AI in higher education is no longer just a technology issue. The larger question is whether colleges and universities will redesign learning so students develop judgment, critical thinking, and decision-making skills in a world where AI can already generate summaries, essays, and plausible answers on demand.

In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with France Hoang, Founder and CEO of BoodleBox, about how higher education leaders can think more clearly and more strategically about AI. Hoang explains why AI should be used to augment human capability rather than replace it, and why educators matter even more in a world where AI can get students only part of the way.

Drawing on examples from the classroom and across campus operations, Hoang outlines how colleges can move from AI independent to AI enabled and eventually toward AI native models of learning and work. He also explains why colleges need to redesign assignments, rethink pedagogy, and focus more intentionally on the development of domain expertise, reflection, and higher-order thinking.

This episode is especially relevant for presidents, provosts, boards, CIOs, and academic leaders who need to make decisions about teaching, student support, workforce preparation, and institutional implementation in an AI-enabled environment.

Topics Covered

• Why AI is forcing higher education to rethink what students should learn when AI can already do much of the visible academic work
• Why AI often produces a B-minus answer and why domain expertise still matters
• How the loss of routine entry-level work may weaken the apprenticeship path for graduates
• Why colleges need to redesign assignments around judgment, application, and reflection
• How faculty can use simulations, case studies, and human-AI collaboration in the classroom
• What AI independent, AI enabled, and AI native mean for institutional strategy
• How AI can support advising, counseling, and career services without replacing human connection
• Why AI adoption is as much a training, culture, and change-management issue as it is a technology issue

Real-World Examples Discussed

• A marketing course at Point Loma where students build an AI assistant from their own class notes and use it in case studies and simulations
• A writing program at Pikes Peak State College where students compare their own writing with AI-generated writing and reflect on the differences
• A reimagined history assignment that uses role-based simulation instead of a traditional reading-and-essay model
• Institutional examples that show how colleges can move toward more applied, AI-enabled, and AI-native learning environments

Three Key Takeaways for Higher Education Leaders

1. Leaders need to know where their institution currently sits on the AI continuum, from AI independent to AI enabled to AI native.
2. AI adoption is as much a training and human resource issue as it is a technology issue, so institutions need to invest in people as much as platforms.
3. A culture of innovation, experimentation, and collaborative implementation will outperform a purely top-down rollout.

This episode offers a practical framework for higher education leaders who want to move beyond AI policy and think more seriously about how learning, assessment, student support, and institutional strategy need to change when AI can already do much of the lower-level work.

Read the transcript: https://changinghighered.com/ai-in-higher-education-teaching-human-judgement/

#HigherEducation #ArtificialIntelligence #HigherEducationPodcast