Monitoring, Evaluation, and Reflection on AI Use

Evaluating Impact

In an earlier section of this guide, we introduced exercises to help you identify specific problems or areas of curosity regarding AI. Now that we’ve explored a range of tools and ideas for embedding AI in your educational and research practices, it’s timely to reflect on those initial exercises.

The emerging field of AI in education presents opportunities to develop methods for assessing the impact of AI on teaching and research. Below, you’ll find a collection of research questions / curiosities, with potential methodologies to assess the impact and effectiveness of AI tools.

Quantitative Insights

Grades

Engagement and Participation

Critical Thinking and Problem-Solving

Accessibility, Diversity, Inclusivity

Teaching Practices and Workload Management

Scope and Depth of Research Findings

Efficiency in Research Processes

Publication and Dissemination

Qualitative Insights

 

Student Feedback on AI-Enhanced Learning

Faculty Perspectives on AI Integration

Impact of AI on Classroom Dynamics

AI’s Role in Inclusivity and Accessibility

Changes in Student Motivation and Attitudes

Faculty Workload and Time Management

AI’s Influence on Research Methodologies

Perceptions of AI in Enhancing Research Quality

Challenges and Ethical Considerations in AI-Driven Research

License

Icon for the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

The Curious Educator’s Guide to AI Copyright © 2024 by Paul R MacPherson Institute for Leadership, Innovation and Excellence in Teaching is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

Share This Book