Faculty, Skills, and the Future of Higher Education

Overview

This course helps higher education faculty, instructors, and academic leaders make sense of the forces reshaping colleges and universities, and what they mean for everyday teaching practice. You will examine key shifts such as technological acceleration, especially advances in artificial intelligence, changing student expectations, and evolving labor market demands that are influencing perceptions of degree value and student outcomes.

Throughout, you will distinguish between temporary environmental changes and the enduring mission and purposes of higher education. Building on this foundation, you will explore how knowledge, skills, and judgment interact in a world where AI is increasingly capable of performing routine cognitive tasks.

The course examines the continued role of faculty expertise in guiding learning, maintaining academic rigor, and supporting meaning-making—not just skill acquisition. You will analyze the gaps between academic learning and workforce expectations, and learn how skills can serve as connectors between disciplines and career pathways.

Finally, you will identify concrete opportunities in your own courses to make learning more visible and transferable, incorporate more active and applied learning, and experiment with AI-supported tools that extend instructional presence while preserving faculty autonomy. You will leave with a practical, low-risk action plan for integrating new approaches into your teaching context and contributing thoughtfully to institutional responses to change.

Syllabus

• The World Has Changed, The Mission Has Not
Higher education continues to serve a consistent mission, even as the environment around it evolves. This module explores the forces reshaping student expectations, workforce dynamics, and institutional pressures, and invites reflection on how these changes are experienced within your own teaching context. You will connect external trends to the enduring mission of higher education and consider implications for your courses and institution.
• Expertise in an Age of Intelligent Tools
As new tools expand access to information and automate aspects of work, the role of human expertise is being redefined rather than diminished. This module examines how judgment, interpretation, and disciplinary knowledge remain central to meaningful learning in an increasingly AI-supported environment. You will consider how artificial intelligence reshapes knowledge, skills, and judgment while reaffirming the importance of faculty expertise.
• From Knowledge to Application: Making Learning Visible
Students often develop deep knowledge within their disciplines, yet struggle to connect that learning to evolving career pathways. This module explores how skills can serve as bridges between academic work and real-world application, making learning more visible and transferable. You will analyze how curriculum design, pacing, and assessment practices can surface skills and prepare students for changing workforce demands.
• Extending Teaching Through Interactive Learning
Active engagement is central to effective learning, but can be difficult to sustain at scale. This module considers how interactive approaches, including AI-supported tools, can extend faculty presence and create more opportunities for practice, feedback, and application. You will explore practical strategies to integrate interactive learning into your courses while maintaining quality and manageability.
• Faculty Leadership in a Changing Landscape
Higher education is navigating increasing expectations from students, employers, and society more broadly. This module reflects on the opportunities and challenges this creates, and considers how faculty can play a leading role in shaping how institutions respond while preserving academic values. You will examine pressures on higher education, weigh risks and opportunities associated with evolving expectations, and define concrete steps for leading change in your own teaching practice.

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Taught by

Geoffrey Koch

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Subjects

Artificial Intelligence