人工智能教育研究所

FD99







严栗翔

职称: 助理教授

地址: 北京市海淀区清华大学黄松益楼四层

邮箱: lixiangyan@mail.tsinghua.edu.cn

电话: 17326831995

个人简介

严栗翔博士现任清华大学教育学院人工智能教育研究所助理教授。他长期从事人工智能、教育技术与学习分析交叉领域的研究,致力于探索前沿技术与人类学习过程的深度融合,通过数据与智能技术更好地理解并优化学习与教学过程。凭借在多模态学习分析与生成式人工智能教育应用方面的创新性研究成果,他入选国家高层次青年人才计划。

严博士的研究主要聚焦于两个方向。其一,他开创性地将多模态学习分析应用于复杂协作学习情境,通过整合位置、语音、生理等多源数据,揭示协作学习中的行为模式、互动结构与调节机制,为真实学习环境中的教学设计与评估提供数据驱动的证据基础。其二,他系统性地探讨生成式人工智能在教育中的机遇与挑战,围绕学习支持、学习分析、智能体协作以及人工能动性等议题开展前瞻性研究,推动人机协同学习的新范式发展。

他的研究成果发表于 Nature Human Behaviour、Nature Reviews Psychology、Computers & Education、British Journal of Educational Technology 等国际顶尖期刊,并在学习分析与人工智能教育领域产生了广泛影响。同时,他积极参与国际学术共同体建设,担任 British Journal of Educational Technology 特约编辑、Journal of Learning Analytics 特约编辑,以及 国际学习分析学会(SoLAR)理事成员(Members-at-Large) 等学术服务职务。

教育背景

博士 (信息技术), 2020/07 - 2023/12

○ 莫纳什大学 (Monash University), 澳大利亚

硕士 (应用心理学), 2018/07 - 2019/12

○ 墨尔本大学 (University of Melbourne), 澳大利亚

学士 (心理学), 2014/03 - 2016/12

○ 墨尔本大学 (University of Melbourne), 澳大利亚

工作履历

助理教授, 2025/08 - 至今

○ 清华大学

博士后研究员, 2023/12 - 2025/07

○ 莫纳什大学 (Monash University), 澳大利亚

学术兼职

第一特约编辑, British Journal of Educational Technology, 2026/03 - 至今

理事成员(Members-at-Large), Society for Learning Analytics Research (SoLAR), 2026/02 - 至今

专题分会共同主席(PIP Track Co-Chair), The 27th International Conference on Artificial Intelligence in Education (AIED 2026), 2025/12 - 2026/07

第一特约编辑, British Journal of Educational Technology, 2024/05 - 2025/09

特约编辑, Journal of Learning Analytics, 2024/05 - 2025/03

青年学者编委会委员, British Journal of Educational Technology, 2024/03 - 至今

工作坊组织者, International Learning Analytics and Knowledge (LAK) Conference, 2024/03 - 至今

峰会主组织者, Adaptive Skills and Knowledge for the Age of AI (ASK4AI) Melbourne Summit, 2024

特邀讲师, 奥地利维也纳工业大学建筑学院, 2024

博士论文评审组成员, Saleh Ramadhan Alghamdi, 2024

博士论文评审组成员, Sehrish Iqbal, 2024

组委会成员(学生代表), The Australian Learning Analytics Summer Institute (ALASI), 2022

讲授课程

● 教育大数据与学习行为分析(81030202-0)

研究领域及概况

研究领域: 人工智能教育、生成式人工智能、教育智能体、教育技术学、多模态学习分析、人机交互、协作学习

研究概况: 严博士的研究聚焦于教育与技术的交叉领域,旨在利用人工智能、数据分析和人机交互的前沿理论与技术,为真实的学习与教学场景提供富有洞察力的支持。其研究特色在于跨学科的深度融合以及理论与实践的紧密结合。

学术贡献1:协作学习中的多模态学习分析。 严博士开创性地运用多模态学习分析方法(结合定位、音频、生理等多源数据),深入揭示了协作学习(尤其是在医疗模拟等复杂情境中)的行为模式、时间动态及影响因素,为优化协作学习的设计与评估提供了坚实的实证依据。

学术贡献2:教育领域的生成式人工智能。 严博士对生成式人工智能在教育中的应用进行了系统性、前瞻性的研究,全面审视了其作为学习工具的机遇与挑战。他不仅探讨了其变革学习交付与评估的潜力,还深入分析了相关的模型、伦理及评估难题,并在顶尖期刊组织专题,引领该领域的国际学术讨论。

研究课题

  1. 项目负责人, Evaluating and Cultivating Generative AI Literacy in Computer Science Education, FIT Early Career Researcher Seed Grant, 莫纳什大学 (2.3万澳元), 2024-2025.

