the teaching team does their best to “make it fun” and ensure they nurture students’ curiosities and questions.

Takeaways and best practices

• Incorporate previous students’ work into the course. Capellini intentionally discusses findings from previous student groups in lectures. “They’re developing real findings and we share that when we explain the project for the next groups.” Capellini also invites students to share their own progress and findings as part of class discussion, which helps them participate as independent researchers and receive feedback from their peers.
• Assign groups intentionally.  Maintaining flexibility allows the teaching team to be more responsive to students’ various needs and interests. Capellini will often place graduate students by themselves to enhance their workload and give them training directly relevant to their future thesis work. Undergraduates are able to self-select into groups or can be assigned based on shared interests. “If two people are enthusiastic about examining the knee, for instance, we’ll match them together.”
• Consider using multiple types of assessments.  Capellini notes that exams and quizzes are administered in the first half of the course and scaffolded so that students can practice the skills they need to successfully apply course material in the final project. “Lots of the initial examples are hypothetical,” he explains, even grounded in fiction and pop culture references, “but [students] have to eventually apply the skills they learned in addressing the hypothetical example to their own real example and the data they generate” for the Evo-Devo project. This is coupled with a paper and a presentation treated like a conference talk.

Bottom line:  Capellini’s top advice for professors looking to help their own students grow as researchers is to ensure research projects are designed with intentionality and fully integrated into the syllabus. “You can’t simply tack it on at the end,” he underscores. “If you want this research project to be a substantive learning opportunity, it has to happen from Day 1.” That includes carving out time in class for students to work on it and make the connections they need to conduct research. “Listen to your students and learn about them personally” so you can tap into what they’re excited about. Have some fun in the course, and they’ll be motivated to do the work.

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• Open access
• Published: 02 December 2020

Enhancing senior high school student engagement and academic performance using an inclusive and scalable inquiry-based program

• Locke Davenport Huyer   ORCID: orcid.org/0000-0003-1526-7122 1 , 2   na1 ,
• Neal I. Callaghan   ORCID: orcid.org/0000-0001-8214-3395 1 , 3   na1 ,
• Sara Dicks 4 ,
• Edward Scherer 4 ,
• Andrey I. Shukalyuk 1 ,
• Margaret Jou 4 &
• Dawn M. Kilkenny   ORCID: orcid.org/0000-0002-3899-9767 1 , 5  

npj Science of Learning volume  5 , Article number:  17 ( 2020 ) Cite this article

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The multi-disciplinary nature of science, technology, engineering, and math (STEM) careers often renders difficulty for high school students navigating from classroom knowledge to post-secondary pursuits. Discrepancies between the knowledge-based high school learning approach and the experiential approach of future studies leaves some students disillusioned by STEM. We present Discovery , a term-long inquiry-focused learning model delivered by STEM graduate students in collaboration with high school teachers, in the context of biomedical engineering. Entire classes of high school STEM students representing diverse cultural and socioeconomic backgrounds engaged in iterative, problem-based learning designed to emphasize critical thinking concomitantly within the secondary school and university environments. Assessment of grades and survey data suggested positive impact of this learning model on students’ STEM interests and engagement, notably in under-performing cohorts, as well as repeating cohorts that engage in the program on more than one occasion. Discovery presents a scalable platform that stimulates persistence in STEM learning, providing valuable learning opportunities and capturing cohorts of students that might otherwise be under-engaged in STEM.

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Exploring the impact of web-based inquiry on elementary school students’ science identity development in a STEM learning unit

Introduction.

High school students with diverse STEM interests often struggle to understand the STEM experience outside the classroom 1 . The multi-disciplinary nature of many career fields can foster a challenge for students in their decision to enroll in appropriate high school courses while maintaining persistence in study, particularly when these courses are not mandatory 2 . Furthermore, this challenge is amplified by the known discrepancy between the knowledge-based learning approach common in high schools and the experiential, mastery-based approaches afforded by the subsequent undergraduate model 3 . In the latter, focused classes, interdisciplinary concepts, and laboratory experiences allow for the application of accumulated knowledge, practice in problem solving, and development of both general and technical skills 4 . Such immersive cooperative learning environments are difficult to establish in the secondary school setting and high school teachers often struggle to implement within their classroom 5 . As such, high school students may become disillusioned before graduation and never experience an enriched learning environment, despite their inherent interests in STEM 6 .

It cannot be argued that early introduction to varied math and science disciplines throughout high school is vital if students are to pursue STEM fields, especially within engineering 7 . However, the majority of literature focused on student interest and retention in STEM highlights outcomes in US high school learning environments, where the sciences are often subject-specific from the onset of enrollment 8 . In contrast, students in the Ontario (Canada) high school system are required to complete Level 1 and 2 core courses in science and math during Grades 9 and 10; these courses are offered as ‘applied’ or ‘academic’ versions and present broad topics of content 9 . It is not until Levels 3 and 4 (generally Grades 11 and 12, respectively) that STEM classes become subject-specific (i.e., Biology, Chemistry, and/or Physics) and are offered as “university”, “college”, or “mixed” versions, designed to best prepare students for their desired post-secondary pursuits 9 . Given that Levels 3 and 4 science courses are not mandatory for graduation, enrollment identifies an innate student interest in continued learning. Furthermore, engagement in these post-secondary preparatory courses is also dependent upon achieving successful grades in preceding courses, but as curriculum becomes more subject-specific, students often yield lower degrees of success in achieving course credit 2 . Therefore, it is imperative that learning supports are best focused on ensuring that those students with an innate interest are able to achieve success in learning.

