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Rethinking GenAI Competencies for University Teachers

Professor LIM Cher Ping

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Chair Professor of Learning Technologies and Innovation

Co-Director, Global Institute for Emerging Technologies

The Education University of Hong Kong

16 Sep 2025

Equity Team

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GenAI and University Teaching and Learning: Shift of Paradigm

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Existing AI Competency Frameworks for Teachers

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GenAI Competency Framework for University Teachers

03

What is ongoing?

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CONTENT

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01 GenAI and University Teaching and Learning: Shift of Paradigm

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1.1 The Transformative Impact of GenAI on Higher Education 

    • Redefining Cognitive Process Instructional & Pedagogical Shift
    • Reshapes knowledge construction, critique, and dissemination.
    • Learner-Driven Dynamic
    • Shifts from Educator-directed to student-centered learning.
    • Systemic Transformation of Academic Ecosystems
    • Transforms curriculum design, scholarly writing, peer interactions, and institutional policies and mechanisms.
    • Necessitates redefining curricular outcomes and teaching and learning practices.

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1.2 Key challenges for University Teachers

The Need for a GenAI-Responsive Competency Framework

    • Instructional & Pedagogical Shift
    • Learner-Driven Dynamic
    • Systemic Transformation of Academic Ecosystems

01 GenAI and University Teaching and Learning: Shift of Paradigm

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02 Existing AI Competency Frameworks for Teachers

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2.1 TPACK and AI-TPACK

Koehler, M. J., & Mishra, P. (2005). Teachers learning technology by design. Journal of computing in teacher education, 21(3), 94-102.

Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in human behavior, 138, 107468.

    • Overlook complexities

(e.g., ethical, cognitive, and sociocultural complexities)

    • Insufficient scaffolding for students
    • Tool-centric view

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2.2 DigCompEdu Framework

Redecker, C. (2017). European Framework for the Digital Competence of Educators: DigCompEdu (Y. Punie, Ed.). Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/178382 (print),10.2760/159770    

    • Lacking specificity
    • Static human-AI view

Neglects co-evolution of human agency and autonomous AI systems.

Focuses on general pedagogy, lacks disciplinary/ethical AI integration.

02 Existing AI Competency Frameworks for Teachers

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02 Existing Teacher AI cmpetency Frameworks

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2.3 Digital Age Learning Matrix

    • Pre-GenAI framework
    • Human-centered mindset

Assumes full human control, neglecting AI as co-creator/collaborator in learning.

Lacks focus on ethical/sociotechnical challenges of autonomous, generative AI tools.

Starkey, L. (2011). Evaluating learning in the 21st century: a digital age learning matrix. Technology, pedagogy and education, 20(1), 19-39.

02 Existing AI Competency Frameworks for Teachers

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02 Existing Teacher AI competency Frameworks

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2.4 UNESCO AI Competency Framework for Teachers

Cukurova, M., & Miao, F. (2024). AI competency framework for teachers. UNESCO Publishing. 

    • Abstract & policy-driven nature
    • Limited student-AI dynamics

Neglects fostering critical relationship between students and AI.

Lacks "how" guidance for GenAI classroom implementation.

    • Operational gaps

Prioritizes policy alignment over actionable practices for GenAI-enhanced pedagogy.

02 Existing AI Competency Frameworks for Teachers

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03 GenAI Competency Framework for University Teachers

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3.1 The Driving Ideas​

    • The use of generative artificial intelligence (GenAI) is determined by students rather than prescribed by teachers.
    • Rather than resisting or preventing the use of GenAI, teachers are suggested to actively explore innovative designs, activities, and assessments that push students to use GenAI in effective ways.
    • Aside from teachers’ own GenAI competencies, it may be even more important for teachers to have the competencies to innovate teaching practices that embrace and drive GenAI use.

