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Assessment Redesign: Rethinking What and How We Assess in an GenAI-enabled World

Event Details

Date : 22 Sep (Tue), 29 Sep (Tue) 2026 & more

Time : Varies

Venue : Learning Lab (RRS321, 3/F, Run Run Shaw Building, Main Campus, HKU)

Abstract

Generative Artificial Intelligence (GenAI) is reshaping the landscape of higher education, challenging long-held assumptions about how student learning is demonstrated and assessed. As GenAI tools become increasingly capable of producing sophisticated written, visual, and multimodal outputs, reliance on detection technologies may be insufficient and unsustainable. Emerging discussions have increasingly focused on assessment redesign, encouraging educators to reconsider what they assess, how to make learning processes visible, and how to foster higher-order thinking, authentic application, critical judgement, and responsible AI use through assessment.

Drawing on contemporary assessment frameworks and faculty-led examples of assessment redesign, this series aims to develop educators’ knowledge, skills, and confidence in assessment redesign for a GenAI-enabled world. Participants will critically review their existing assessment tasks and explore practical strategies for designing assessments that make learning visible, support responsible AI use, and maintain academic integrity.

The series includes an interactive workshop introducing frameworks and principles for assessment redesign, a consultation session offering advice and feedback on participants’ assessment plans, and faculty sharing sessions showcasing assessment redesign journeys. Participants will have opportunities to reflect on their own assessment practices and learn from colleagues’ experiences of redesign and implementation.

Learning Outcomes

By the end of this series, participants will be able to:

  • Analyse the implications of GenAI capabilities for assessment design and academic integrity;
  • Reflect on their existing assessment tasks to identify opportunities for meaningful redesign; and
  • Apply concepts and strategies to redesign assessments that support transparent AI use and visible student learning.

Date : 22 Sep 2026 (Tue)

Time : 1:00pm – 3:00pm

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Speaker : Dr. Jessica To, Lecturer, TALIC, HKU

Abstract

This hands-on workshop supports participants in making informed and defensible decisions about assessment design in a GenAI-enabled world through three theoretical lenses: Technological Pedagogical Content Knowledge (TPACK) (Mishar & Koehler, 2006), Human-Centric Artificial Intelligence Pedagogy (HCAP) (Chiu, 2026), and the updated Artificial Intelligence Assessment Scale (AIAS) (Perkins et al., 2025). Participants will first critically review the alignment between their intended learning outcomes and existing assessment tasks to evaluate the sustainability of these assessments in the age of GenAI. Through guided activities and discussion, they will identify areas for meaningful design and apply practical strategies to create assessments that support transparent AI use and make student learning visible.

About the Speaker

Dr. Jessica To is a Lecturer at TALIC, The University of Hong Kong, and also the founder of the HKU GenAI Community of Practice. Her work focuses on helping educators design meaningful learning, assessment, and feedback experiences in a rapidly evolving AI landscape. She has led educational development and research projects across Hong Kong and Singapore, including a current Teaching Development Grant project exploring the role of GenAI in student-teacher feedback co-creation.

Her expertise lies in higher education pedagogy, assessment for learning, and the pedagogical use of GenAI. Combining scholarly research with practical experience in supporting faculty development, she works closely with educators to rethink assessment and feedback practices for the future of learning. Her research has been published in leading journals such as Assessment & Evaluation in Higher Education, Higher Education Research & Development, and Teaching & Teacher Education.

References

  • Chiu, T. K. (2026). Human-Centric Artificial Intelligence Pedagogy (HCAP) framework developed from TPACK through integration of artificial intelligence literacy and competency. Interactive Learning Environments, 1-16. [Link]
  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. [Link]
  • Perkins, M., Roe, J., & Furze, L. (2025). Reimagining the Artificial Intelligence Assessment Scale (AIAS): A refined framework for educational assessment. Journal of University Teaching and Learning Practice, 22(7), 1-26. [Link]

Date : 29 Sep 2026 (Tue)

Time : 1:00pm – 2:00pm

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Facilitators :

  • Dr. Jessica To, Lecturer, TALIC, HKU
  • Mr. Donn Gonda, Lecturer, TALIC, HKU

Abstract

Redesigning assessments in the age of GenAI often raises discipline-specific questions and practical challenges. This consultation session provides a space for participants to discuss their challenges, explore redesign ideas, and receive feedback from facilitators and peers. Participants are encouraged to bring their assessment tasks, course outlines, marking rubrics, or preliminary redesign plans for discussion. Through conversations and peer exchange, they will gain constructive feedback, practical suggestions, and diverse perspectives on addressing assessment challenges in their own contexts.

