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Feedback on performance is one of the most important factors to learning (Cavalcanti et al., 2021). But feedback need not come only from instructors. Students can learn from getting feedback from other students. It not only improves their work but also teaches them to look at work from a reader’s perspective, helping them develop the skills they need to review and revise their own work.
Two factors often keep instructors from using peer feedback in their classes. One of them is the worry that the feedback will be poor or poorly given, and the other is finding a system to facilitate peer feedback on an assignment. But the TAG feedback method can address the former concern, and there are multiple systems for collecting peer feedback that incorporate into a learning management system. We will discuss both in this article.
The TAG feedback system guides students in giving peer feedback. It involves three steps:
We ask students to use this method when providing feedback. For shorter work, they provide it in the LMS discussion forum; for longer works, they use peerScholar to do so. When using the discussion forum, students first post a draft of their work to the forum. Then they must give feedback to at least two other works. Having students post comments and suggestions within a public forum helps build a community around feedback and also allows students to learn from the feedback other students received.
We also provide a rubric to support self- and peer assessment during the draft stage of a project. Explaining the criteria in the rubric helps students give targeted feedback to others and makes it easier for the recipients of the feedback to act on it.
We have found that students really like this way of providing feedback and take this responsibility seriously. After receiving feedback, learners have time to work on their final drafts or projects and decide whether to act on the feedback given or not. They are also required to write a reflection on their processes of working on the project, giving feedback, and receiving feedback. If they choose not to alter their work on the basis of the suggestions provided to them, they have the opportunity to justify their position.
peerScholar is a web tool used at several institutions for collecting peer feedback.
Students start by watching short videos on the peerScholar website or on the app. (Instructors can embed them into the LMS page too). These microlearning video series gradually build learner feedback literacy skills. Students then submit their work through the app integrated within the LMS. The app assigns each student another student’s work, which is presented anonymously, and students provide anonymous feedback on the work.
peerScholar provides instructors with a number of options for channeling student feedback. They can give students multiple-choice questions for a particular evaluation criterion—for instance, asking students to rate the spelling in an assignment from “no spelling errors” to “numerous spelling errors.” Instructors might also have students enter point values, star ratings from one to four , or 1–7 scale ratings. Finally, instructors can give students boxes for entering open-ended comments as well as the opportunity to provide in-text comments within the work.
The system sends all the information to both the receiving student and the instructor (Figure 1). The student then revises their work and submits it to the instructor for a grade.
In each task or step within peerScholar, instructors can add or modify dates and rubrics and add or remove instructions. Additionally, instructors can change the number of reviews students are required to give and can even choose group feedback or a case study activity. This makes peerScholar fairly customizable to suit a variety of course delivery types and fields.
Students might feel hesitant to provide in-depth feedback at first, but over time they start to feel more comfortable giving and receiving it. Peer feedback also helps build community as students help and get help from others. Not only does the process improve students’ work, but it also helps cultivate valuable skills that they will likely use in the future.
Cavalcanti, A. P, Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y., Gašević, D., & Mello, R. F. (2021). Automatic feedback in online learning environments: A systematic literature review. Computers and Education: Artificial Intelligence, 2, Article 100027. https://doi.org/10.1016/j.caeai.2021.100027
Let’s Talk Science. (n.d.). Learning strategies: TAG feedback. https://letstalkscience.ca/educational-resources/learning-strategies/tag-feedback
Elena Chudaeva, PhD, is a professor of physics and mathematics and Katrina Lagace, MA, is a humanities professor at George Brown College.