Robert E. Wright – TapTalk

Robert E. Wright – AI & Higher Education

Robert E. Wright is a Lecturer in Economics at Central Michigan University.  He is the (co)author or (co)editor of over two dozen major books, book series, and edited collections, including AIER’s The Best of Thomas Paine (2021) and Financial Exclusion (2019). He has also (co)authored numerous articles for important journals, including the American Economic Review, Business History Review, Independent Review, Journal of Private Enterprise, Review of Finance, and Southern Economic Review. Robert has taught business, economics, and policy courses at Augustana University, NYU’s Stern School of Business, Temple University, the University of Virginia, and elsewhere since taking his Ph.D. in History from SUNY Buffalo in 1997. Robert E. Wright was formerly a Senior Research Faculty at the American Institute for Economic Research

Topic:

For decades, professors have claimed that some new technology, from filmstrips to the internet, will revolutionize education by making it easier and cheaper for students to attain important intellectual milestones. Yet standardized test scores have plummeted while tuition and other costs have soared. Moreover, many university students today manage to graduate without the emotional maturity necessary to hold down a job, achieve stable relationships, or raise children. That dismal outcome occurred because the limiting factor was never technology but rather the incentives of administrators, professors, and students. Administrators want retention, professors want “good” evaluations, and students want “good” grades. All three groups implicitly trade with each other. Administrators, students, and ensconced faculty pressure maverick faculty to water down course content or give simple tests of memorization rather than critical thinking skills. That enables most students to obtain increasingly meaningless grades good enough to stay enrolled.

If allowed, Artificial Intelligence could break the entrenched pattern by divorcing content delivery and skills building from assessment. Large language model AIs, like Chat GPT, trained on course content are already capable of creating unique questions/challenges and assessing student responses both pre- and post-course, thus allowing the direct measurement of the change, i.e., student learning and faculty effectiveness. With standards set externally by accrediting bodies or governments, grade compression and watering down can be arrested and faculty judged by real student achievement not student sentiments.