When given opportunity and focused support, high school students are capable of successfully completing rigorous programs at STEM-focused schools 10 . Specialized STEM schools have existed in the US for over 100 years; generally, students are admitted after their sophomore year of high school experience (equivalent to Grade 10) based on standardized test scores, essays, portfolios, references, and/or interviews 11 . Common elements to this learning framework include a diverse array of advanced STEM courses, paired with opportunities to engage in and disseminate cutting-edge research 12 . Therein, said research experience is inherently based in the processes of critical thinking, problem solving, and collaboration. This learning framework supports translation of core curricular concepts to practice and is fundamental in allowing students to develop better understanding and appreciation of STEM career fields.

Despite the described positive attributes, many students do not have the ability or resources to engage within STEM-focused schools, particularly given that they are not prevalent across Canada, and other countries across the world. Consequently, many public institutions support the idea that post-secondary led engineering education programs are effective ways to expose high school students to engineering education and relevant career options, and also increase engineering awareness 13 . Although singular class field trips are used extensively to accomplish such programs, these may not allow immersive experiences for application of knowledge and practice of skills that are proven to impact long-term learning and influence career choices 14 , 15 . Longer-term immersive research experiences, such as after-school programs or summer camps, have shown successful at recruiting students into STEM degree programs and careers, where longevity of experience helps foster self-determination and interest-led, inquiry-based projects 4 , 16 , 17 , 18 , 19 .

Such activities convey the elements that are suggested to make a post-secondary led high school education programs successful: hands-on experience, self-motivated learning, real-life application, immediate feedback, and problem-based projects 20 , 21 . In combination with immersion in university teaching facilities, learning is authentic and relevant, similar to the STEM school-focused framework, and consequently representative of an experience found in actual STEM practice 22 . These outcomes may further be a consequence of student engagement and attitude: Brown et al. studied the relationships between STEM curriculum and student attitudes, and found the latter played a more important role in intention to persist in STEM when compared to self-efficacy 23 . This is interesting given that student self-efficacy has been identified to influence ‘motivation, persistence, and determination’ in overcoming challenges in a career pathway 24 . Taken together, this suggests that creation and delivery of modern, exciting curriculum that supports positive student attitudes is fundamental to engage and retain students in STEM programs.

Supported by the outcomes of identified effective learning strategies, University of Toronto (U of T) graduate trainees created a novel high school education program Discovery , to develop a comfortable yet stimulating environment of inquiry-focused iterative learning for senior high school students (Grades 11 & 12; Levels 3 & 4) at non-specialized schools. Built in strong collaboration with science teachers from George Harvey Collegiate Institute (Toronto District School Board), Discovery stimulates application of STEM concepts within a unique term-long applied curriculum delivered iteratively within both U of T undergraduate teaching facilities and collaborating high school classrooms 25 . Based on the volume of medically-themed news and entertainment that is communicated to the population at large, the rapidly-growing and diverse field of biomedical engineering (BME) were considered an ideal program context 26 . In its definition, BME necessitates cross-disciplinary STEM knowledge focused on the betterment of human health, wherein Discovery facilitates broadening student perspective through engaging inquiry-based projects. Importantly, Discovery allows all students within a class cohort to work together with their classroom teacher, stimulating continued development of a relevant learning community that is deemed essential for meaningful context and important for transforming student perspectives and understandings 27 , 28 . Multiple studies support the concept that relevant learning communities improve student attitudes towards learning, significantly increasing student motivation in STEM courses, and consequently improving the overall learning experience 29 . Learning communities, such as that provided by Discovery , also promote the formation of self-supporting groups, greater active involvement in class, and higher persistence rates for participating students 30 .

The objective of Discovery , through structure and dissemination, is to engage senior high school science students in challenging, inquiry-based practical BME activities as a mechanism to stimulate comprehension of STEM curriculum application to real-world concepts. Consequent focus is placed on critical thinking skill development through an atmosphere of perseverance in ambiguity, something not common in a secondary school knowledge-focused delivery but highly relevant in post-secondary STEM education strategies. Herein, we describe the observed impact of the differential project-based learning environment of Discovery on student performance and engagement. We identify the value of an inquiry-focused learning model that is tangible for students who struggle in a knowledge-focused delivery structure, where engagement in conceptual critical thinking in the relevant subject area stimulates student interest, attitudes, and resulting academic performance. Assessment of study outcomes suggests that when provided with a differential learning opportunity, student performance and interest in STEM increased. Consequently, Discovery provides an effective teaching and learning framework within a non-specialized school that motivates students, provides opportunity for critical thinking and problem-solving practice, and better prepares them for persistence in future STEM programs.