  2. 项目负责人, Augmenting Learning Analytics Dashboard with Interactive AI Agents, OpenAI Research Grant, OpenAI (1.8万美元), 2024-2025.

  3. 课题负责人, Empowering Indigenous Language Learning through Co-created Knowledge Graph, Monash Data Futures Institute (3.2万澳元), 2023-2024.

  4. 项目负责人, Clatics - Real-time Classroom Analytics, Monash Generator Accelerator Program, 莫纳什大学 (1万澳元), 2022-2023.

  5. 项目骨干, Assessments for writing with generative artificial intelligence, Australian Research Council (70万澳元), 2024-2027.

  6. 项目骨干, Human-centred Teamwork Analytics, Australian Research Council (24万澳元), 2021-2024.

  7. 项目骨干, Researching Digital Citizenship in Asia-Pacific, UNESCO Grant (3.9万澳元), 2021-2022.

奖励与荣誉

入选国家高层次青年人才计划,2025

Wiley年度高被引文章, British Journal of Educational Technology, 2021-2022.

Wiley年度高被引文章, British Journal of Educational Technology, 2023-2024.

最佳论文奖提名, The 15th International Conference on Learning Analytics & Knowledge (LAK'25), 2025.

最佳论文奖提名, The 14th International Conference on Learning Analytics & Knowledge (LAK'24), 2024 (2篇).

最佳论文奖提名, The 24th International Conference on Artificial Intelligence in Education (AIED'23), 2023.

最佳论文奖, The 12th International Conference on Learning Analytics & Knowledge (LAK'22), 2022.

特邀报告

  1. 主旨报告, Generative AI and Learning Analytics, The 14th International Learning Analytics and Knowledge Conference (LAK'24), 日本京都, 2024.

  2. 特邀网络研讨会报告, Socio-spatial Learning Analytics for Embodied Collaborative Learning, Society for Learning Analytics Research (SoLAR), 线上, 2023.

  3. 主旨报告, Practical and ethical challenges of large language models in education, AIED for the Future International Forum & the BNU Digital Learning Festival, 北京师范大学珠海校区未来教育学院, 线上, 2023.

  4. 专题研讨会报告, How do teachers use open learning spaces? Mapping from teachers' socio-spatial data to spatial pedagogy, The 20th Biennial EARLI Conference, 希腊塞萨洛尼基, 2023.

学术成果

Yan, L., Greiff, S., Lodge, J. M., & Gašević, D. (2025). Distinguishing performance gains from learning when using generative AI. Nature Reviews Psychology, 1-2.

Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839-1850.

Yan, L., Martinez-Maldonado, R., Jin, Y., Echeverria, V., Milesi, M., Fan, J., . . . Gašević, D. (2025). The effects of generative AI agents and scaffolding on enhancing students’ comprehension of visual learning analytics. Computers & Education.

Yan, L., Echeverria, V., Jin, Y., Fernandez‐Nieto, G., Zhao, L., Li, X., . . . Martinez‐Maldonado, R. (2024). Evidence‐based multimodal learning analytics for feedback and reflection in collaborative learning. British Journal of Educational Technology, 55(5), 1900-1925.

Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., . . . Gašević, D. (2023). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 1-23.

Yan, L., Martinez‐Maldonado, R., Zhao, L., Dix, S., Jaggard, H., Wotherspoon, R., . . . Gašević, D. (2023). The role of indoor positioning analytics in assessment of simulation‐based learning. British Journal of Educational Technology, 54(1), 267-292.

Yan, L., Martinez‐Maldonado, R., Gallo Cordoba, B., Deppeler, J., Corrigan, D., & Gašević, D. (2022). Mapping from proximity traces to socio‐spatial behaviours and student progression at the school. British Journal of Educational Technology, 53(6), 1645-1664.

