Dr Lei Shi, PhD
I am an Assistant Professor in the Innovative Computing Group at Durham University. I hold a PhD in Computer Science from the University of Warwick and an MSc in Digital Art and Design from Zhejiang University. Before joining Durham Computer Science, I was a Research Fellow at the University of Warwick, and then a Lecturer at the University of Liverpool.
My research lies at the intersection of Human-Centred Computing (HCC) and Artificial Intelligence (AI). I investigate both theoretical aspects of Human-AI collaboration and its practical applications in real-world settings. I aim at enabling computers to reproduce and complement human abilities, work with humans, and facilitate human-human collaboration. I am particularly interested in how humans perceive, interact, collaborate and co-create with AI, especially in the fields of education and social innovation.
I have worked in the domain of Intelligent Tutoring Systems, where I implemented social interactions, open user modelling and gamification based on the theoretical underpinning of Social Constructivism, Self-Determination Theory, and Flow Theory, in order to improve learning engagement, efficiency and effectiveness. I have worked on Digital Crowdsourcing to improve Situated Engagement in the co-design of built healthcare and well-being environments. I have been working on Learning Analytics, where I use statistical modelling and machine learning to analyse massive and heterogeneous data to cluster learners, model behavioural patterns and predict learning outcomes, aiming at understanding and supporting learners in open-scale courses such as MOOCs (Massive Open Online Courses).
I am keen to supervise highly self-motivated PhD students who have similar research interests to mine. If you have a master degree in artificial intelligence, data science, applied statistics, human-technology interaction, cognitive sciences, cognitive and/or experimental psychology, learning science, applied linguistics, instructional design, industrial design, innovation sciences, or similar, you are encouraged to contact me with your research proposal (max. 2 pages), CV, degree transcripts (BSc and MSc) and other supporting materials.
You will be supervised by an interdisciplinary academic team (including myself) and be part of a broader cohort of students in the Innovative Computing Group.
PhD Project Ideas
- Combining Human-Computer Collaboration and Machine Learning to build Intelligent Tutoring Systems that learn to collaborate with their human users (teachers and students) and guide their interaction and collaboration over time.
- Implementing a gamified social learning environment for students with special needs (e.g. visual and hearing impairment), for them to be motivated, satisfied and engaged in learning.
- Developing smart AR/VR/MR technologies to facilitate immersive environments that facilitate teaching and learning.
- Fabricating sim-learners that can help train educational systems to be able to understand, predict and shape learning behaviours of students.
Department of Computer Science
- Intelligent Tutoring Systems
- Behavioural Analytics
- Explainable AI
- Human-Computer Collaboration
- Human-AI Co-creation
Chapter in book
- Alamri, Ahmed, Alshehri, Mohammad, Cristea, Alexandra I., Pereira, Filipe D., Oliveira, Elaine, Shi, Lei & Stewart, Craig (2019). Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week’s Activities. In Intelligent Tutoring Systems. ITS 2019. Coy, Andre, Hayashi, Yugo & Chang, Maiga Cham: Springer. 11528: 163-173.
- Shi, Lei, MacKrill, James, Dimitrokali, Elisavet, Dawson, Carolyn & Cain, Rebecca (2015). Digital Co-design Applied to Healthcare Environments: A Comparative Study. In Human-Computer Interaction -- INTERACT 2015. Abascal, Julio, Barbosa, Simone, Fetter, Mirko, Gross, Tom, Palanque, Philippe & Winckler, Marco Springer International Publishing. 9299: 518-522.
- Shi, Lei, Cristea, Alexandra I. & Stewart, Craig (2015). Students as Customers: Participatory Design for Adaptive Web 3.0. In The Evolution of the Internet in the Business Sector: Web 1.0 to Web 3.0. IGI Global. 306-331.
- Toda, Armando, Oliveira, Wilk, Klock, Ana, Shi, Lei, Bittencourt, Ig Ibert, Gasparini, Isabela, Isotani, Seiji, Cristea, Alexandra & Palomino, Paula (2019), A Taxonomy of Game Elements for Gamification in Educational Contexts: Proposal and Evaluation, International Conference on Advanced Learning Technologies and Technology-enhanced Learning. Maceió, Brazil, IEEE, 84-88.
- Yang, Bokuan, Shi, Lei & Toda, Armando (2019), Demographical Changes of Student Subgroups in MOOCs: Towards Predicting At-Risk Students, 28th International Conference on Information Systems Development (ISD2019). Toulon, France, Association for Information Systems.
- Toda, Armando, Oliveira, Wilk, Shi, Lei, Bittencourt, Ig Ibert, Isotani, Seiji & Cristea, Alexandra I. (2019), Planning Gamification Strategies based on User Characteristics and DM: A Gender-based Case Study, in Desmarais, Michel, Lynch, Collin F., Merceron,Agathe & Nkambou, Roger eds, International Conference on Educational Data Mining. Montréal, Canada, Educational Data Mining 2019, Montréal, Canada, 438-443.
- Shi, Lei, Cristea, Alexandra I., Toda, Armando & Oliveira, Wilk (2019), Revealing the Hidden Patterns: A Comparative Study on Profiling Subpopulations of MOOC Students, 28th International Conference on Information Systems Development (ISD2019). Toulon, France, Association for Information Systems.