Program delivery

The outcomes of the current study result from execution of Discovery over five independent academic terms as a collaboration between Institute of Biomedical Engineering (graduate students, faculty, and support staff) and George Harvey Collegiate Institute (science teachers and administration) stakeholders. Each term, the program allowed senior secondary STEM students (Grades 11 and 12) opportunity to engage in a novel project-based learning environment. The program structure uses the problem-based engineering capstone framework as a tool of inquiry-focused learning objectives, motivated by a central BME global research topic, with research questions that are inter-related but specific to the curriculum of each STEM course subject (Fig. 1 ). Over each 12-week term, students worked in teams (3–4 students) within their class cohorts to execute projects with the guidance of U of T trainees ( Discovery instructors) and their own high school teacher(s). Student experimental work was conducted in U of T teaching facilities relevant to the research study of interest (i.e., Biology and Chemistry-based projects executed within Undergraduate Teaching Laboratories; Physics projects executed within Undergraduate Design Studios). Students were introduced to relevant techniques and safety procedures in advance of iterative experimentation. Importantly, this experience served as a course term project for students, who were assessed at several points throughout the program for performance in an inquiry-focused environment as well as within the regular classroom (Fig. 1 ). To instill the atmosphere of STEM, student teams delivered their outcomes in research poster format at a final symposium, sharing their results and recommendations with other post-secondary students, faculty, and community in an open environment.

The general program concept (blue background; top left ) highlights a global research topic examined through student dissemination of subject-specific research questions, yielding multifaceted student outcomes (orange background; top right ). Each program term (term workflow, yellow background; bottom panel ), students work on program deliverables in class (blue), iterate experimental outcomes within university facilities (orange), and are assessed accordingly at numerous deliverables in an inquiry-focused learning model.

Over the course of five terms there were 268 instances of tracked student participation, representing 170 individual students. Specifically, 94 students participated during only one term of programming, 57 students participated in two terms, 16 students participated in three terms, and 3 students participated in four terms. Multiple instances of participation represent students that enrol in more than one STEM class during their senior years of high school, or who participated in Grade 11 and subsequently Grade 12. Students were surveyed before and after each term to assess program effects on STEM interest and engagement. All grade-based assessments were performed by high school teachers for their respective STEM class cohorts using consistent grading rubrics and assignment structure. Here, we discuss the outcomes of student involvement in this experiential curriculum model.

Student performance and engagement

Student grades were assigned, collected, and anonymized by teachers for each Discovery deliverable (background essay, client meeting, proposal, progress report, poster, and final presentation). Teachers anonymized collective Discovery grades, the component deliverable grades thereof, final course grades, attendance in class and during programming, as well as incomplete classroom assignments, for comparative study purposes. Students performed significantly higher in their cumulative Discovery grade than in their cumulative classroom grade (final course grade less the Discovery contribution; p  < 0.0001). Nevertheless, there was a highly significant correlation ( p  < 0.0001) observed between the grade representing combined Discovery deliverables and the final course grade (Fig. 2a ). Further examination of the full dataset revealed two student cohorts of interest: the “Exceeds Expectations” (EE) subset (defined as those students who achieved ≥1 SD [18.0%] grade differential in Discovery over their final course grade; N  = 99 instances), and the “Multiple Term” (MT) subset (defined as those students who participated in Discovery more than once; 76 individual students that collectively accounted for 174 single terms of assessment out of the 268 total student-terms delivered) (Fig. 2b, c ). These subsets were not unrelated; 46 individual students who had multiple experiences (60.5% of total MTs) exhibited at least one occasion in achieving a ≥18.0% grade differential. As students participated in group work, there was concern that lower-performing students might negatively influence the Discovery grade of higher-performing students (or vice versa). However, students were observed to self-organize into groups where all individuals received similar final overall course grades (Fig. 2d ), thereby alleviating these concerns.

a Linear regression of student grades reveals a significant correlation ( p  = 0.0009) between Discovery performance and final course grade less the Discovery contribution to grade, as assessed by teachers. The dashed red line and intervals represent the theoretical 1:1 correlation between Discovery and course grades and standard deviation of the Discovery -course grade differential, respectively. b , c Identification of subgroups of interest, Exceeds Expectations (EE; N  = 99, orange ) who were ≥+1 SD in Discovery -course grade differential and Multi-Term (MT; N  = 174, teal ), of which N  = 65 students were present in both subgroups. d Students tended to self-assemble in working groups according to their final course performance; data presented as mean ± SEM. e For MT students participating at least 3 terms in Discovery , there was no significant correlation between course grade and time, while ( f ) there was a significant correlation between Discovery grade and cumulative terms in the program. Histograms of total absences per student in ( g ) Discovery and ( h ) class (binned by 4 days to be equivalent in time to a single Discovery absence).

The benefits experienced by MT students seemed progressive; MT students that participated in 3 or 4 terms ( N  = 16 and 3, respectively ) showed no significant increase by linear regression in their course grade over time ( p  = 0.15, Fig. 2e ), but did show a significant increase in their Discovery grades ( p  = 0.0011, Fig. 2f ). Finally, students demonstrated excellent Discovery attendance; at least 91% of participants attended all Discovery sessions in a given term (Fig. 2g ). In contrast, class attendance rates reveal a much wider distribution where 60.8% (163 out of 268 students) missed more than 4 classes (equivalent in learning time to one Discovery session) and 14.6% (39 out of 268 students) missed 16 or more classes (equivalent in learning time to an entire program of Discovery ) in a term (Fig. 2h ).

