AI as a scaffold for learning: From access to judgment
AI can enable deeper engagement, broader exploration, and iterative individualized learning at scale
Meaningful learning should not be about memorization or developing the ability to solve problems for which solutions are already known. Rather, it should focus on doing, experiencing, questioning and deciding, engaging with ideas in context, testing them against reality, and developing the ability to act thoughtfully under conditions of uncertainty.
Top Stories
What higher ed can do about getting research into the K-12 classroom
Educational research has never been more abundant, yet its impact on classroom practice remains uneven at best. While universities continue to produce studies on instructional strategies, student outcomes, and emerging technologies, many K-12 educators rarely engage with this work in meaningful ways.
Building the AI-ready graduate
Artificial intelligence is already part of how students learn, and it is starting to change how work gets done. The question for higher education is how to ensure students understand what these systems are doing, not just the answers they produce.
When opportunities knock: How senior leaders navigate multiple offers with integrity
The path to a senior leadership appointment in higher education or the nonprofit sector is rarely linear. It demands months of reflection, rigorous preparation, and a willingness to be scrutinized at the highest levels.
When AI does the work, who does the learning?
AI is rapidly reshaping education, but not always in ways that support learning. A growing number of AI tools promise to “help” students by doing assignments, writing papers, solving problem sets, or even completing exams automatically.
How well can your institution recover from a ransomware attack?
Most educational institutions believe they’re prepared for a cyberattack. Perhaps they’re running backups, and an incident response plan exists somewhere on the shared drive. Maybe they have a cyber insurance policy in place, or have run a tabletop exercise or two.
What doctoral programs must change in an AI-saturated research environment
Generative AI has moved from novelty to a core tool in a remarkably short period of time. Doctoral students now routinely use AI tools to locate sources, summarize literature, generate outlines, and even draft sections of academic writing.
The pedagogy gap: Redefining the role of faculty and AI in higher education
AI’s rapid integration into the higher-education landscape has prompted a period of profound structural reassessment. For decades, new technology adoption in education has often been driven by a “technology for technology’s sake” mentality–a pursuit of digital innovation that typically prioritizes the novelty of the tool over the efficacy of the intended outcome.
Higher education’s AI denial is not academic integrity–it’s institutional negligence
Higher education is having a familiar conversation in an unfamiliar moment. We are debating whether students “should” use AI, whether it is “ethical,” whether it is “cheating,” whether we can “ban” it, whether we can “detect” it, whether it will “go away.” This is what happens when an institution confuses discomfort with principle.
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The Visual Edge: How High-Impact Technology Redefines Campus Differentiation and Enrollment Strategy
In the current higher education landscape, waning enrollment is still a present challenge. While overall enrollment numbers are showing signs of a rebound, National Student Clearinghouse Research Center data indicates that undergraduate enrollment has yet to fully return to pre-pandemic levels.