Study: Graduate Teaching Course Integrating ChatGPT, Perplexity and Copilot Improves AI Knowledge

A study published in the Journal of the Scholarship of Teaching and Learning examined the integration of ChatGPT, Perplexity and Microsoft Copilot in a graduate course preparing future faculty members. Using a mixed-methods approach combining pre- and post-course surveys with structured observations, the researcher studied graduate students in a University Teaching in Human Sciences course. Findings showed significant improvements in students' AI knowledge and confidence in using AI tools for educational purposes, but effectiveness depended heavily on structured facilitation and intentional integration with evidence-based teaching practices.

This study directly addresses the preparation of future higher-education faculty, indicating that bringing AI tools into teaching requires integration with evidence-based teaching practices and structured facilitation. For teacher-education programs, it offers a reference for course design; for AI education product practitioners, it shows that tool value depends on how it is organized within teaching scenarios. The study is based on surveys and observations in a single graduate course, so its sample and scope are limited and conclusions should not be extrapolated to other levels or institutions. Graduate teacher-preparation courses can reference designs that combine AI tools with evidence-based teaching practices. Adoption of AI education products in higher education may depend more on accompanying instructional facilitation and training.