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Student-Staff Partnership x AI Integration in Higher Education Seminar Series

Event Details

Stay tuned for more GenAI and EdTech Toolkits workshops coming in Spring 2026!

Date : 24 Sep (Thu), 9 Oct (Fri), 26 Oct (Mon), 10 Nov (Tue), 25 Nov (Wed) & 14 Dec (Mon) 2026

Time : 1:00pm – 2:00pm

Online : Zoom

Abstract

As Artificial Intelligence (AI) continues to reshape the landscape of higher education, meaningful collaboration between students and staff has become more essential than ever. The SSPxAI Seminar Series aims to explore the synergies between student-staff partnership and AI integration in teaching and learning. Through this seminar series, speakers (including staff and their student partners) will share their experiences of experimentation and explore how collaborative approaches can enrich teaching, learning, and the broader educational experience within an AI-enhanced environment. They will also reflect on the essential knowledge, tools, and collaborative mindsets needed to navigate this evolving landscape.

The series welcomes anyone interested in exploring innovative pedagogical approaches that harness the potential of AI while fostering meaningful human collaboration in the learning process. Across the sessions, participants will engage with diverse perspectives on integrating AI tools into curriculum design, assessment practices, outside-classroom activities, and more. These discussions will be explored through a partnership lens that values the voices and contributions of both students, staff in shaping AI-enhanced learning experiences.

Following each presentation and Q&A session, a virtual Co-Creation Cafe hosted in breakout rooms will provide an informal space for participants to seek advice, exchange ideas, and continue the conversation. Partnership Advocates of the Community of Practice for Student Partnership (CoP-SP) will be available for consultation and support.

1:00pm - 1:05pm	Introduction by facilitator
1:05pm -1:30pm	Presentation
1:30pm - 1:40pm	Q&A
1:40pm - 1:55pm	Virtual Co-Creation Café
1:55pm - 2:00pm	Wrap-up, evaluation and next session announcement

* This is an online interactive session where speakers will stay for 15 min in Zoom breakout rooms to meet individual participants for in-depth conversation or potential collaboration. CoP-SP members and Partnership Advocates will host other breakout rooms for general consultation, e.g., university policies and resources for SaP or use of AI tools in teaching and learning. Participants will be encouraged to continue the dialogue afterwards. Turn on screen reader support

[24 Sep 2026] Seminar 1: Ever Tried. Ever Failed. Fail Better: Navigating Uncertainty through the Trio Model in Students as Partners

Date : 24 Sep 2026 (Thu)

Time : 1:00pm – 2:00pm

Online : Zoom

Speakers :

Ms. Chin Yu Tso, Year 4 UG, Faculty of Social Sciences, HKU
Dr. Peter Fat Man Lau, Lecturer, TALIC, HKU

Abstract

The incorporation of AI into higher education has muddied assumptions about knowledge, expertise, and student–educator relationships. Its most underdiscussed consequence is affective: the vulnerability, self-doubt, and fear of failure that emerge when clear answers no longer exist. This session explores what becomes possible when uncertainty is approached as something students and staff navigate together. We examine how cultures of care and productive failure can reframe uncertainty, inspiring the development of our proposed Trio Model, which positions students, educators, and AI as partners in shared learning. Inspired by Cook-Sather’s (2025) notion of generative unknowingness, Brantmeier’s (2013) pedagogy of vulnerability, and Noddings’ (1988) ethic of caring, we reimagine uncertainty as possibility.

Intended Learning Outcomes

Identify the principles, values, and pedagogical intervention underlying the Trio Model.
Explore new ways of conceptualising and navigating uncertainty and failure in the age of AI.

About the Speakers

Ms. Tso is a year 4 undergraduate student majoring in Interdisciplinary Studies and Comparative Literature at HKU. She’s passionate about empowering students, fostering student engagement, and driving positive change in higher education through student–staff partnerships. She is also the Student Partner and Core Project Member for Exploring GenAI Use in Teaching and Learning Enhancement through a Pedagogical Partnership Approach and Collaborative Showcase, UGC TDLEG-IICA (2025-2028 Triennium).

