Design Feedback for Learning

Effective feedback is less about the amount of information you provide and more about whether students can make sense of it and use it to improve their learning. Useful feedback is focused, connected to clear criteria or expectations for quality, and provided at a point when students can act on it. Selecting when and how to provide feedback can help direct instructor and teaching assistant time toward the places where feedback will be most useful.

Start with the Purpose

Choosing among automated, rubric-based, collective, peer, self-assessment, and individualized feedback allows you to match the type of feedback to the learning you want to support and the time available to provide it.

Before deciding how to give feedback, consider:

• What do students most need to know? Focus feedback on the most important areas for improvement rather than commenting on everything.
• When will students be able to use it? Feedback has greater value when students can apply it through revision, practice, or a subsequent task.
• How much feedback can students realistically use? A few clear priorities are often more actionable than extensive comments.
• Where could useful feedback come from? Feedback can come from multiple sources, including instructors, TAs, peers, students themselves, or automated systems.
• How will students be supported to use it? Consider what opportunities, guidance, or follow-up will help students interpret and act on feedback rather than assuming comments alone will lead to improvement.
• What might make the feedback easier to access, understand, and use? Consider whether the tone, language, format, technology, or mode of feedback may create barriers to students engaging with it.

Choosing a Feedback Approach 

No single feedback approach works equally well in every context. Choose and combine approaches based on the learning you want to support, student needs, the assessment task, class size, and the time and resources available. For example, students might receive rubric-based feedback from a peer, automated feedback on a quiz, and collective feedback from the instructor on common patterns across an assignment. 

Time Feedback for Impact

The amount and type of feedback you provide should depend less on whether an assessment is formally labeled formative or summative and more on whether students will have an opportunity to use the feedback.

During learning

When students have opportunities to revise, practice, or complete a related task, focus feedback on what they should do next. More detailed feedback is often most useful here because students still have an opportunity to act on it.

For example: 

• identify one or two priorities for improvement;
• ask students to revise part of an assignment;
• provide feedback on an early component of a larger project;
• use patterns from a quiz or assignment to determine what needs to be revisited in class;
• ask students to apply previous feedback when completing the next task.

At the end of a learning cycle

When students have limited opportunity to revise or apply feedback within the course, focus on helping them understand how their work was judged and what they should carry forward into later work.

This may include concise comments explaining:

• key strengths
• the most significant areas for development
• how the assessment criteria were applied
• learning that may transfer to subsequent courses, professional practice, or related work

Help Students Use Feedback

Feedback contributes to learning when students have opportunities to make sense of it and use it to improve subsequent work or learning strategies. Consider building a small feedback activity into the assessment process rather than assuming students will automatically know what to do with your comments.

Students might:

• identify the two most important changes they will make on their next assignment
• revise a section of their work using the feedback
• compare their work with an exemplar and identify what it reveals about quality
• explain how feedback from an earlier task influenced a later one
• categorize comments into strengths, questions, and next steps; or
• use feedback to develop a short learning or revision plan

These activities also help students develop feedback literacy: understanding their active role in feedback, making judgments about quality, managing their responses to feedback, and deciding how to act on it.

Using AI for Student Feedback

If you are considering using generative artificial intelligence (GenAI) for student feedback, use it to complement rather than replace instructor judgment. GenAI can provide timely feedback at scale, but instructors remain important for context, dialogue, and nuanced disciplinary judgment.

GenAI tools come with clear trade-offs. They can quickly produce detailed guidance and step-by-step corrections, but overly prescriptive feedback may reduce students' opportunities to reflect, make judgments, and decide how to improve their own work.

GenAI can generate feedback, but instructor involvement remains important for context, dialogue, and nuanced judgment, especially for complex or higher-stakes work. Khayer and Mirzaei recommend a “hybrid” approach, grounded in their synthesis of 29 studies:

• Use GenAI selectively for lower-stakes feedback: AI may help provide rapid, criteria-aligned guidance on early work, while students still have opportunities to review, question, and act on it.
• Focus instructor attention where it adds the most value: Prioritize context, dialogue, and nuanced disciplinary judgment, especially for complex or higher-stakes work.

When evaluating student work, you can safely use institutionally approved tools like Google Gemini. Under the U of A’s AI Data Safety Guidelines, student submissions are classified as "protected" data, and the university's license ensures that tool providers will not retain or use student work to train AI models. 

But if you incorporate GenAI into your grading workflow, lead by example. Be open with your students about how and when you use these tools. Transparency is a core principle of the U of A Framework for the Responsible Use of AI.

Putting it into practice

1. Timing: Where do students most need feedback to improve before their next significant assessment? 
2. Use: What do students need to do with the feedback you provide — revise, practice, or apply it to a subsequent task? 
3. Approach: Which time-intensive, narrative comments could be replaced with automated, rubric-based, or group feedback without sacrificing student development?
4. Patterns: Where are you repeatedly writing the same comments? Could those patterns become collective feedback, a rubric criterion, an exemplar, or an instructional resource?
5. Peer Feedback: Where in your course could peer feedback help students develop evaluative judgment and draw inspiration from each other before submitting major work?

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Learn more

Carless, D., & Winstone, N. (2023). Teacher feedback literacy and its interplay with student feedback literacy. Teaching in Higher Education, 28(1), 150–163.

CAST (2024). Universal Design for Learning Guidelines version 3.0. 

Centre for Teaching and Learning, University of Alberta. (2026, March 31). Ask the CTL scholar: Getting students to use instructor feedback.

Henderson, M., Boud, D., Molloy, E., Dawson, P., Phillips, M., Ryan, T., & Mahoney, P. (2018). Feedback for learning: Closing the assessment loop – Final report. Australian Government Department of Education and Training.

Khayer, B., & Mirzaei, S. (2025). Enhancing feedback personalisation with AI-generated analytics: A narrative review. Learning Letters, 5, Article 50. 

Lee, S. S., & Moore, R. L. (2024). Harnessing Generative AI (GenAI) for automated feedback in higher education: A systematic review. Online Learning, 28(3).