Discovery EE students (Fig. 3 ), roughly by definition, obtained lower course grades ( p  < 0.0001, Fig. 3a ) and higher final Discovery grades ( p  = 0.0004, Fig. 3b ) than non-EE students. This cohort of students exhibited program grades higher than classmates (Fig. 3c–h ); these differences were significant in every category with the exception of essays, where they outperformed to a significantly lesser degree ( p  = 0.097; Fig. 3c ). There was no statistically significant difference in EE vs. non-EE student classroom attendance ( p  = 0.85; Fig. 3i, j ). There were only four single day absences in Discovery within the EE subset; however, this difference was not statistically significant ( p  = 0.074).

The “Exceeds Expectations” (EE) subset of students (defined as those who received a combined Discovery grade ≥1 SD (18.0%) higher than their final course grade) performed ( a ) lower on their final course grade and ( b ) higher in the Discovery program as a whole when compared to their classmates. d – h EE students received significantly higher grades on each Discovery deliverable than their classmates, except for their ( c ) introductory essays and ( h ) final presentations. The EE subset also tended ( i ) to have a higher relative rate of attendance during Discovery sessions but no difference in ( j ) classroom attendance. N  = 99 EE students and 169 non-EE students (268 total). Grade data expressed as mean ± SEM.

Discovery MT students (Fig. 4 ), although not receiving significantly higher grades in class than students participating in the program only one time ( p  = 0.29, Fig. 4a ), were observed to obtain higher final Discovery grades than single-term students ( p  = 0.0067, Fig. 4b ). Although trends were less pronounced for individual MT student deliverables (Fig. 4c–h ), this student group performed significantly better on the progress report ( p  = 0.0021; Fig. 4f ). Trends of higher performance were observed for initial proposals and final presentations ( p  = 0.081 and 0.056, respectively; Fig. 4e, h ); all other deliverables were not significantly different between MT and non-MT students (Fig. 4c, d, g ). Attendance in Discovery ( p  = 0.22) was also not significantly different between MT and non-MT students, although MT students did miss significantly less class time ( p  = 0.010) (Fig. 4i, j ). Longitudinal assessment of individual deliverables for MT students that participated in three or more Discovery terms (Fig. 5 ) further highlights trend in improvement (Fig. 2f ). Greater performance over terms of participation was observed for essay ( p  = 0.0295, Fig. 5a ), client meeting ( p  = 0.0003, Fig. 5b ), proposal ( p  = 0.0004, Fig. 5c ), progress report ( p  = 0.16, Fig. 5d ), poster ( p  = 0.0005, Fig. 5e ), and presentation ( p  = 0.0295, Fig. 5f ) deliverable grades; these trends were all significant with the exception of the progress report ( p  = 0.16, Fig. 5d ) owing to strong performance in this deliverable in all terms.

The “multi-term” (MT) subset of students (defined as having attended more than one term of Discovery ) demonstrated favorable performance in Discovery , ( a ) showing no difference in course grade compared to single-term students, but ( b outperforming them in final Discovery grade. Independent of the number of times participating in Discovery , MT students did not score significantly differently on their ( c ) essay, ( d ) client meeting, or ( g ) poster. They tended to outperform their single-term classmates on the ( e ) proposal and ( h ) final presentation and scored significantly higher on their ( f ) progress report. MT students showed no statistical difference in ( i ) Discovery attendance but did show ( j ) higher rates of classroom attendance than single-term students. N  = 174 MT instances of student participation (76 individual students) and 94 single-term students. Grade data expressed as mean ± SEM.

Longitudinal assessment of a subset of MT student participants that participated in three ( N  = 16) or four ( N  = 3) terms presents a significant trend of improvement in their ( a ) essay, ( b ) client meeting, ( c ) proposal, ( e ) poster, and ( f ) presentation grade. d Progress report grades present a trend in improvement but demonstrate strong performance in all terms, limiting potential for student improvement. Grade data are presented as individual student performance; each student is represented by one color; data is fitted with a linear trendline (black).

Finally, the expansion of Discovery to a second school of lower LOI (i.e., nominally higher aggregate SES) allowed for the assessment of program impact in a new population over 2 terms of programming. A significant ( p  = 0.040) divergence in Discovery vs. course grade distribution from the theoretical 1:1 relationship was found in the new cohort (S 1 Appendix , Fig. S 1 ), in keeping with the pattern established in this study.

Teacher perceptions

Qualitative observation in the classroom by high school teachers emphasized the value students independently placed on program participation and deliverables. Throughout the term, students often prioritized Discovery group assignments over other tasks for their STEM courses, regardless of academic weight and/or due date. Comparing within this student population, teachers spoke of difficulties with late and incomplete assignments in the regular curriculum but found very few such instances with respect to Discovery -associated deliverables. Further, teachers speculated on the good behavior and focus of students in Discovery programming in contrast to attentiveness and behavior issues in their school classrooms. Multiple anecdotal examples were shared of renewed perception of student potential; students that exhibited poor academic performance in the classroom often engaged with high performance in this inquiry-focused atmosphere. Students appeared to take a sense of ownership, excitement, and pride in the setting of group projects oriented around scientific inquiry, discovery, and dissemination.

