Instructor Course Introduction Modeling AI Transparency

Professor Nirusha Thavarajah is an Associate Professor in the Teaching Stream in Physical and Environmental Sciences at the University of Toronto Scarborough. She holds a Ph.D. in Synthetic Organic Chemistry, an LL.M. in Intellectual Property Law, and an M.Ed. in Higher Education, and teaches chemistry courses including Organic Chemistry and Advanced Bio-Organic Chemistry. Prof. Thavarajah has integrated generative AI into her teaching by using structured exercises where students critically evaluate AI-generated responses, fostering analytical thinking and deeper comprehension of course material. To maintain academic integrity, she has restructured lab assessments by shifting online post-lab reports and quizzes to in-person settings completed during lab time. This approach prioritizes active learning while minimizing reliance on AI for assessments.

Nirusha Thavarajah Associate Professor, Teaching Stream, Department of Physical & Environmental Sciences

Objectives

As part of CHMA10’s (Winter 2026) comprehensive course redesign, Professor Thavarajah included a reflective statement in the lab manual explaining the pedagogical rationale behind major structural and assessment changes, with particular attention to how and why the course integrates generative AI. Rather than issuing blanket prohibitions or permissions, the reflection models transparent decision-making by openly acknowledging the instructor’s own AI use (using Copilot to generate instructional images throughout the manual for improved accessibility), while simultaneously explaining why certain student AI uses are permitted (concept map creation) and others prohibited (reflective writing and analysis).

This modeling is pedagogically significant: students witness their instructor making nuanced judgments about AI appropriateness based on learning objectives, not arbitrary rules. The reflection explicitly distinguishes between tasks where AI scaffolds learning (visualization, organization) versus tasks requiring authentic intellectual engagement (critical thinking, original analysis). By communicating this reasoning transparently, the reflection builds student trust, develops their capacity for contextual judgment, and prepares them to make similar responsible decisions about AI use in future academic and professional scientific work where such technologies are ubiquitous but their appropriate use requires ongoing ethical discernment.

Process

The communication was implemented as a multi-page reflective statement included in the lab manual and made available to students at the beginning of the semester. The approach included:

Step 1: Position Reflection Prominently in the Lab Manual

Include “Rethinking, Revising and Redesigning the Lab Content Delivery and Assessments: Instructor’s Reflection” immediately after welcome letter
Make accessible before first lab session so students understand rationale before experiencing changes

Step 2: Explain Pedagogical Goals and Course Redesign

Contextualize revisions: “enhance the lab materials, making them more engaging, accessible, and meaningful for students”
Address key structural changes (immediate post-lab completion, expanded pre-lab questions, repositioned learning outcomes) with clear rationale about authentic scientific practice and immediate feedback

Step 3: Model and Explain GenAI Integration Transparently

Openly acknowledge instructor’s own AI use: Explain that Copilot-generated images throughout the manual enable students to “interpret each instruction visually” for improved accessibility
Detail student AI-integrated assignment rationale: Concept map activity “aims to integrate AI tools into the learning process to enhance understanding while emphasizing the importance of human reasoning”
Distinguish permitted vs. prohibited uses: Explain that AI “can improve efficiency and tailor resources” but “cannot replace the critical thinking, problem-solving, and creativity inherent in traditional learning”
Model thoughtful approach to emerging technology rather than blanket prohibition or uncritical adoption

Step 4: Connect to Student Benefits and Future Practice

Synthesize how changes collectively improve the overall learning experience and ensure that students are well prepared for future scientific work
Frame GenAI policies as preparation for professional environments requiring ethical technology decisions

Pedagogical Rationale

This instructor reflection serves multiple pedagogical functions beyond policy communication. By openly disclosing her own AI use for generating instructional images, Professor Thavarajah models the transparent, reflective practice students are expected to develop. The reflection builds trust by treating students as capable of understanding nuanced decision-making rather than simply following rules: explaining why AI is appropriate for some tasks but not others respects students’ intellectual maturity and invites them into the reasoning process.

By making her own decision-making visible, the instructor creates an apprenticeship model where students learn ethical technology judgment not through abstract rules but by witnessing how an expert navigates the same questions they face. This approach reduces anxiety, demystifies AI policies, and cultivates the contextual judgment students need for future academic and professional environments.

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