Artificial Intelligence (AI) Task Force

AI and Assessment

Generative AIs have heightened faculty’s concerns about a potential explosion in student plagiarism and cheating. By now it has become clear that rather than just focusing on AI as a threat to academic integrity, educators can use this moment as an opportunity to re-examine and update teaching and assessment practices. Resources below will help generate ideas for how re-examination can work. We also encourage faculty to review resources on AI Detection Tools which highlight their limitations. 

For a brief overview of authentic assessments you can check out Macmillan’s primer on authentic assessment and the Minerva Project White Paper, “A Systematic Approach to Authentic Assessment.” 

  • Assessment and Generative AI - Developing Robust Assessment in the Light of Generative AI Developments
    This document reports the results of a study conducted by researchers from The Open University. Addressing the challenges and opportunities posed by Generative AI tools (GAI) for assessment in higher education, the study examined GAI capabilities in order to enable institutions to risk-assess current assessment practices, identify potential changes, and evaluate the benefits of a faculty training program. The useful discussion begins on p. 43, and the study’s most important conclusions are that the majority of traditional assessment types can be completed by GAI and that “...questions typically aligned with ‘authentic assessment’ are currently the most robust type of assessment.”