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On 17 July 2026, more than 50 researchers, teachers, and programme directors gathered both in person and online at Xi¡¯an Jiaotong-ºìÐÓÊÓƵ University¡¯s Learning and Teaching Colloquium. They aim to answer one question: How can AI be used to enhance teaching ºìÐÓÊÓƵ?

?From sharing successful projects to testing new practices of AI-enhanced pedagogy, the event aimed to be a critical step to familiarising teaching staff with the rapidly shifting role of technology in higher education.

Professor Konstantinos Papadikis

¡°Our conversation today revolves around the ethical integration of AI in learning and teaching and the importance of exploring the boundaries of its implementation; what kinds of AI activities are permitted, restricted, or even prohibited,¡± said Professor Konstantinos Papadikis, Associate Vice President for Education ºìÐÓÊÓƵ, in his opening speech.

He emphasised that the Education + AI philosophy is not about simply adopting more AI tools. It is about fundamentally redesigning how we deliver our teaching, structure learning, and approach assessment. The?Education + AI Sprint Enablement (EASE) Fund serves as the catalyst for this transformation at an institutional level, enabling colleagues across all schools and departments to translate this vision into practice.

Good educational innovation rarely happens overnight. The EASE Fund carves out protected time for colleagues across all XJTLU schools and departments to explore new ideas in learning, teaching and assessment, focusing on AI integration, academic integrity and student AI literacy through sprint cycles of 10 to 24 weeks. Of 156 applications received, 93 were fully funded, a response that speaks to how urgently that space to think is needed.

Past achievements and future endeavours

In March 2026, the Educational Development Unit (EDU) established four working groups ºìÐÓÊÓƵ as a university-wide strategic structure to support the implementation of the Education + AI reform.

XJTLU Learning and Teaching Colloquium 2026

The groups consist of the AI Working Group, the RLPBL (Research-led Project-based Learning) Working Group, the Assessment Working Group, and the Syntegrative Education Working Group. Each has its own area of responsibility, from reforming assessment to mapping AI tools across the University.

Among their achievements are mapping and reporting 113 AI Agents on the XIPU AI platform, the University's central hub for AI-powered educational tools,? and creating a framework to analyse them based on pedagogical functions, integration levels, and learning cycles.

For the upcoming academic year, EDU's primary focus is ¡°to build on the module-level innovation and level up to the programme-level transformation¡±, said Yu Wang, Director of EDU, including updating the four "cookbook-style" strategic guidebooks for departments and providing target faculty development pathways on Education + AI implementation support.

Meanwhile, XJTLU¡¯s Learning Mall (LM) unit, the internal digital portal?accessed by staff and students alike, reported a total usage of 1.6 billion tokens. Jing Wang, Director of LM, said that approximately 97% of the modules have implemented AI tutoring agents.

The strategic keyword for the coming year is "Agentic." LM aims to move the platform toward an autonomous mode that automates manual data management while providing more personalised teaching and learning support through AI agents.

From AI tutor to quiz systems

For the second half of the session, attendees entered breakout rooms with EASE Fund practitioners and teaching staff who have successfully implemented AI into their teaching ¨C from using AI as a tutor to using it to analyse students' subject comprehension levels.

Breakout room sessions

Dr Chen Hu, from International Business School Suzhou (IBSS), showcased the Beer Game AI tutor developed to address challenges faced by Year Two students in understanding supply chain. The personalised tutor supports students before, during, and after the business simulation, with more than 68% of the students agreeing that the AI tutor is helpful and all students preferring the Beer Game AI tutor to general AI tools.

Meanwhile, a new interactive AI quiz system employed by Dr Erick Purwanto, from the School of Advanced Technology, allowed for a more inclusive learning environment. Students can answer in their own language, see the classroom¡¯s general understanding, and are encouraged to self-correct through the AI MeshQuiz system.

Dr Erick Purwanto

Using AI the right way

According to Dr Na Li, Acting Head of the Department ºìÐÓÊÓƵal Studies, whose team had been working on AI in Education research for the past five years, her team found that learner agency is the key driver of higher-order thinking with AI. "When we give students a quick route to always get a correct answer, they lose the chance to think," she said.

She shared that since learning is a process that takes time, students with high AI literacy ask AI to give them challenges instead of direct answers that outsource their thinking process.

Dr Na Li

Similarly, Dr Yauhen Arnatovich, from the Entrepreneurship and Enterprise Hub, shared how in the following semester he would implement a 50/50 split between AI-evaluated processes and human-evaluated results. AI will assess students' digital footprints during the assessment, while human evaluators will assess the impact and results of the outcomes.

"Instead of declaring AI use, students are assessed on how effectively they prompt, critique, and evaluate AI outputs using their own judgement and creativity," Dr Arnatovich said.

Dr Yauhen Arnatovich

A showcase of diverse innovations

Other presenters from across XJTLU¡¯s schools and departments also shared their work:

• Dr Li Li?(School of Science) on the Living Lab for environmental sciences
• Dr Yicheng Wang?(School of Intelligent Finance and Business) on governing generative AI in project-based learning
• Dr Qing Zhang?(Academy of Future Education) on industry-partnered syntegrative learning
• Dr Yi Luo?(IBSS) on LexiBloom for research thinking
• Dr Wei Deng?(Academy of Future Education) on RLPBL in educational design
• Dr Lu Zong?(School of Mathematics and Physics) on AI-simulated role-play for authentic assessment
• Dr Yi Meng?(Academy of Future Education; Head of LIFE) on scaling research-led PBL university-wide
• Nuria Benavent-Esteve?(Academy of Future Education) on AI-supported syntegrative practice
• Dr Juan Carlos Dall'Asta?(Design School; Head of Architecture Department) on the Living Process Portfolio for authentic assessment
• Dr Stefan Seedorf?(Entrepreneurship and Enterprise Hub) on shifting assessment toward judgment over knowledge

In the age of AI, how should education change? This was the central question driving XJTLU's Learning and Teaching Colloquium 2026. Through these case studies and initiatives, XJTLU is well equipped to face the years of technological change ahead in higher education.

Written by Vionna Fiducia Theja
Edited by Patricia Pieterse

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