Student perceptions

Students were asked to consider and rank the academic difficulty (scale of 1–5, with 1 = not challenging and 5 = highly challenging) of the work they conducted within the Discovery learning model. Considering individual Discovery terms, at least 91% of students felt the curriculum to be sufficiently challenging with a 3/5 or higher ranking (Term 1: 87.5%, Term 2: 93.4%, Term 3: 85%, Term 4: 93.3%, Term 5: 100%), and a minimum of 58% of students indicating a 4/5 or higher ranking (Term 1: 58.3%, Term 2: 70.5%, Term 3: 67.5%, Term 4: 69.1%, Term 5: 86.4%) (Fig. 6a ).

a Histogram of relative frequency of perceived Discovery programming academic difficulty ranked from not challenging (1) to highly challenging (5) for each session demonstrated the consistently perceived high degree of difficulty for Discovery programming (total responses: 223). b Program participation increased student comfort (94.6%) with navigating lab work in a university or college setting (total responses: 220). c Considering participation in Discovery programming, students indicated their increased (72.4%) or decreased (10.1%) likelihood to pursue future experiences in STEM as a measure of program impact (total responses: 217). d Large majority of participating students (84.9%) indicated their interest for future participation in Discovery (total responses: 212). Students were given the opportunity to opt out of individual survey questions, partially completed surveys were included in totals.

The majority of students (94.6%) indicated they felt more comfortable with the idea of performing future work in a university STEM laboratory environment given exposure to university teaching facilities throughout the program (Fig. 6b ). Students were also queried whether they were (i) more likely, (ii) less likely, or (iii) not impacted by their experience in the pursuit of STEM in the future. The majority of participants (>82%) perceived impact on STEM interests, with 72.4% indicating they were more likely to pursue these interests in the future (Fig. 6c ). When surveyed at the end of term, 84.9% of students indicated they would participate in the program again (Fig. 6d ).

We have described an inquiry-based framework for implementing experiential STEM education in a BME setting. Using this model, we engaged 268 instances of student participation (170 individual students who participated 1–4 times) over five terms in project-based learning wherein students worked in peer-based teams under the mentorship of U of T trainees to design and execute the scientific method in answering a relevant research question. Collaboration between high school teachers and Discovery instructors allowed for high school student exposure to cutting-edge BME research topics, participation in facilitated inquiry, and acquisition of knowledge through scientific discovery. All assessments were conducted by high school teachers and constituted a fraction (10–15%) of the overall course grade, instilling academic value for participating students. As such, students exhibited excitement to learn as well as commitment to their studies in the program.

Through our observations and analysis, we suggest there is value in differential learning environments for students that struggle in a knowledge acquisition-focused classroom setting. In general, we observed a high level of academic performance in Discovery programming (Fig. 2a ), which was highlighted exceptionally in EE students who exhibited greater academic performance in Discovery deliverables compared to normal coursework (>18% grade improvement in relevant deliverables). We initially considered whether this was the result of strong students influencing weaker students; however, group organization within each course suggests this is not the case (Fig. 2d ). With the exception of one class in one term (24 participants assigned by their teacher), students were allowed to self-organize into working groups and they chose to work with other students of relatively similar academic performance (as indicated by course grade), a trend observed in other studies 31 , 32 . Remarkably, EE students not only excelled during Discovery when compared to their own performance in class, but this cohort also achieved significantly higher average grades in each of the deliverables throughout the program when compared to the remaining Discovery cohort (Fig. 3 ). This data demonstrates the value of an inquiry-based learning environment compared to knowledge-focused delivery in the classroom in allowing students to excel. We expect that part of this engagement was resultant of student excitement with a novel learning opportunity. It is however a well-supported concept that students who struggle in traditional settings tend to demonstrate improved interest and motivation in STEM when given opportunity to interact in a hands-on fashion, which supports our outcomes 4 , 33 . Furthermore, these outcomes clearly represent variable student learning styles, where some students benefit from a greater exchange of information, knowledge and skills in a cooperative learning environment 34 . The performance of the EE group may not be by itself surprising, as the identification of the subset by definition required high performers in Discovery who did not have exceptionally high course grades; in addition, the final Discovery grade is dependent on the component assignment grades. However, the discrepancies between EE and non-EE groups attendance suggests that students were engaged by Discovery in a way that they were not by regular classroom curriculum.

In addition to quantified engagement in Discovery observed in academic performance, we believe remarkable attendance rates are indicative of the value students place in the differential learning structure. Given the differences in number of Discovery days and implications of missing one day of regular class compared to this immersive program, we acknowledge it is challenging to directly compare attendance data and therefore approximate this comparison with consideration of learning time equivalence. When combined with other subjective data including student focus, requests to work on Discovery during class time, and lack of discipline/behavior issues, the attendance data importantly suggests that students were especially engaged by the Discovery model. Further, we believe the increased commute time to the university campus (students are responsible for independent transit to campus, a much longer endeavour than the normal school commute), early program start time, and students’ lack of familiarity with the location are non-trivial considerations when determining the propensity of students to participate enthusiastically in Discovery . We feel this suggests the students place value on this team-focused learning and find it to be more applicable and meaningful to their interests.

Given post-secondary admission requirements for STEM programs, it would be prudent to think that students participating in multiple STEM classes across terms are the ones with the most inherent interest in post-secondary STEM programs. The MT subset, representing students who participated in Discovery for more than one term, averaged significantly higher final Discovery grades. The increase in the final Discovery grade was observed to result from a general confluence of improved performance over multiple deliverables and a continuous effort to improve in a STEM curriculum. This was reflected in longitudinal tracking of Discovery performance, where we observed a significant trend of improved performance. Interestingly, the high number of MT students who were included in the EE group suggests that students who had a keen interest in science enrolled in more than one course and in general responded well to the inquiry-based teaching method of Discovery , where scientific method was put into action. It stands to reason that students interested in science will continue to take STEM courses and will respond favorably to opportunities to put classroom theory to practical application.

