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Separating promise from peril remains a challenge when it comes to generative AI in higher education: Compelling use cases for promoting real learning are growing in number but so too are concerns about students using generative AI to offload not just some cognitive tasks but learning—and even thinking—itself. That dynamic is forcing serious college- and sectorwide conversations about how institutions can reinforce their fundamental mission: teaching and supporting credible, skilled graduates.
A new special report from Inside Higher Ed, “The Reckoning: Training Authentically Skilled Graduates in the Age of Generative AI,” seeks to help practitioners and leaders promote real student learning in the age of, and with, generative AI. Download it here.
Continue the Discussion
On Thursday, Nov. 6, at 2 p.m. Eastern, Inside Higher Ed will host a free webcast discussion on the report and the broader reckoning for teaching and assessment. Register for that here.
The free report draws on research, AI usage trends, expert insights and case studies from the University of Toronto, Arizona State University, Auburn University and the University at Buffalo to demonstrate how institutions are moving beyond offloading and toward constructive engagement with AI. It concludes with an action guide encouraging institutions to rethink rigid AI policies or hands-off approaches in favor of flexible use frameworks, equitable AI tool access, faculty development, assessments that don’t reproduce common triggers for academic misconduct and ongoing evaluation.
“The longer we have these classroom cultures of uncertain guidelines and prohibition, the longer that students are going to be behind on learning the AI skills they’re going to need for the workforce,” says Nicole Muscanell, researcher at Educause.
This independent editorial report is supported by Studiosity.