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GenAI Literacy

Curriculum Design

Teaching & Learning

Assessment

3.2 Horizontal Axis – Four Dimensions & Two Perspectives

    • Teachers’ own literacy/usage
    • Empowering students’ literacy/usage

03 GenAI Competency Framework for University Teachers

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03 GenAI Competency Framework for University Teachers

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Basic automation 

3.3 Vertical Axis - Three Developmental Tiers

Advanced (collaborative partnership and knowledge creation sharing) 

Basic(basic automation-doing & thinking about connections)

Intermediate (Guided application & skill augmentation, thinking about conception and critiquing evaluating)

Guided application 

Creative partnership

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3.4 Overview (1/2)

03 GenAI Competency Framework for University Teachers

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Basic

Intermediate

Advanced

GenAI Literacy  �Teachers’ own literacy 

Demonstrates foundational understanding of safe, ethical, and effective interaction with GenAI systems.

Critically engages with GenAI outputs, identifying potential issues, biases, and opportunities for improvement.

Explores innovative ways of collaborating with GenAI, reflecting on its evolving role as a cognitive partner.

Empowering students’ literacy 

Introduces students to responsible, ethical and basic methods for interacting with GenAI systems. 

Guides students to critically engage in iterative dialogues with GenAI tools. 

Supports students in co-creating knowledge and artefacts through advanced human-AI collaboration. 

Curriculum/Learning Design  �Teachers’ own usage 

Uses GenAI to generate ideas and curate teaching resources, recognizing its potential for curriculum innovation. 

Collaborates with GenAI to refine, adapt, and personalize curricular materials responsively. 

Co-designs interdisciplinary, project-based curricula that integrate student-GenAI partnership models. 

Empowering students’ usage 

Introduces students to GenAI-supported curriculum exploration and learning design. 

Facilitates students’ collaborative construction of learning artefacts using GenAI tools. 

Empowers students to co-design meaningful, GenAI-enhanced, self-directed learning experiences. 

Competency Dimension 

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03 GenAI Competency Framework for University Teachers

3.4 Overview (2/2)

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Basic

Intermediate

Advanced

Teaching and Learning�Teachers’ own literacy 

Uses GenAI to support basic instructional tasks, such as generating examples, explaining concepts, or developing simple interactive materials. 

Applies GenAI for dynamic scaffolding, simulations, or adaptive feedback to personalize student learning pathways. 

Designs and facilitates co-learning environments where GenAI serves as a cognitive partner in inquiry, co-construction, and classroom dialogue. 

Empowering students’ literacy 

Introduces students to using GenAI for basic exploration, such as brainstorming, retrieving information, or generating explanations. 

Guides students to interact critically and collaboratively solve problems with GenAI support. 

Enables students to co-create knowledge through GenAI-supported innovation, reflective dialogue, and creative project development. 

Assessment �Teachers’ own usage 

Uses GenAI to automate simple assessments and provide immediate feedback. 

Adopts GenAI to design adaptive formative assessments responsive to student learning trajectories. 

Co-creates innovative, AI-enhanced assessment models that integrate both human and machine feedback for deeper learning insights. 

Empowering students’ usage 

Introduces students to interactive self-assessment tools powered by GenAI. 

Guides students to interpret and apply GenAI-generated feedback to improve their work. 

Support students in designing AI-enhanced peer and self-assessment systems, promoting reflective and collaborative evaluation processes. 

Competency Dimension 

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04 Flow Chart of Model Design and Development

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Phase I

Collective Case Study on How University Teachers across Various Disciplines facilitate GenAI Integration in Teaching and Learning

Methodology

Relevant literature review

Interview (teachers)

Course design analysis

Questionnaire (students)

Phase II

Development of University Teacher GenAI Competency Model and A Self-assessment Tool

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Phase III

Development and Application of AI-enabled Professional Learning System for University Teacher

Key AI technologies

Data Mining

Machine Learning

Intelligent Recommender Systems

Data Analytics and Learning Analytics Natural Language Processing & Generation

Methodology

Relevant literature review

Delphi technique

Questionnaire (teachers)

Experimental design

Key features

Scalability

Sustainability

Iterative Prototype

User-centered Design

Personalization & Adaptation

Embed the self-assessment tool

Qualitative & Quantitative

Concurrent & Interrelated

Identify effective strategies and practices

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04 What is ongoing?

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    • Conduct Case Studies with university teaches across disciplines
    • Develop a

self-assessment tool for university teachers

    • Build a GenAI-Enabled Professional Development Tool
    • Conduct consultations with UNESCO ICHEI’s partner HEIs from Latin America, Asia-Pacific, West Aisa, and North Africa

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