AI in Higher Education
AI in Higher Education explores current developments in artificial intelligence and their implications for colleges and universities. Episodes examine how AI can enhance teaching and learning, support student success, improve the delivery of student services, and increase institutional effectiveness and efficiency. The podcast also considers emerging challenges and questions surrounding the responsible use of AI in higher education, drawing on recent developments, research, and examples from institutions and organizations. Created by Ralph Aldredge, PhD, PE, Executive Associate Dean in the College of Engineering and Professor of Mechanical and Aerospace Engineering at the University of California, Davis. AI in Higher Education...
Practical AI in Higher Education: Faculty Development, Course Design, and Student Services
SUMMARY:
This episode examines how universities are moving from broad AI principles to practical, supported applications in faculty development, course design, assessment, and student services. It also considers why bounded use, human judgment, and iterative evaluation matter for responsible adoption.
DESCRIPTION:
Universities are developing shared resources, faculty workshops, course-design tools, and discipline-specific guidance to help educators integrate AI without treating it as a substitute for professional expertise. The episode highlights initiatives at MIT, Georgia Tech, the University of Michigan, and Kennesaw State.
It also examines the University of Leicester’s narrowly focused student-service ag...
Beyond the Chatbot: Five Reality Checks for AI in Higher Education
This special gateway episode of AI in Higher Education revisits five developments from the series that challenge simple assumptions about AI in higher education.
It asks what actually improves learning, how AI can support timely student intervention, what institutions must govern, and whether curricula reflect the AI-enabled work employers expect.
Topics include a randomized trial in which course-integrated AI tutoring was associated with lower grades and LMS engagement; Purdue’s AI-supported practice, feedback, and resubmission model; Austin Community College’s digital twin initiative; Jisc’s pilot of institution-specific AI assistants; and an Ithaka S+R st...
AI in Higher Education: Evidence, Faculty Pilots, and Campus AI Readiness
A randomized university trial found that students given access to a course-integrated generative AI tutor had lower final grades and LMS participation, with larger estimated losses among first-generation students. The finding underscores the need to evaluate AI tools using learning, engagement, and subgroup outcomes—not simply adoption or convenience.
The episode also explores faculty-led AI pilots at the University of Michigan and the University of Washington, where experiments are tied to specific learning challenges, assignments, and feedback cycles.
It concludes with public-system AI coordination through NASH and the University of Alabama’s campuswide AI literacy expe...
How Higher Education Is Testing AI for Teaching, Literacy, and Student Support
This episode examines a shift from broad AI experimentation toward focused applications in higher education. Examples include Stanford’s course-level AI pilots, Purdue’s AI-supported iterative feedback and inquiry-driven AI literacy work, and new approaches to student support and campus-wide AI fluency.
The discussion considers how institutions can use AI to extend teaching and advising capacity while keeping human judgment central. It also explores practical questions about evidence, assessment, data governance, student consent, and responsible implementation.
TOPICS:
- Course-level AI pilots and evidence-based experimentation
- AI-supported feedback, resubmission, and mastery learning
- Disc...
Bounded AI Pilots in Higher Education: Feedback, Tutoring, Canvas, and Student Success
This episode examines how higher-education institutions are moving from broad AI announcements toward bounded, evaluated implementations. Topics include New Jersey’s statewide AI readiness grants, Georgia State’s AI-supported writing feedback, and the University of Texas at Arlington’s question-driven AI tutor.
The episode also explores the University of Alberta’s Canvas-integrated LearnWise pilot and the University of North Carolina at Pembroke’s human-centered AI and student-success initiative. Across these examples, the focus is on formative feedback, guided reasoning, human review, shared infrastructure, and evidence of educational or student-support value.
The discussion concludes with practical considerat...
Higher Education AI: From Faculty Playbooks to Active Learning at Scale
This episode examines how higher-education institutions are moving from broad AI principles toward focused implementation. Topics include Georgia Tech’s faculty-authored AI playbook, MIT’s cross-institution faculty-development pilot, and the University of Sydney’s research into course-specific AI feedback.
The episode also considers the University of Leicester’s bounded, source-grounded student assistant and Arizona State University’s large-scale research on AI-supported active learning. Across these examples, the discussion focuses on human oversight, discipline-specific context, scaffolded feedback, and evaluating whether AI improves learning and student services.
The voice in this episode is AI-generated.
TOPICS:
- Facul...