About the Facilitators

Dr. Jessica To is a Lecturer at TALIC, The University of Hong Kong, and also the founder of the HKU GenAI Community of Practice. Her work focuses on helping educators design meaningful learning, assessment, and feedback experiences in a rapidly evolving AI landscape. She has led educational development and research projects across Hong Kong and Singapore, including a current Teaching Development Grant project exploring the role of GenAI in student-teacher feedback co-creation.

Her expertise lies in higher education pedagogy, assessment for learning, and the pedagogical use of GenAI. Combining scholarly research with practical experience in supporting faculty development, she works closely with educators to rethink assessment and feedback practices for the future of learning. Her research has been published in leading journals such as Assessment & Evaluation in Higher Education, Higher Education Research & Development, and Teaching & Teacher Education.

Mr. Donn Gonda is a Lecturer at TALIC, The University of Hong Kong. He is an educator and a learning designer with over a decade of experience from higher education to corporate training. He specialises in designing innovative learning experiences, leveraging emerging technologies, and applying research to evaluate and enhance professional development programs.

Passionate about integrating technology into teaching to improve learner engagement, he has facilitated numerous workshops and seminars on learning design, e-learning strategies, and the future of professional development. His work centres on reimagining how learning can be both purposeful and enjoyable — curating cutting-edge tools and approaches that make education not only practical but inspiring.

Date : 23 Sep 2026 (Wed)

Time : 1:00pm – 2:00pm

Venue : Learning Lab (RRS 321 Run Run Shaw Building, Main Campus, HKU)

Speakers :

  • Dr. Ken Lau, Senior Lecturer and Associate Director, CAES, HKU
  • Dr. Vivian Kwan, Lecturer, CAES, HKU
  • Dr. Alice Yau, Lecturer, CAES, HKU

Facilitator : Dr. Carson Hung, Lecturer / E-learning Technologist, TALIC, HKU

Abstract

Details will be announced soon.

Date : 5 Nov 2026 (Thu)

Time : 1:00pm – 2:00pm

Online : Zoom

Speaker : Prof. Patrick Adler, Assistant Professor, Department of Geography, Faculty of Social Sciences, HKU

Abstract

This presentation introduces a pro-AI framework for university writing assignments that rewards responsible AI use and the ability to maintain fluency across contexts. Entitled consistency-weighted writing, it promotes the use of AI as a copilot in traditional writing assignments and rewards students for being able to express their ideas in spontaneous written and oral contexts. The approach was developed for large lectures in HKU’s Common Core Curriculum and the Faculty of Social Sciences, which have traditionally relied on take-home writing assessments and have struggled to ensure that these remain authored by students as LLMs have proliferated. In this approach, students complete similar communication exercises across multiple contexts: written take-home, written in class, recorded video, and in-class debate. Students who demonstrate consistency in quality across contexts are graded more on their higher scoring assignments, while those who do not are graded more on their lowest scoring ones. The approach is designed to encourage AI-assisted writing as practice for live communication, allowing students to benefit from it as a tutor without being able to avoid independent communication altogether.

The session will begin with a few remarks from the perspective of a teacher who uses AI in their own work and has struggled to promote responsible AI use. It continues with examples from HKU classes and closes with advice for how to adopt this approach in other academic settings.

About the Speakers

Prof. Patrick Adler is an Assistant Professor in the Department of Geography at the University of Hong Kong. His research focuses on how regions adapt to macroeconomic and technological change, with a particular emphasis on creative city economies. His work has been published in leading journals in economic and urban geography and cited in The New York Times, The Hollywood Reporter, and Bloomberg. He teaches courses on globalization, creative cities, future urban development, and regional economic change. His scholarly project, Disembedded, consists of a series of “experiments” exploring the integration of new technologies into academic research and scholarship. More information is available at disembedded.com.
For information, please contact:

Ms. Miffy LEUNG

Teaching and Learning Innovation Centre

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