White paper highlights transformative assessment methods in response to ChatGPT's threat to traditional education, featuring insights from Center for 21st Century Universities thought leaders.

In this white paper, we mainly discuss the impact of generative language models on the assessment of students’ learning in the higher education setting and provide example alternative or other transformative assessment methods that faculty can consider adopting in response to threats posed by ChatGPT.

Next, we discuss ideas on how faculty should adapt to the emergence of AI language models like ChatGPT. To garner knowledge about transformations that are expected to happen within the classroom and beyond, we incorporate perspectives and insights from our interviews with the thought leaders of the Center for 21st Century Universities (C21U), Dr. Ashok Goel and Dr. Stephen Harmon. Goel is Chief Scientist at C21U, a Professor of Computer Science and Human-Centered Computing, and a Principal Investigator of the National Artificial Intelligence Institute in adult learning and online education (AI-ALOE). Harmon is Executive Director at C21U, Professor at the College of Design, and Associate Dean of Research in Georgia Tech Professional Education (GTPE).

Finally, we conclude by offering a set of recommendations for enhancing assessment practices in the era of rapidly evolving AI technology.

Read 'ChatGPT and Assessment in Higher Education' White Paper

Discover the Future of Education Assessment: Read our White Paper to Learn About Transformative Methods for Adapting to AI Language Models like ChatGPT and Gain Insights from C21U Thought Leaders.

Artificial Intelligence Research

Artificial Intelligence (AI) can enhance education in numerous ways, such as providing personalized learning experiences, automating administrative tasks, improving student engagement, and facilitating data-driven decision-making. C21U is exploring the next frontier of education.

About generative content

Content on this page was generated (wholly, or in part) using a Large Language Model tool. All generative content is reviewed, edited, and revised to publication, and follows the Institute’s Editorial Style Guide.