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Enhancing Learning in the Age of Generative AI

Edited by Laura Ferdinand, Assistant Director of Content and Communications

As generative AI (GAI) becomes increasingly integrated into learning and teaching in higher education, instructors are navigating complex questions around academic integrity and student learning. While many emerging policies emphasize detection and sanctions, the Searle Center has created a three-part series on pedagogy and GAI, which offers a proactive alternative by centering trust, transparency, reflection, and student agency.

The following three teaching tips introduce each guide in the series, highlighting evidence-driven practices to enhance learning in the age of GAI.

1. Build Critical Thinking by Discussing Verification Strategies

Inviting students to critically engage with GAI is a method for developing broader analytical skills and modeling professional practice to prepare students for meaningful engagement within and beyond the classroom.

Tip: Facilitate a brief class discussion on verification strategies. Ask students to share how they verified GAI outputs and what sources or reasoning they used. Encourage students to verify citations and use academic databases to cross-check facts and claims.

Explore the full guide: “In Brief: Critical Thinking & GAI in Course Delivery.”

2. Deepen Learning through Iterative Revision

Iterative revision reduces students’ misuse or over-reliance on GAI by emphasizing process over product. When assignments include drafts, feedback loops, and scaffolding, instructors minimize the need to use GAI as a shortcut to more polished work.

Tip: Add a low-stakes peer feedback checkpoint. Ask students to exchange a short excerpt of an upcoming assignment and to provide each other with one piece of process-focused feedback (e.g., “What revision strategy do you think would strengthen this section?)

Explore the full guide: “In Brief: Iterative Revision & GAI in Course Design”

3. Harness the Academic Benefits of Metacognition with Reflection Prompts

When students are asked to rigorously reflect on how they arrive at an answer—not just what the answer is—they can engage authentically and are less likely to outsource their work to GAI.

Tip: Use post-assessment reflections, known as wrappers, to prompt students to consider the relationship between GAI and their learning strategies/habits. Examples of such metacognitive questions include:

  • Where did you feel tempted to take a shortcut using GAI?
  • When did you think GAI could do your work better or faster?

Explore the full guide: “In Brief: Metacognition & GAI in Course Assessment.”

Published Fall 2025