Learning and
Teaching Hub
“Fostering a culture of teaching excellence and learning
to promote inclusion and academic success.”
The Learning and Teaching Hub is a dedicated Engineering faculty resource for ongoing professional development and communities of practice, instructional consultation and coaching, collaborative learning development, and effective use of learning technology and analytics. Explore the links below to access helpful resources and information.
Spotlight
AI Mentors: Supporting Teaching and Learning at Scale
As enrollments grow and courses become more complex, faculty are increasingly asked to support learners with diverse prior knowledge, pacing needs, confidence levels, and executive function limitations. This seminar introduces AI mentors.
Rethinking Engineering Education with AI and Active Learning
What happens when AI and active learning converge in the engineering classroom? At ASU, this intersection presents an exciting opportunity: to design experiences that equip students to thrive in an AI-enabled future.
AI Learning Design Suite: Tools to Support Course Design and Teaching
How can AI make course design easier without compromising quality and maintaining academic rigor? ASU’s Learning Design Suite offers practical tools — from syllabus helpers to learning objective generators — grounded in learning science and aligned with instructional best practices. The Learning and Teaching Hub is proud to have contributed to the development of these tools.
News and Events
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“Building Better Courses Together”: Insights from Lindsey Lewandowski Robinson and Amy Janiczek
Lindsey Lewandowski Robinson, Senior Learning Experience Designer at the Learning and Teaching Hub, and Amy Janiczek, Manager, Design and Development at Western Governors University (former Learning and Teaching Hub team member), recently co-authored Building Better Courses Together. In the article,…
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How Do We Teach Adaptability? Insights from Engineering Practice and Research
Engineering educators widely agree that adaptability is essential for preparing students to thrive in a rapidly changing profession, and yet we still lack clear ways to define, teach, and measure it. This seminar presents findings from the NSF CAREER project,…
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Data-Driven EdTech Decisions Matter
Data-Driven EdTech Decisions Matter May 11th, 2026 By Chris Puddy, Learning Technologist “Are we choosing edtech tools based on evidence — or convenience?” I recently explored a resource from The Learning Accelerator on using data to drive more equitable edtech…
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From Hardwood to Higher Ed: Moving Beyond Assumptions
Change is inevitable. In engineering, we expect iteration, innovation, and responsiveness to new data. Yet in teaching, change can feel personal.
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Innovation through Engaged, Multi-Interest Partnership
This seminar examines how frontier technologies, such as artificial intelligence, can be ethically and equitably adopted through intentional collaboration between educators and researchers, and across systems, ensuring that innovation expands rather than narrows opportunity. It also explores how cross-functional and…