Dr. Peter Lau is a Lecturer at the Teaching and Learning Innovation Centre. He has a decade of teaching experience. As an advocate for Students as Partners (SaP), Peter works with colleagues and students in T&L projects on various topics, such as service-learning, team-based learning, academic integrity, creative drama, reflective portfolio, etc. Peter is the project leader of Exploring GenAI Use in Teaching and Learning Enhancement through a Pedagogical Partnership Approach and Collaborative Showcase, UGC TDLEG-IICA (2025-2028 Triennium). And he is also the program leader of University Climate Action Program, UGC TDLEG-IICA (2025-2028 Triennium)

[9 Oct 2026] Seminar 2: Productive Friction in Student-AI Collaboration: AI-Task Fit Design in a Business AI Course

Date : 9 Oct 2026 (Fri)

Time : 1:00pm – 2:00pm

Online : Zoom

Speaker :

Dr. Dimple R. Thadani, Senior Lecturer, Department of Management, Marketing and Information Systems, HKBU

Student Partner : Ms. Naina Manoj Ramchandani, Year 2, Bachelor of Arts, Science and Technology in Individualised Major, HKBU

Abstract

This presentation reports on the implementation of an AI Affordance-Cognition Fit Framework within a first-year Business AI core course. Using authentic coursework data and a student partnership approach, we examine how aligning AI affordances with task cognitive demands influences student learning and assessment quality. Guided by task-technology fit principles, students engaged with AI as a collaborative thinking partner rather than a content replacement tool. Findings suggest that deliberately introducing “productive friction” through critique, evaluation, and refinement of AI outputs promotes deeper engagement and stronger coursework outcomes. The presentation offers practical insights for designing AI-enhanced curricula that balance efficiency, critical thinking, and meaningful student-AI collaboration.

Intended Learning Outcomes

Describe how the alignment of AI affordances and task cognitive demands influence student learning and assignment quality.
Evaluate assessment tasks using the AI-Task Fit framework.

About the Speaker

Dr. Dimple R. Thadani (PhD, SFHEA, PGCHE) is a Senior Lecturer at Hong Kong Baptist University, specialising in AI-related business subjects, including AI for Business and Business Intelligence. She holds a PhD in Information Systems, an Advance HE Senior Fellowship (SFHEA), and a Postgraduate Certificate in Higher Education (PGCHE). Dedicated to integrating technology, education, and business to prepare students for the digital era, she received the Higher Education Outstanding Teaching Achievement Award from the Ningbo Education Bureau (Municipal Level) in April 2025. Her research interests include AI tools and pedagogy, agentic AI for education, AI in business education, digital transformation, platform strategies, and the development of smart cities.

Student Partner

Ms. Naina Manoj Ramchandani Year 2, Bachelor of Arts, Science and Technology in Individualised Major, HKBU

[26 Oct 2026] Seminar 3: Realigning Assessment and Authentic Learning to Neutralize AI Misuses in Learning

Date : 26 Oct 2026 (Mon)

Time : 1:00pm – 2:00pm

Online : Zoom

Speaker :

Prof. Lukas Liu, Assistant Professor, Faculty of Education, HKU

Student Partner(s): TBC

Abstract

In the wake of generative AI, academic misuse often stems from a fundamental misalignment where instructors design tasks for learning, while students deploy AI to survive high-stakes assessments. In this talk, I will discuss this issue from the perspective of contextual differences in human-AI interaction and explore a pedagogical shift within a reading-intensive MEDD8935 Theories of Learning in STEM Education course that addresses this disconnect. By reframing the primary objective from textbook memorization to articulating a personal learning theory, the stakes of AI misuse are fundamentally altered. This talk will present an instructional design model course requirements feed directly into live, experience-driven classroom discourse, ensuring that even AI-assisted preparation can be grounded in concrete human experience during class.

Intended Learning Outcomes

Analyze how the structural misalignment between pedagogical goals and high-stakes assessment drives student AI misuse.
Design collaborative, experience-driven assessment sequences that prioritize authentic knowledge construction over rote retention, thereby reducing the incentive for AI misuse.

About the Speaker

Prof. Lukas Liu is an Assistant Professor of Learning Design and Implementation Sciences at the Faculty of Education, the University of Hong Kong. He received his PhD degree in instructional systems and learning technologies from Florida State University. His current work aims to promote the development and learning transfer of computational thinking among K-12 students and teachers. He focuses on designing and developing active game-based learning experiences to facilitate learners’ knowledge acquisition and transferable skill development through problem-solving. Moreover, his research interests also include using quantitative analytics methods to understand learners’ behaviour, competence, discourse, and interactions.

