Contributing Editor: Kim Arnold, Director, Teaching and Learning Program, EDUCAUSE.
As generative artificial intelligence reshapes conversations about teaching, learning, and assessment, colleges and universities have an opportunity to look beyond what learners produce and better understand how human capability develops over time, strengthening teaching, feedback, and assessment through richer evidence of learning.
Higher education institutions can better prepare students for an artificial intelligence–augmented workforce by shifting from teacher-centered models to facilitative instructional approaches that develop the enduring professional capacities that become more, not less, valuable as AI transforms work: critical thinking, collaboration, creativity, and adaptability.
Artificial intelligence (AI) will transform the classroom into an interactive ecosystem of guidance and support. The Triadic Learning Ecosystem (TLE) offers an architecture of that near future, connecting teachers, students, and AI-enabled tools in a collaborative model of learning.
![EDUCAUSE QuickPoll Results: Instructional Continuity in the Face of Major Disruption [infographic]](https://er.educause.edu/-/media/images/multimedia/2026/june-2026-instructional-continuity-quickpoll-infographic-header.png)
Recent disruptions to the educational systems that support many colleges and universities have highlighted the need for institutions to develop plans for instructional continuity to safeguard the educational activities of higher education.
The interruption of service for the Canvas LMS after a ransomware attack left many in higher education reckoning with how to sustain academic activities when critical services are down.
Generative artificial intelligence can expand the reach of open educational resources, but educators and institutions need a clear framework for licensing, disclosure, and responsible use.
The SAMR + AI Matrix is a structured learning design tool that aligns the SAMR Model with Bloom's Taxonomy, mapping levels of technological use to cognitive demand to guide instructors in determining how artificial intelligence (AI) could impact student work. This matrix is operationalized through a five-step framework that helps instructors deliberately design for the presence of AI in learning experiences.
Listening to faculty concerns about generative AI can help institutions respond with more clarity, precision, and trust.
Driven by a bottom-up partnership between the Faculty Center for Teaching and Learning and the Division of Digital Learning, the University of Central Florida established an evolving campus infrastructure of policies, training, and a national conference to guide the ethical and effective integration of generative AI into teaching and learning.
As generative artificial intelligence reshapes instructional workflows at colleges and universities, a four-level transparency framework can help education developers calibrate documentation and disclosure practices to support ethical responsibility and maintain student trust.
