Enhancing Reflective Practice in the Age of AI

Reflective practice is a cornerstone of effective learning, helping students consolidate their knowledge, understand its significance, and apply it in future contexts. In the era of generative AI, fostering genuine reflection is essential for preparing students to be critical consumers and co-creators with AI. Here’s how you can enhance reflective practice and make it more AI-resistant.

The Importance of Reflection

Reflective practice is vital because it:

• Consolidates Learning: Helps students integrate and solidify what they have learned.
• Encourages Critical Thinking: Promotes questioning of assumptions and deeper understanding.
• Fosters Personal Growth: Aids in self-awareness and personal development.
• Prepares for Future Challenges: Equips students to work independently and with AI.

Making Reflective Practice More AI-Resistant

While personal reflection assignments were once considered highly AI resistant, the reality is that current Generative AI can generate strong reflective content. However, there are ways to structure reflective assignments that make it more challenging to use AI exclusively and that require students to feed AI specific information about their course leaning and context (thereby forcing some reflection) to generate convincing outputs. To help encourage genuine reflection rather than AI-generated work, consider these strategies:

• Personalized Prompts: Use prompts that require personal insights and experiences and that ask students to connect learning to specific course activities.
• Consolidation of Course Interactions: Ask students to refer to specific statements and activities in the course and attribute them to a specific student or describe their context before discussing their impact on learning.
• Document the Process: Have students detail their reflective process, including initial thoughts and changes in perspective.
• Interactive Elements: Incorporate peer reviews and discussions to deepen understanding.
• Ethical Reflections: Ask students to consider the ethical implications of using AI in their work.
• Regular Check-Ins: Implement ongoing check-ins to monitor reflective progress.

Provide Modelling and Structure for Reflection

Careful reflective practice is a skill that requires teaching and feedback. Students will need to know what you are looking for and how assessment will occur. Here’s how to structure it:

• Teach Reflection: Explain what good reflection looks like and provide examples.
• Share Models of Reflective Practice: Students may benefit from a structured model to ensure their reflection goes beyond reporting what happened to making meaning of it.
• Clarify AI Use: Be explicit about whether AI can be used in the reflection process. Generally, independent reflection is more beneficial.
• Connect Metacognition with Future Success: Stress the need for students to reflect independently to develop metacognitive skills they will need to work on their own and with AI in the future
• Practice with Peers: Allow students to practice reflection with classmates.
• Provide Feedback: Give constructive feedback or utilize peer feedback to help students improve.

A USask Example

For a look at how reflection as assessment can be successfully applied, we can consider the example of Professor Hayley Hesseln in the College of Agriculture and Bioresources. Hesseln assigns students in her Agricultural Economics course, delivered both online and face-to-face, to write a reflective paper about their learning for the final exam. She remarked that it can be quite surprising how such an activity can show evidence of student learning. “I find that by allowing students to tell me what they learned, they realize they learned much more than they initially thought,” explains Hesseln. “Having to put it into words and having them discuss the application and importance also embeds the lessons that much further.”

The questions that Hesseln uses for her final are in general terms and could be easily used in other disciplines:

1. What did you learn (do not give me a list of topics or repeat lectures).
2. Why is it important to you?
3. How will you use it (consider your job, future classes, higher education, life in general).

Hesseln provides learners with a rubric (shown below), written from the perspective of a student to guide their writing and allow her to mark their work.

An activity such as Hesseln’s described above could also be adapted into an oral exam (link to new oral exam article) if desired.

Conclusion

Reflective practice is essential for deep learning and personal growth, especially in the context of AI. By clarifying the purpose, planning practice and feedback, and making reflection activities AI-resistant, educators can foster meaningful reflection that prepares students for the future.

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^{Title image credit: USDAGov - Flickr}

^{This article was created with the assistance of AI tools, as described in the  GMCTL AI Disclosure Statement.}

This resource is shared by the Gwenna Moss Centre for Teaching and Learning (GMCTL), University of Saskatchewan, under a CC BY-NC-SA license.