Yan, L., Whitelock‐Wainwright, A., Guan, Q., Wen, G., Gašević, D., & Chen, G. (2021). Students’ experience of online learning during the COVID‐19 pandemic: A province‐wide survey study. British Journal of Educational Technology, 52(5), 2038-2057.

Yan, L., Martinez-Maldonado, R., Swiecki, Z., Zhao, L., Li, X., & Gašević, D. (2024). Dissecting the temporal dynamics of embodied collaborative learning using multimodal learning analytics. Journal of Educational Psychology.

Yan, L., Gašević, D., Echeverria, V., Zhao, L., Jin, Y., Li, X., & Martinez-Maldonado, R. (2025). In Sync or Out of Sync? Understanding Stress and Learning Performance in Collaborative Healthcare Simulations through Physiological Synchrony and Arousal. International Journal of Artificial Intelligence in Education, 1-32.

Yan, L., Martinez-Maldonado, R., Cordoba, B. G., Deppeler, J., Corrigan, D., Nieto, G. F., & Gasevic, D. (2021). Footprints at school: Modelling in-class social dynamics from students’ physical positioning traces. Paper presented at the LAK21: 11th international learning analytics and knowledge conference.

Yan, L., Gasevic, D., Echeverria, V., Jin, Y., Zhao, L., & Martinez-Maldonado, R. (2025). From Complexity to Parsimony: Integrating Latent Class Analysis to Uncover Multimodal Learning Patterns in Collaborative Learning. Paper presented at the Proceedings of the 15th International Learning Analytics and Knowledge Conference.

Yan, L., Martinez-Maldonado, R., & Gasevic, D. (2024). Generative artificial intelligence in learning analytics: Contextualising opportunities and challenges through the learning analytics cycle. Paper presented at the Proceedings of the 14th Learning Analytics and Knowledge Conference.

Yan, L., Martinez-Maldonado, R., Zhao, L., Deppeler, J., Corrigan, D., & Gasevic, D. (2022). How do Teachers Use Open Learning Spaces? Mapping from Teachers’ Socio-spatial Data to Spatial Pedagogy. Paper presented at the LAK22: 12th international learning analytics and knowledge conference.

Yan, L., Martinez-Maldonado, R., Zhao, L., Li, X., & Gasevic, D. (2023). SeNA: Modelling socio-spatial analytics on homophily by integrating social and epistemic network analysis. Paper presented at the LAK23: 13th International Learning Analytics and Knowledge Conference.

Yan, L., Martinez-Maldonado, R., Zhao, L., Li, X., & Gašević, D. (2023). Physiological synchrony and arousal as indicators of stress and learning performance in embodied collaborative learning. Paper presented at the International Conference on Artificial Intelligence in Education.

Yan, L., Talic, S., Wild, H., Gasevic, D., Gasević, D., Ilic, D., . . . Trauer, J. (2022). Transmission of SARS-CoV-2 in a primary school setting with and without public health measures using real-world contact data: A modelling study. Journal of Global Health, 12, 05034.

Yan, L., Tan, Y., Swiecki, Z., Gašević, D., Williamson Shaffer, D., Zhao, L., . . . Martinez-Maldonado, R. (2023). Characterising individual-level collaborative learning behaviours using ordered network analysis and wearable sensors. Paper presented at the International Conference on Quantitative Ethnography.

Yan, L., Zhao, L., Echeverria, V., Jin, Y., Alfredo, R., Li, X., . . . Martinez-Maldonado, R. (2024). VizChat: enhancing learning analytics dashboards with contextualised explanations using multimodal generative AI chatbots. Paper presented at the International Conference on Artificial Intelligence in Education.

Yan, L., Zhao, L., Gaševic, D., Li, X., & Martinez-Maldonado, R. (2023). Socio-Spatial Learning Analytics in Co-located Collaborative Learning Spaces: A Systematic Literature Review. Journal of Learning Analytics, 10(3), 45-63.

Yan, L., Zhao, L., Gasevic, D., & Martinez-Maldonado, R. (2022). Scalability, Sustainability, and Ethicality of Multimodal Learning Analytics. Paper presented at the LAK22: 12th international learning analytics and knowledge conference.