The true value of an inquiry-based program such as Discovery may not be based in inspiring students to perform at a higher standard in STEM within the high school setting, as skills in critical thinking do not necessarily translate to knowledge-based assessment. Notably, students found the programming equally challenging throughout each of the sequential sessions, perhaps somewhat surprising considering the increasing number of repeat attendees in successive sessions (Fig. 6a ). Regardless of sub-discipline, there was an emphasis of perceived value demonstrated through student surveys where we observed indicated interest in STEM and comfort with laboratory work environments, and desire to engage in future iterations given the opportunity. Although non-quantitative, we perceive this as an indicator of significant student engagement, even though some participants did not yield academic success in the program and found it highly challenging given its ambiguity.

Although we observed that students become more certain of their direction in STEM, further longitudinal study is warranted to make claim of this outcome. Additionally, at this point in our assessment we cannot effectively assess the practical outcomes of participation, understanding that the immediate effects observed are subject to a number of factors associated with performance in the high school learning environment. Future studies that track graduates from this program will be prudent, in conjunction with an ever-growing dataset of assessment as well as surveys designed to better elucidate underlying perceptions and attitudes, to continue to understand the expected benefits of this inquiry-focused and partnered approach. Altogether, a multifaceted assessment of our early outcomes suggests significant value of an immersive and iterative interaction with STEM as part of the high school experience. A well-defined divergence from knowledge-based learning, focused on engagement in critical thinking development framed in the cutting-edge of STEM, may be an important step to broadening student perspectives.

In this study, we describe the short-term effects of an inquiry-based STEM educational experience on a cohort of secondary students attending a non-specialized school, and suggest that the framework can be widely applied across virtually all subjects where inquiry-driven and mentored projects can be undertaken. Although we have demonstrated replication in a second cohort of nominally higher SES (S 1 Appendix , Supplementary Fig. 1 ), a larger collection period with more students will be necessary to conclusively determine impact independent of both SES and specific cohort effects. Teachers may also find this framework difficult to implement depending on resources and/or institutional investment and support, particularly if post-secondary collaboration is inaccessible. Offerings to a specific subject (e.g., physics) where experiments yielding empirical data are logistically or financially simpler to perform may be valid routes of adoption as opposed to the current study where all subject cohorts were included.

As we consider Discovery in a bigger picture context, expansion and implementation of this model is translatable. Execution of the scientific method is an important aspect of citizen science, as the concepts of critical thing become ever-more important in a landscape of changing technological landscapes. Giving students critical thinking and problem-solving skills in their primary and secondary education provides value in the context of any career path. Further, we feel that this model is scalable across disciplines, STEM or otherwise, as a means of building the tools of inquiry. We have observed here the value of differential inclusive student engagement and critical thinking through an inquiry-focused model for a subset of students, but further to this an engagement, interest, and excitement across the body of student participants. As we educate the leaders of tomorrow, we suggest that use of an inquiry-focused model such as Discovery could facilitate growth of a data-driven critical thinking framework.

In conclusion, we have presented a model of inquiry-based STEM education for secondary students that emphasizes inclusion, quantitative analysis, and critical thinking. Student grades suggest significant performance benefits, and engagement data suggests positive student attitude despite the perceived challenges of the program. We also note a particular performance benefit to students who repeatedly engage in the program. This framework may carry benefits in a wide variety of settings and disciplines for enhancing student engagement and performance, particularly in non-specialized school environments.

Study design and implementation

Participants in Discovery include all students enrolled in university-stream Grade 11 or 12 biology, chemistry, or physics at the participating school over five consecutive terms (cohort summary shown in Table 1 ). Although student participation in educational content was mandatory, student grades and survey responses (administered by high school teachers) were collected from only those students with parent or guardian consent. Teachers replaced each student name with a unique coded identifier to preserve anonymity but enable individual student tracking over multiple terms. All data collected were analyzed without any exclusions save for missing survey responses; no power analysis was performed prior to data collection.

Ethics statement

This study was approved by the University of Toronto Health Sciences Research Ethics Board (Protocol # 34825) and the Toronto District School Board External Research Review Committee (Protocol # 2017-2018-20). Written informed consent was collected from parents or guardians of participating students prior to the acquisition of student data (both post-hoc academic data and survey administration). Data were anonymized by high school teachers for maintenance of academic confidentiality of individual students prior to release to U of T researchers.

Educational program overview

Students enrolled in university-preparatory STEM classes at the participating school completed a term-long project under the guidance of graduate student instructors and undergraduate student mentors as a mandatory component of their respective course. Project curriculum developed collaboratively between graduate students and participating high school teachers was delivered within U of T Faculty of Applied Science & Engineering (FASE) teaching facilities. Participation allows high school students to garner a better understanding as to how undergraduate learning and career workflows in STEM vary from traditional high school classroom learning, meanwhile reinforcing the benefits of problem solving, perseverance, teamwork, and creative thinking competencies. Given that Discovery was a mandatory component of course curriculum, students participated as class cohorts and addressed questions specific to their course subject knowledge base but related to the defined global health research topic (Fig. 1 ). Assessment of program deliverables was collectively assigned to represent 10–15% of the final course grade for each subject at the discretion of the respective STEM teacher.

