A&S Teaching & Learning Community of Practice 2025-26: Instructor evaluation of course-specific multiple-choice questions created via a generative AI tool

Assessment of student learning often relies on multiple-choice questions (MCQs). Students can struggle with these questions for numerous reasons such as uneven level of difficulty between tests (e.g. the ratios of recall vs application questions). To address this, we developed a generative AI (gAI) tool designed to rapidly compose accurate, consistent and content-specific MCQs. We then asked instructors with expertise in the content area to assess both the gAI tool- and instructor (human)-generated MCQs using a rubric that scores for accuracy, clarity and strength of distractors. In this workshop, we will present the findings of our study. 

Presenters:

Stavroula Andreopoulos, Professor, Teaching Stream, Department of Biochemistry 

Matthew Reid, School of Continuing Studies, Department of Physiology 

Michelle French, Professor, Teaching Stream, Department of Physiology 

Christine Wong, Assistant Professor, Teaching Stream; Associate Chair, Undergraduate, Department of Health and Society, UTSC 

Nohjin Kee, Professor, Teaching Stream, Department of Physiology

For more upcoming CoP sessions, visit our Quercus site.