Yan, L., Echeverria, V., Fernandez-Nieto, G. M., Jin, Y., Swiecki, Z., Zhao, L., . . . Martinez-Maldonado, R. (2024). Human-AI collaboration in thematic analysis using ChatGPT: A user study and design recommendations. Paper presented at the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems.

Yan, L. (2023). Socio-spatial Learning Analytics. Monash University,

Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R. (2024). Human-centred learning analytics and AI in education: A systematic literature review. Computers and Education: Artificial Intelligence, 100215.

Alfredo, R., Echeverria, V., Zhao, L., Lawrence, L., Fan, J. X., Yan, L., . . . Martinez-Maldonado, R. (2024). Designing a human-centred learning analytics dashboard in-use. Journal of Learning Analytics, 11(3), 62-81.

Damşa, C., Echeverria, V., Popov, V., Chernikova, O., Karlgren, K., Milesi, M., . . . Yan, L. (2025). Enhancing Team-Based Medical Simulations: Learning Through Reflection with Analytics and AI Tools. Paper presented at the Proceedings of the 18th International Conference on Computer-Supported Collaborative Learning-CSCL 2025, pp. 516-524.

Echeverria, V., Martinez-Maldonado, R., Yan, L., Zhao, L., Fernandez-Nieto, G., Gašević, D., & Shum, S. B. (2022). HuCETA: A framework for human-centered embodied teamwork analytics. IEEE Pervasive Computing, 22(1), 39-49.

Echeverria, V., Yan, L., Zhao, L., Abel, S., Alfredo, R., Dix, S., . . . Buckingham Shum, S. (2024). TeamSlides: A multimodal teamwork analytics dashboard for teacher-guided reflection in a physical learning space. Paper presented at the Proceedings of the 14th learning analytics and knowledge conference.

Echeverria, V., Zhao, L., Alfredo, R., Milesi, M. E., Jin, Y., Abel, S., . . . Wotherspoon, R. (2025). TeamVision: An AI-powered Learning Analytics System for Supporting Reflection in Team-based Healthcare Simulation. Paper presented at the Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.

Feng, S., Yan, L., Zhao, L., Maldonado, R. M., & Gašević, D. (2024). Heterogenous network analytics of small group teamwork: Using multimodal data to uncover individual behavioral engagement strategies. Paper presented at the Proceedings of the 14th learning analytics and knowledge conference.

Jin, Y., Echeverria, V., Yan, L., Zhao, L., Alfredo, R., Tsai, Y.-S., . . . Martinez-Maldonado, R. (2024). FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics. Journal of Learning Analytics, 11(3), 6-23.

Jin, Y., Martinez-Maldonado, R., Gašević, D., & Yan, L. (2025). GLAT: The generative AI literacy assessment test. Computers and Education: Artificial Intelligence, 100436.

Jin, Y., Yan, L., Echeverria, V., Gašević, D., & Martinez-Maldonado, R. (2025). Generative AI in higher education: A global perspective of institutional adoption policies and guidelines. Computers and Education: Artificial Intelligence, 8, 100348.

Jin, Y., Yang, K., Yan, L., Echeverria, V., Zhao, L., Alfredo, R., . . . Gasevic, D. (2025). Chatting with a learning analytics dashboard: The role of generative AI literacy on learner interaction with conventional and scaffolding chatbots. Paper presented at the Proceedings of the 15th International Learning Analytics and Knowledge Conference.

Jovanovic, J., Gašević, D., Yan, L., Baker, G., Murray, A., & Gasevic, D. (2024). Explaining trace‐based learner profiles with self‐reports: The added value of psychological networks. Journal of Computer Assisted Learning, 40(4), 1481-1499.

Khosravi, H., Shibani, A., Jovanovic, J., Pardos, Z. A., & Yan, L. (2025). Generative AI and Learning Analytics: Pushing Boundaries, Preserving Principles. Journal of Learning Analytics, 12(1), 1-11.

Li, T., Yan, L., Iqbal, S., Srivastava, N., Singh, S., Raković, M., . . . Fan, Y. (2025). Analytics of self-regulated learning strategies and scaffolding: Associations with learning performance. Computers and Education: Artificial Intelligence, 100410.