The Discovery program framework was developed, prior to initiation of student assessment, in collaboration with one high school selected from the local public school board over a 1.5 year period of time. This partner school consistently scores highly (top decile) in the school board’s Learning Opportunities Index (LOI). The LOI ranks each school based on measures of external challenges affecting its student population therefore schools with the greatest level of external challenge receive a higher ranking 35 . A high LOI ranking is inversely correlated with socioeconomic status (SES); therefore, participating students are identified as having a significant number of external challenges that may affect their academic success. The mandatory nature of program participation was established to reach highly capable students who may be reluctant to engage on their own initiative, as a means of enhancing the inclusivity and impact of the program. The selected school partner is located within a reasonable geographical radius of our campus (i.e., ~40 min transit time from school to campus). This is relevant as participating students are required to independently commute to campus for Discovery hands-on experiences.

Each program term of Discovery corresponds with a five-month high school term. Lead university trainee instructors (3–6 each term) engaged with high school teachers 1–2 months in advance of high school student engagement to discern a relevant overarching global healthcare theme. Each theme was selected with consideration of (a) topics that university faculty identify as cutting-edge biomedical research, (b) expertise that Discovery instructors provide, and (c) capacity to showcase the diversity of BME. Each theme was sub-divided into STEM subject-specific research questions aligning with provincial Ministry of Education curriculum concepts for university-preparatory Biology, Chemistry, and Physics 9 that students worked to address, both on-campus and in-class, during a term-long project. The Discovery framework therefore provides students a problem-based learning experience reflective of an engineering capstone design project, including a motivating scientific problem (i.e., global topic), subject-specific research question, and systematic determination of a professional recommendation addressing the needs of the presented problem.

Discovery instructors were volunteers recruited primarily from graduate and undergraduate BME programs in the FASE. Instructors were organized into subject-specific instructional teams based on laboratory skills, teaching experience, and research expertise. The lead instructors of each subject (the identified 1–2 trainees that built curriculum with high school teachers) were responsible to organize the remaining team members as mentors for specific student groups over the course of the program term (~1:8 mentor to student ratio).

All Discovery instructors were familiarized with program expectations and trained in relevant workspace safety, in addition to engagement at a teaching workshop delivered by the Faculty Advisor (a Teaching Stream faculty member) at the onset of term. This workshop was designed to provide practical information on teaching and was co-developed with high school teachers based on their extensive training and experience in fundamental teaching methods. In addition, group mentors received hands-on training and guidance from lead instructors regarding the specific activities outlined for their respective subject programming (an exemplary term of student programming is available in S 2 Appendix) .

Discovery instructors were responsible for introducing relevant STEM skills and mentoring high school students for the duration of their projects, with support and mentorship from the Faculty Mentor. Each instructor worked exclusively throughout the term with the student groups to which they had been assigned, ensuring consistent mentorship across all disciplinary components of the project. In addition to further supporting university trainees in on-campus mentorship, high school teachers were responsible for academic assessment of all student program deliverables (Fig. 1 ; the standardized grade distribution available in S 3 Appendix ). Importantly, trainees never engaged in deliverable assessment; for continuity of overall course assessment, this remained the responsibility of the relevant teacher for each student cohort.

Throughout each term, students engaged within the university facilities four times. The first three sessions included hands-on lab sessions while the fourth visit included a culminating symposium for students to present their scientific findings (Fig. 1 ). On average, there were 4–5 groups of students per subject (3–4 students per group; ~20 students/class). Discovery instructors worked exclusively with 1–2 groups each term in the capacity of mentor to monitor and guide student progress in all project deliverables.

After introducing the selected global research topic in class, teachers led students in completion of background research essays. Students subsequently engaged in a subject-relevant skill-building protocol during their first visit to university teaching laboratory facilities, allowing opportunity to understand analysis techniques and equipment relevant for their assessment projects. At completion of this session, student groups were presented with a subject-specific research question as well as the relevant laboratory inventory available for use during their projects. Armed with this information, student groups continued to work in their classroom setting to develop group-specific experimental plans. Teachers and Discovery instructors provided written and oral feedback, respectively , allowing students an opportunity to revise their plans in class prior to on-campus experimental execution.

Once at the relevant laboratory environment, student groups executed their protocols in an effort to collect experimental data. Data analysis was performed in the classroom and students learned by trial & error to optimize their protocols before returning to the university lab for a second opportunity of data collection. All methods and data were re-analyzed in class in order for students to create a scientific poster for the purpose of study/experience dissemination. During a final visit to campus, all groups presented their findings at a research symposium, allowing students to verbally defend their process, analyses, interpretations, and design recommendations to a diverse audience including peers, STEM teachers, undergraduate and graduate university students, postdoctoral fellows and U of T faculty.

Data collection

Teachers evaluated their students on the following associated deliverables: (i) global theme background research essay; (ii) experimental plan; (iii) progress report; (iv) final poster content and presentation; and (v) attendance. For research purposes, these grades were examined individually and also as a collective Discovery program grade for each student. For students consenting to participation in the research study, all Discovery grades were anonymized by the classroom teacher before being shared with study authors. Each student was assigned a code by the teacher for direct comparison of deliverable outcomes and survey responses. All instances of “Final course grade” represent the prorated course grade without the Discovery component, to prevent confounding of quantitative analyses.