- Shi, Lei, Cristea, Alexandra I., Toda, Armando M. & Oliveira, Wilk (2019), Social Engagement versus Learning Engagement - An Exploratory Study of FutureLearn Learners, the IEEE International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2019). Dalian, Liaoning, IEEE.
- Oliveira,Wilk, Toda,Armando Maciel, Palomino,Paula Toledo, Rodrigues, Luiz, Shi,Lei & Isotani,Seiji (2019), Towards Automatic Flow Experience Identification in Educational Systems: A Theory-driven Approach, CHI PLAY 19. Barcelona, Spain, ACM, 581-588.
- Toda, Armando, Palomino,Paula, Rodrigues, Luiz, Oliveira, Wilk, Shi, Lei, Isotani, Seiji & Cristea, Alexandra (2019), Validating the Effectiveness of Data-Driven Gamification Recommendations: An Exploratory Study, The Brazilian Symposium on Informatics in Education (SBIE). Brasilia, Brasil, 763-772.
- Alamri, A., Rusby, H., Cristea, Alexandra I., Khan, J., Shi, Lei & Stewart, C. (2018), An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System, ACM International Conference Proceeding Series (ICPS) 3rd International Conference on Information and Education Innovations (ICIEI'18). London, Association for Computing Machinery, New York, NY, USA, 57-61.
- Cristea, Alexandra I., Alamri, Ahmed, Alshehri, Mohammad, Kayama, Mizue, Foss, Jonathan, Shi, Lei & Stewart, Craig D. (2018), Can Learner Characteristics Predict Their Behaviour on MOOCs?, 10th International Conference on Education Technology and Computers - ICETC '18. Tokyo, ACM, New York, 119-125.
- Cristea, Alexandra I., Alamri, Ahmed, Kayama, Mizue, Stewart, Craig, Alshehri, Mohammad & Shi, Lei (2018), Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses, in Andersson, B., Johansson, B., Carlsson, S., Barry, C., Lang, M., Linger, H. & Schneider, C. eds, 27th International Conference on Information Systems Development (ISD2018). Lund, Sweden, Association for Information Systems.
- Cristea, Alexandra I., Alamri, Ahmed, Kayama, Mizue, Stewart, Craig, Alshehri, Mohammad & Shi, Lei (2018), How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers, in Andersson, B., Johansson, B., Carlsson, S., Barry, C., Lang, M., Linger, H. & Schneider, C. eds, 27th International Conference on Information Systems Development (ISD2018). Lund, Sweden, Association for Information Systems.
- Alshehri,Mohammad, Foss,Jonathan, Cristea,Alexandra I., Kayama,Mizue, Shi,Lei, Alamri,Ahmed & Tsakalidis,Adam (2018), On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs, ACM International Conference Proceedings Series (ICPS) 3rd International Conference on Information and Education Innovations (ICIEI'18). London, Association for Computing Machinery, New York, NY, USA, 73-77.
- Yiwei Zhou, Cristea, Alexandra I. & Shi, Lei (2017), Connecting Targets to Tweets: Semantic Attention-based Model for Target-Specific stance Detection, in Bouguettaya, Athman Gao, Yunjun Klimenko, Andrey Chen, Lu Zhang, Xiangliang Dzerzhinskiy, Fedor Jia, Weijia Klimenko, Stanislav V. & Li, Qing eds, Lecture Notes in Computer Science 10569: Web Information Systems Engineering – WISE 2017, 18th International Conference. Moscow, Springer, Cham, 18-32.
- Alamri, Afaf S., Cristea, Alexandra I. & Shi, Lei (2016), Designing a Collaborative Group Project Recommender for an E-learning System, 2016 SAI Computing Conference (SAI). IEEE, 781-787.
- Shi, Lei, Dawson, Carolyn, MacKrill, James, Dimitrokali, Elisavet & Cain, Rebecca (2015), Digital Co-design: A Future Method?, Proceedings of the 2015 British HCI Conference on - British HCI '15. Lincoln, Lincolnshire, United Kingdom, ACM Press, 295-296.
- Shi, Lei, MacKrill, James, Dimitrokali, Elisavet & Cain, Rebecca (2015), Digital Crowdsourcing in Healthcare Environment Co-design, in Vogel, D., Guo, X., Barry, C. Lang, M., Linger, H & Schneider, C. eds, International Conference on Information Systems Development (ISD2015). Harbin, China, Association for Information Systems, 285-296.
- Shi, Lei & Cristea, Alexandra I. (2014), Making It Game-like: Topolor 2 and Gamified Social E-Learning, The 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014). Aalborg, Denmark, 61-64.
- Shi, Lei, Cristea, Alexandra I. & Hadzidedic, Suncica (2014), The Critical Role of Profiles in Social E-learning Design, SIGITE '14 Proceedings of the 15th Annual Conference on Information Technology Education. Atlanta, Georgia, USA, ACM, 71-76.
- Shi, Lei (2014). Scaffolding for Social Personalised Adaptive e-Learning. University of Warwick. PhD.
- Shi, Lei & Cristea, Alexandra I. (2016). : Learners Thrive When Using Multifaceted Open Social Learner Models. IEEE MultiMedia 23(1): 36-47.