Teaching and Learning in the Age of AI: Current Status Analysis and Action Plans

The capabilities of generative AI are advancing at an astonishing pace, moving from general-purpose models toward specialized applications with increasingly sophisticated analytical and reasoning abilities comparable to those of human experts. This transformation is reshaping not only how knowledge is transmitted and acquired, but also redefining the meaning of learning and expertise. Research shows that using AI tools without guidance—or relying on them excessively—may diminish learners’ understanding, critical thinking, and memory. However, when learning tasks are appropriately designed and human–AI collaboration is thoughtfully implemented, AI can deepen learning processes and foster meaningful reflection.

At this turning point, the role of education is shifting: from imparting knowledge to guiding thinking, from teaching skills to cultivating judgment and creativity. To navigate this wave of change, educational reform must focus on three dimensions :

  • AI in Education: Effective use of AI tools in teaching
  • AI Literacy: Understanding how AI works and the risks involved
  • AI Education: Developing the ability to create and reform AI technologies


These three dimensions form the core of education in the AI era and are crucial directions for curriculum design and learning outcomes in universities. In this time of transformation, this section explores how faculty can redefine their expertise and professional identity, how students can learn alongside AI, and how universities can respond—both institutionally and philosophically—to the AI generation. While paying attention to technological development and applications, universities must continue to fulfill their responsibility to cultivate in students the capacity to coexist with emerging technologies and to think and create, thereby nurturing future leaders for the AI era.

(AI Index Steering Committee. The AI Index 2025 Annual Report. Institute for Human-Centered AI, Stanford University, 2025.)

◎ Teaching in the Generative AI Era – Four Recommendations for University Instructors
As generative AI rapidly evolves and becomes widely used, the Center for Teaching and Learning Development (CTLD) and the Digital Learning Center (DLC) have integrated the characteristics of university teaching, discussions from domestic and international education forums, and faculty experiences on campus to offer four recommendations on how to effectively integrate AI into teaching. These guidelines apply to most course designs and can be implemented by instructors without the need for advanced technical expertise.

  • Define Contexts in Which AI Use Is Permitted or Prohibited
    • By setting external conditions—such as allowing or restricting AI use in certain tasks—students can better understand their own learning performance while instructors can evaluate whether students have developed the intended competencies.
    • Examples: AI tools may be used for regular assignments, but grading standards are raised. AI tools are not allowed in in-person final exams to assess students’ understanding of core knowledge.
    • Instructors should carefully determine the sequence of AI-allowed and AI-restricted activities. In the initial phase of learning, employ scenario design to reduce students’ dependency on AI tools. It is important to explain to students the rationale behind such design and the expected learning outcomes to avoid misunderstandings.
  • Guide Students to Use AI Effectively
    • With instructors’ guidance, students can learn the professional skills required to use AI wisely and develop habits for making AI an effective assistant./span>
    • Examples: Demonstrating AI use during class. Assigning scaffolded tasks that gradually build students’ competence with AI tools.
    • Instructors may select AI tools appropriate for their course content and should be mindful of differences in students’ proficiency. Through supporting students in reflective and informed use of AI, instructors can help them develop their human-AI collaboration skills and capabilities .
  • Increase Human Feedback
    • Receiving feedback from humans—not machines—and experts allows students to experience genuine exchange of perspectives and interaction.
    • Examples: Adjusting assignment grading practices to increase personalized feedback from instructors, rather than relying solely on numerical scores.
    • Feedback from instructors or peers should align with the course’s learning goals and reflect personal expertise and lived experience, emphasizing the irreplaceability of human judgment.
  • Use AI Tools to Prepare Course Materials
    • AI can increase efficiency for certain tasks, reducing instructors’ time spent on routine work and allowing more time for meaningful teaching activities.
    • Examples: Using AI to help design exercises or prepare lecture materials, freeing up time to write personalized feedback for students.
    • Instructors should remain mindful of the uncertainty in AI-generated content and perform necessary quality checks. Time saved through AI can then be reinvested into more valuable teaching practices.

For detailed guidelines, please refer to the video recorded by DLC Associate Director Prof. Ling-Chieh Kung.

◎ Practical Experiences: Integrating AI into Teaching
CTLD and DLC have interviewed faculty members from various disciplines. Through these interview reports, instructors can learn how colleagues apply AI tools in their courses, how they guide students in using AI effectively, and how they develop their teaching philosophy in the generative-AI era. More interviews reports will be published over time.

 
◎ Internal Funding Opportunities

AI Assistant Program (Final Round for 2025)

  • Objective: Encourage faculty to independently explore various AI tools and discover possibilities for AI-enhanced teaching.
  • Program Description: Faculty may subscribe to any online AI tools they need. There are no limits on the types or number of tools. Subscriptions must be on a monthly basis. The maximum subsidy is NT$4,000, and it should not overlap with other AI-related funding provided by the center.
  • Application Period: Open from October 17 to November 20.
  • How to Apply: Submit the online application form.After approval, reimbursement instructions and additional notes will be provided by email.

*New funding programs for 2026 will be launched. Faculty who miss this round are welcome to apply next year.

◎ Internal Faculty Community
  • CTLD hosts an online faculty community where higher-education trends and on-campus events are shared regularly. Faculty are encouraged to exchange experiences and insights with colleagues from different fields.

We sincerely invite all instructors interested in exploring the possibilities of innovative teaching to join us and experience the joy of teaching together!

Please search on Facebook for “臺大教師玩教學” (NTU Teachers Play with Teaching) or click the link to request to join.