Survey instruments were used to gain insight into student attitudes and perceptions of STEM and post-secondary study, as well as Discovery program experience and impact (S 4 Appendix ). High school teachers administered surveys in the classroom only to students supported by parental permission. Pre-program surveys were completed at minimum 1 week prior to program initiation each term and exit surveys were completed at maximum 2 weeks post- Discovery term completion. Surveys results were validated using a principal component analysis (S 1 Appendix , Supplementary Fig. 2 ).

Identification and comparison of population subsets

From initial analysis, we identified two student subpopulations of particular interest: students who performed ≥1 SD [18.0%] or greater in the collective Discovery components of the course compared to their final course grade (“EE”), and students who participated in Discovery more than once (“MT”). These groups were compared individually against the rest of the respective Discovery population (“non-EE” and “non-MT”, respectively ). Additionally, MT students who participated in three or four (the maximum observed) terms of Discovery were assessed for longitudinal changes to performance in their course and Discovery grades. Comparisons were made for all Discovery deliverables (introductory essay, client meeting, proposal, progress report, poster, and presentation), final Discovery grade, final course grade, Discovery attendance, and overall attendance.

Statistical analysis

Student course grades were analyzed in all instances without the Discovery contribution (calculated from all deliverable component grades and ranging from 10 to 15% of final course grade depending on class and year) to prevent correlation. Aggregate course grades and Discovery grades were first compared by paired t-test, matching each student’s course grade to their Discovery grade for the term. Student performance in Discovery ( N  = 268 instances of student participation, comprising 170 individual students that participated 1–4 times) was initially assessed in a linear regression of Discovery grade vs. final course grade. Trends in course and Discovery performance over time for students participating 3 or 4 terms ( N  = 16 and 3 individuals, respectively ) were also assessed by linear regression. For subpopulation analysis (EE and MT, N  = 99 instances from 81 individuals and 174 instances from 76 individuals, respectively ), each dataset was tested for normality using the D’Agostino and Pearson omnibus normality test. All subgroup comparisons vs. the remaining population were performed by Mann–Whitney U -test. Data are plotted as individual points with mean ± SEM overlaid (grades), or in histogram bins of 1 and 4 days, respectively , for Discovery and class attendance. Significance was set at α ≤ 0.05.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The data that support the findings of this study are available upon reasonable request from the corresponding author DMK. These data are not publicly available due to privacy concerns of personal data according to the ethical research agreements supporting this study.

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Acknowledgements

This study has been possible due to the support of many University of Toronto trainee volunteers, including Genevieve Conant, Sherif Ramadan, Daniel Smieja, Rami Saab, Andrew Effat, Serena Mandla, Cindy Bui, Janice Wong, Dawn Bannerman, Allison Clement, Shouka Parvin Nejad, Nicolas Ivanov, Jose Cardenas, Huntley Chang, Romario Regeenes, Dr. Henrik Persson, Ali Mojdeh, Nhien Tran-Nguyen, Ileana Co, and Jonathan Rubianto. We further acknowledge the staff and administration of George Harvey Collegiate Institute and the Institute of Biomedical Engineering (IBME), as well as Benjamin Rocheleau and Madeleine Rocheleau for contributions to data collation. Discovery has grown with continued support of Dean Christopher Yip (Faculty of Applied Science and Engineering, U of T), and the financial support of the IBME and the National Science and Engineering Research Council (NSERC) PromoScience program (PROSC 515876-2017; IBME “Igniting Youth Curiosity in STEM” initiative co-directed by DMK and Dr. Penney Gilbert). LDH and NIC were supported by Vanier Canada graduate scholarships from the Canadian Institutes of Health Research and NSERC, respectively . DMK holds a Dean’s Emerging Innovation in Teaching Professorship in the Faculty of Engineering & Applied Science, U of T.

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These authors contributed equally: Locke Davenport Huyer, Neal I. Callaghan.

Authors and Affiliations

Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada

Locke Davenport Huyer, Neal I. Callaghan, Andrey I. Shukalyuk & Dawn M. Kilkenny

Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada

Locke Davenport Huyer

Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, ON, Canada

Neal I. Callaghan

George Harvey Collegiate Institute, Toronto District School Board, Toronto, ON, Canada

Sara Dicks, Edward Scherer & Margaret Jou

Institute for Studies in Transdisciplinary Engineering Education & Practice, University of Toronto, Toronto, ON, Canada

Dawn M. Kilkenny

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Contributions

LDH, NIC and DMK conceived the program structure, designed the study, and interpreted the data. LDH and NIC ideated programming, coordinated execution, and performed all data analysis. SD, ES, and MJ designed and assessed student deliverables, collected data, and anonymized data for assessment. SD assisted in data interpretation. AIS assisted in programming ideation and design. All authors provided feedback and approved the manuscript that was written by LDH, NIC and DMK.

Corresponding author

Correspondence to Dawn M. Kilkenny .

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Davenport Huyer, L., Callaghan, N.I., Dicks, S. et al. Enhancing senior high school student engagement and academic performance using an inclusive and scalable inquiry-based program. npj Sci. Learn. 5 , 17 (2020). https://doi.org/10.1038/s41539-020-00076-2

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DOI : https://doi.org/10.1038/s41539-020-00076-2

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