2.3 GenAI and teaching integrity

Meranda Salem, Sessional Instructor, PhD, Electrical and Computer Engineering, FASE                 

Filtering the Noise: Tools, Trends, and Tensions        

The rapid adoption of generative artificial intelligence (GenAI) tools in higher education presents both opportunities and challenges for maintaining teaching and assessment integrity. Rather than viewing GenAI solely as a threat to academic honesty, this proposal frames it as a pedagogical tool that must be intentionally integrated through evidence-informed course design. Teaching integrity in the GenAI era is supported not by surveillance or detection technologies, but by transparent expectations, authentic assessments, and student accountability.

This approach emphasizes clearly defining acceptable and unacceptable uses of GenAI, aligning AI use with learning goals, and designing assessments that require students to demonstrate understanding, reasoning, and decision-making. Iterative assessment structures, such as drafts, design reviews, reflections, and oral explanations, encourage responsible AI use while preserving student ownership of learning. Students are required to disclose how GenAI tools were used and to critically evaluate and validate any AI-generated output.

By focusing on process-oriented assessment and professional communication, this framework promotes ethical engagement with GenAI while maintaining fairness and rigor. It also addresses equity concerns by recognizing differences in access to AI tools and emphasizing learning outcomes over tool proficiency. Ultimately, this approach supports academic integrity by reinforcing the principle that GenAI should augment, rather than replace, student thinking, thereby preparing learners for responsible professional practice in AI-enabled environments.