[10 Nov 2026] Seminar 4: Amplifying Student Voices: How AI and Student-Staff Partnership Transform Student Learning in ESG Podcast Production at HKU

Date : 10 Nov 2026 (Tue)

Time : 1:00pm – 2:00pm

Online : Zoom

Speakers :

Program leaders

Prof. Janet Chan, School of Biological Sciences, HKU
Mr. Vincent Leung, MSc in Environmental Management Graduate (2024), HKU

Students

Ms. Anvesha Bajpai, Year 4 UG, Faculty of Science, HKU
Ms. Gungun Jain, Year 2 UG, HKU Business School
Mr. Sam Bekemans, Year 2 TPg, MSc in Environmental Management, HKU

Abstract

ESG Podcast: From Classroom to Boardroom is a student-led ESG podcast supported by the HKU Climate Ambassador Program and funded by a Teaching Development Grant. Student partners from diverse faculties (Science, Arts, Engineering, Business, Medicine, and Social Science) take the lead as hosts, content researchers, scriptwriters, editors, and social media strategists while program leaders and coordinators provide academic oversight and industry connections.

AI tools are integrated across the production workflow—from AI-powered transcription and content summarisation to automated social media caption generation and distribution. This enhances efficiency while allowing students to focus on developing critical thinking, interviewing, and communicating professional knowledge to the general public. The podcast has produced seven episodes across ESG topics, including food waste (Part 1 & 2), ESG education in universities, ESG reporting and sustainable finance, green risk (Part 1 & 2), biodiversity finance, and sustainable governance, featuring academic and industry leaders. We will share practical insights, challenges, and evidence of student development from this ongoing project.

If you are interested in following our journey, please follow us on:
Instagram : https://www.instagram.com/hku_esgpodcast/
LinkedIn : https://www.linkedin.com/company/esg-podcastt

About the Speakers

Program Leaders

Prof. Janet Chan is a Senior Lecturer (Associate Professor of Teaching) in the School of Biological Sciences, Faculty of Science, at The University of Hong Kong, where she serves as the Program Coordinator and Chief Examiner for the Master of Science in Environmental Management. As the Program Director and Co-founder of the HKU ESG Podcast, she leads the project under a “Students-as-Partners” framework—delivering foundational ESG briefings, mentoring student teams, and leveraging her extensive network to connect students with leading academic and industry experts. In addition to teaching courses in environmental management, she was featured as a guest speaker in Episodes 2 and 6, addressing urban food waste solutions and environmental education in Hong Kong, with a strong commitment to empowering students as proactive leaders in climate action and corporate ESG transformation.

Mr. Vincent Leung is a graduate of the HKU MSc in Environmental Management (2024) and an Assistant Manager in Financial Services at Sia and. As a Co-founder of the HKU ESG Podcast, he plays a key role in guiding and mentoring student researchers, scriptwriters, and hosts across various production phases. Bringing deep expertise in sustainable finance and corporate ESG strategies, Vincent served as the professional co-host for Episodes 1, 2, 3.2, and 5—leading discussions on circular economy solutions, food industry decarbonization, sustainable banking, and biodiversity finance. His work bridges professional financial advisory with student mentorship, translating complex corporate reporting and sustainability frameworks into engaging public media.

Student Partners

Ms. Anvesha Bajpai is a final-year BSc Environmental Science student at the University of Hong Kong. As a Researcher and Host for the HKU ESG Podcast, she led topic research, guest recruitment, and episode hosting (Episode 3.1: The Fine Print of Green Risk – What Banks Really Ask Before They Lend). She has a strong interest in integrating sustainability within supply chain management, reflected in her work analysing ESG data and lifecycle impacts during her internship at Parallel 51. Beyond academics, she is committed to advancing sustainability through civic and volunteer engagement—contributing to Hong Kong’s public consultation on the First Five-Year Plan and supporting initiatives at Sprout Heroes and Redress.

Mr. Sam Bekemans is an environmental journalist and student in the HKU MSc in Environmental Management, where his work focuses on the nexus between Chinese policy and climate change adaptation and mitigation. He teaches on Sustainable Development Goals in the Transdisciplinary Undergraduate Programmes at HKBU and has taught climate journalism and core skills at the HKU Journalism and Media Studies Centre. As a host for the HKU ESG Podcast, Sam led Episode 4, “Sustainability Governance: Boards, Data, and the People Who Actually Move Things.” Leveraging his deep understanding of sustainability governance and strong hosting skills, he seamlessly bridged insights between industry executive and HKU Business School scholar to facilitate a compelling, high-impact discussion.

[25 Nov 2026] Seminar 5: From Co-Learners to Co-Creators: A Next-Generation GenAI-Powered, Flashcard-Driven Language Tutoring Platform in Action

Date : 25 Nov 2026 (Wed)

Time : 1:00pm – 2:00pm

Online : Zoom

Speaker :

Dr. Chun Kit Sam Hau, Lecturer, Department of Chemistry, CUHK

Abstract

Chemistry is far more than words and symbols in textbooks; it is deeply embedded in everyday life through the substances and reactions that shape our world. Yet many students perceive chemistry as intimidating and inaccessible. This challenge is particularly acute for learners navigating language barriers, such as those transitioning from non-English medium backgrounds into English medium academic environments. Adapting to new disciplinary knowledge and unfamiliar linguistic conventions can be time-consuming, frustrating, and demotivating, eroding confidence and engagement.