Li, X., Yan, L., Zhao, L., Martinez-Maldonado, R., & Gasevic, D. (2023). CVPE: A computer vision approach for scalable and privacy-preserving socio-spatial, multimodal learning analytics. Paper presented at the LAK23: 13th International Learning Analytics and Knowledge Conference.

Li, Y., Sha, L., Yan, L., Lin, J., Raković, M., Galbraith, K., . . . Chen, G. (2023). Can large language models write reflectively. Computers and Education: Artificial Intelligence, 4, 100140.

Martinez-Maldonado, R., Echeverria, V., Fernandez-Nieto, G., Yan, L., Zhao, L., Alfredo, R., . . . Wotherspoon, R. (2023). Lessons learnt from a multimodal learning analytics deployment in-the-wild. ACM Transactions on Computer-Human Interaction, 31(1), 1-41.

Martínez-Maldonado, R., Yan, L., Deppeler, J., Phillips, M., & Gašević, D. (2022). Classroom Analytics: Telling stories about learning spaces using sensor data. In Hybrid learning spaces (pp. 185-203): Springer International Publishing.

Milesi, M. E., Alfredo, R., Echeverria, V., Yan, L., Zhao, L., Tsai, Y.-S., & Martinez-Maldonado, R. (2024). " It's Really Enjoyable to See Me Solve the Problem like a Hero": GenAI-enhanced Data Comics as a Learning Analytics Tool. Paper presented at the Extended abstracts of the CHI conference on human factors in computing systems.

Sha, L., Fincham, E., Yan, L., Li, T., Gašević, D., Gal, K., & Chen, G. (2023). The road not taken: preempting dropout in moocs. Paper presented at the International Conference on Artificial Intelligence in Education.

Shao, H., Martinez-Maldonado, R., Echeverria, V., Yan, L., & Gasevic, D. (2024). Data storytelling in data visualisation: Does it enhance the efficiency and effectiveness of information retrieval and insights comprehension? Paper presented at the Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems.

Yang, K., Raković, M., Liang, Z., Yan, L., Zeng, Z., Fan, Y., . . . Chen, G. (2025). Modifying AI, enhancing essays: How active engagement with generative AI boosts writing quality. Paper presented at the Proceedings of the 15th International Learning Analytics and Knowledge Conference.

Zhao, L., Echeverria, V., Swiecki, Z., Yan, L., Alfredo, R., Li, X., . . . Martinez-Maldonado, R. (2024). Epistemic network analysis for end-users: Closing the loop in the context of multimodal analytics for collaborative team learning. Paper presented at the Proceedings of the 14th learning analytics and knowledge conference.

Zhao, L., Echeverria, V., Tan, Y., Yan, L., Li, X., Alfredo, R., . . . Osborne, A. (2024). Ordered Networked Analysis of Multimodal Data in Healthcare Simulations: Dissecting Team Communication Tactics.

Zhao, L., Gašević, D., Swiecki, Z., Li, Y., Lin, J., Sha, L., . . . Martinez‐Maldonado, R. (2024). Towards automated transcribing and coding of embodied teamwork communication through multimodal learning analytics. British Journal of Educational Technology, 55(4), 1673-1702.

Zhao, L., Swiecki, Z., Gasevic, D., Yan, L., Dix, S., Jaggard, H., . . . Alfredo, R. (2023). METS: Multimodal learning analytics of embodied teamwork learning. Paper presented at the LAK23: 13th International learning analytics and knowledge conference.

Zhao, L., Tan, Y., Gašević, D., Shaffer, D. W., Yan, L., Alfredo, R., . . . Martinez-Maldonado, R. (2023). Analysing verbal communication in embodied team learning using multimodal data and ordered network analysis. Paper presented at the International Conference on Artificial Intelligence in Education.

Zhao, L., Yan, L., Gasevic, D., Dix, S., Jaggard, H., Wotherspoon, R., . . . Martinez-Maldonado, R. (2022). Modelling co-located team communication from voice detection and positioning data in healthcare simulation. Paper presented at the LAK22: 12th international learning analytics and knowledge conference.


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