How Universities Are Testing AI: Pilots, Student Partnerships, Skills, and Safeguards
This episode examines how universities are moving from broad AI mandates toward structured experimentation. We look at faculty-led pilots at Michigan and Cornell, Georgetown’s student–faculty course redesign model, and Washington University’s reported results from AI-literacy and faculty-development initiatives.
DESCRIPTION:
This episode examines how universities are moving from broad AI mandates toward structured experimentation. We look at faculty-led pilots at Michigan and Cornell, Georgetown’s student–faculty course redesign model, and Washington University’s reported results from AI-literacy and faculty-development initiatives.
The episode also explores Ithaka S+R’s findings on the gap between em...
How Universities Are Moving from AI Experimentation to Governed Implementation
This episode examines how higher-education institutions are moving from broad AI experimentation toward managed, evidence-oriented implementation. Examples include Jisc’s secure AI assistants for professional services, MIT’s AI-aware teaching framework, and Stanford’s faculty-led education projects.
The episode also explores Purdue’s combination of AI-supported grading, iterative feedback, and learning analytics, along with the University of Surrey’s managed AI access and institution-wide assessment review. Across these cases, the focus is on assessment redesign, human oversight, governance, and evidence of student learning.
The discussion concludes with practical options for institutions, including narrowly scoped professional-services pilots, ev...
Simulations, AI Literacy, and Critical Thinking
This episode examines how universities are moving beyond general-purpose AI adoption toward structured, discipline-specific learning environments. We explore an AI-powered simulation center at the University of Arkansas at Little Rock and Texas A&M’s AI-avatar practice environment for business communication.
The episode also considers student-designed AI-literacy lessons at the University of Virginia, Purdue’s adaptive inquiry-driven AI-literacy project, and Cornell’s research into AI, reflection, and critical thinking.
Together, these developments highlight the importance of scenario design, clear rubrics, faculty coaching, student partnership, and evaluation plans that measure learning—not just efficiency.
TOPICS:<...
Bounded AI in Higher Education: Pilots, Learning Evidence, Feedback, and Governance
This episode examines how universities are moving from broad access to general-purpose chatbots toward bounded, course-grounded AI. We look at the University of Alberta’s Canvas-based LearnWise pilot and the University of Washington’s assignment-specific AI agents.
The episode also explores research showing that AI access alone does not guarantee better learning, along with evidence on the strengths and limitations of AI-generated feedback. The discussion concludes with Oxford’s institution-wide, managed-access model and practical guidance for designing, evaluating, and governing AI pilots.
TOPICS:
- Course-grounded AI assistants
- Assignment-specific AI agents
- AI acc...
AI in Higher Education: Inquiry-Based Tutors, Multi-Model Access, and AI Readiness
This episode examines how higher education is moving from broad AI experimentation toward more intentional systems. We explore Willamette University’s inquiry-oriented Software Engineering Tutor, SUTD’s university-managed gateway to multiple AI models, and a national AI-readiness initiative for public higher-education systems.
The episode also reviews research on generative AI and learning outcomes, including the roles of instructional design and teacher AI literacy. Student-use data highlights growing demand for AI tutoring and workload support—while showing that learners continue to value instructors, peers, and human advising.
The discussion concludes with practical considerations for piloting inquiry-based tutori...
Designing Purposeful AI Uses in Higher Education: Learning, Advising, and AI Literacy
This episode examines how universities are moving from broad AI experimentation toward targeted applications tied to learning objectives, student support, and measurable outcomes. Examples include Georgia Tech’s AI-supported reflection and clinical practice projects, Case Western Reserve’s structured teaching-pilot grants, and new research on AI-supported learning.
The discussion also explores the University of Leicester’s student-services agent, Austin Community College’s AI-supported advising initiative, and evidence that short, practice-based AI-literacy modules can improve student capability. Across these examples, the episode considers how institutions can define the human role, use reliable information, and evaluate results before scaling.
The...
How Universities Are Moving from AI Pilots to Student Support and Governance
This episode examines how universities are moving from broad AI experimentation toward discipline-specific teaching pilots, AI-supported student services, and more deliberate governance. Examples include Cornell’s faculty-led pilots, UT Arlington’s instructional AI tutor, UT San Antonio’s RITA student-support assistant, and Cedarville’s career-preparation tools.
The episode also considers Georgetown’s AI Fellows initiative and the growing gap between institutional adoption, independent evidence, and protections for privacy, transparency, bias, and accountability. It closes with practical considerations for designing pilots, escalation pathways, and student partnerships.
This episode is intended for higher-education leaders, faculty, staff, and institutio...