To address these challenges, this project proposes the development of gamified, flashcard-based e-learning materials powered by a Generative AI (GenAI) tutoring system. Grounded in a student partnership model, learners are positioned not merely as end users but as genuine co-creators throughout the project lifecycle. Their learning experiences and feedback shape the platform’s design, ensuring it is pedagogically sound and responsive to the learner community.

The platform will diagnose individual strengths and areas for development and provide targeted language scaffolding. By integrating adaptive practice with game-like elements, the tool aims to foster engagement, support diverse linguistic backgrounds, and promote self-regulated learning to improve conceptual understanding and outcomes in introductory chemistry and related science courses.

Intended Learning Outcomes

Describe how GenAI powered, gamified flashcard tools can enhance student engagement and support learning in introductory courses
Identify practical strategies for embedding a student partnership model into the design and development of AI enhanced e-learning resources within their own teaching and institutional contexts.

About the Speaker

Dr. Sam Hau holds a BSc with First Class Honours in Chemistry from Hong Kong Baptist University and a PhD in Organic Synthesis from CUHK. Following postdoctoral work in X-ray Crystallography, he joined CUHK as a lecturer in 2019, committed to developing innovative teaching and exploring AI integration in chemistry education.

[14 Dec 2026] Seminar 6: “Embracing AI?” Student Perceptions, Practices, and Anxiety in a Hong Kong University

Date : 14 Dec 2026 (Mon)

Time : 1:00pm – 2:00pm

Online : Zoom

Speaker :

Prof. Lillian Luk, Assistant Professor, TALIC, HKU

Student Partner:

Ms. Ye Chen, TALIC, HKU

Abstract

The idea for this study was sparked by a moment in my own teaching practice, when my students shared with me how their peers had become obsessed with running their written work through multiple AI detectors. Their stories were not casual anecdotes; they were expressions of genuine worry, describing classmates who repeatedly checked and re‑checked their assignments out of fear of being falsely accused of using AI. Such conversations prompted me to partner with my student to investigate more deeply how these anxieties shape students’ learning experiences in the AI era.

Generative AI (GenAI) is rapidly becoming embedded in university learning and campus life. However, institutional encouragement for students to “embrace AI” has outpaced the development of clear and consistent policies governing its use (McDonald et al., 2025). This ambiguity, where GenAI is promoted as a tool for productivity while certain uses may constitute academic misconduct, creates uncertainty that can heighten students’ anxiety about using AI. This study investigates how undergraduate students navigate AI-mediated learning environments, focusing on their experiences of AI-related anxiety.

Using survey items informed by Wang and Wang’s (2024) four-dimensional framework of AI anxiety, the study adopted a sequential mixed-methods design. Exploratory factor analysis (EFA) was conducted using survey data from 132 students, followed by confirmatory factor analysis (CFA) from an independent sample of 180 students. Follow-up semi-structured interviews were conducted to provide a deeper understanding of students’ experiences.

The EFA identified four factors: AI learning, AI detection, AI-related threats, and the impact of AI on learning. These factors explained 67.0% of the total variance. The CFA supported an acceptable fit for this four-factor model. Interview findings further showed that students’ AI-related anxiety stemmed not only from the technology itself, but also from uncertainty about institutional criteria and policies for AI use, as well as perceived variations in teachers’ attitudes toward AI.

Intended Learning Outcomes

By the end of this seminar, colleagues will be able to consider how students navigate the pedagogical, ethical, and emotional uncertainties surrounding GenAI when designing the curriculum, and apply insights from this study to inform clearer institutional policies and more responsive forms of student support.

About the Speakers

Dr. Lillian Luk was an assistant professor in the Teaching and Learning Innovation Centre in the University of Hong Kong and is currently an Honorary Research Fellow in the Centre for Engineering Education at University College London.

Miss Chen Ye is a second-year PhD student in the Faculty of Education at the University of Hong Kong. Her research interests primarily include postgraduate education and graduate employment.

Acknowledgement

TDLEG Trio Partnership Project
(2025 – 2028)

This seminar series is supported by an Inter-Institutional Collaborative Project in Teaching Development and Language Enhancement Grant (2025 – 2028 Triennium), Exploring GenAI use in teaching and learning enhancement through a pedagogical partnership approach and collaborative showcase (Trio Partnership Project), funded by the University Grants Committee (UGC).