AI disruptions reveal the folly of clinging to an idealized modern university |
In the past five years, higher education has been in a seemingly endless state of disruption.
In early 2020, the COVID-19 pandemic resulted in a mass rapid pivot to emergency remote teaching. In shifting to unfamiliar digital learning environments, instructors scrambled to replicate classroom learning online. When restrictions lifted, many institutions pushed for a “return to normal,” as though the pre-pandemic educational standard was ideal.
Now, with generative AI disruptions, we are seeing a similar desire to cling to an idealized vision of the modern university. AI has unsettled long-established forms of assessment, simultaneously instigating a return to older assessment models in the interest of “academic integrity.”
If students navigating higher education believe the goal is to pass rather than to learn, then student misuse of generative AI technologies is nothing more than a rational action by a rational agent.
For meaningful university education, we need to shift to a process of building relations and knowledge with others through dialogue and critical inquiry. Part of this means taking lessons from pre-industrial forms of learning and contemporary educational movements.
We also need to shift from compliance-based assessments and grading to meaningful and supportive feedback and opportunities for growth, rooted in teaching and learning with care.
Modern higher education systems in North America often function as a “production enterprise” or a “knowledge........