An AI detector may raise questions about a student’s work, but can it provide enough evidence to support an allegation of plagiarism? In this episode, Jeff Mastromonico speaks with Thomas Pear, a lecturer in the Intensive English Program at the University of Miami and author of Due Diligence Before Alleging AI Plagiarism: An Instructor’s Manual.

They discuss the limitations of AI detectors, the risk of false positives, and other information faculty can consider when student work raises concerns. Thomas also explains why instructors should speak with students before drawing conclusions, how clear AI policies can reduce confusion, and how suspected misuse can become an opportunity for learning.

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AI is already part of how students learn and how professionals work. The challenge for higher education is how to integrate it intentionally while helping students develop the knowledge, judgment, and accountability needed to use it well.

In this episode of Speaking of Higher Ed, Gage Christianson, Program Director and Assistant Professor of Construction Management at the Milwaukee School of Engineering, joins host Arthur Takahashi to discuss MSOE’s approach to integrating AI across courses and degree programs. They explore the importance of foundational knowledge, critical evaluation, ethical use, disclosure, and human responsibility for AI-assisted work.

Gage also shares how faculty can begin incorporating AI without rebuilding an entire course.

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Dr. Jesse Bishop, Director of the Center for Excellence in Teaching and Learning at Georgia Highlands College, joins Andrew Everett to discuss how making the purpose of learning visible can strengthen student motivation. He explains TiLT’s purpose, task, and criteria framework and shares how LEGO Serious Play-inspired experiences can make abstract ideas tangible through building, reflection, and dialogue.

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