DYNAMIC TRANSITIONS DURING COLLABORATION
Leveraged human-AI complementarity and human-centred design to co-design an AI-based orchestration tool that distributes power across teachers, students, and technology. This orchestration tool is situated in middle school math classrooms while engaging in dynamic transitions between individual and collaborative learning.
Lawrence, L., *Guo, B., *Yang, K., Echeverria, V., *Kang, Z., *Bathala, V., *Li, C., *Huang, W., Rummel, N., & Aleven, V. (2022). Process to co-design AI-based orchestration tools to support dynamic transitions: Design narratives through Conjecture Mapping. Paper accepted at the15th Annual Conference on Computer Supported Collaborative Learning. International Society of the Learning Sciences. Hiroshima, Japan. Best Design Paper Award. [link] [pdf]
Lawrence, L., Rummel, N., & Aleven, V. (2022). Ethical consideration for designing AI to support dynamic learning transitions. Symposium conducted at the15th Annual Conference on Computer Supported Collaborative Learning. International Society of the Learning Sciences. Hiroshima, Japan. [link] [pdf]
Yang, K., Lawrence, L., Echeverria, V., Guo , B., Holstein, K., Rummel, K., & Aleven, V. (2021). “I like student choice, program insights, but final say from the teacher”: Teachers’ preferences regarding human-AI control in dynamic student pairing. In European Conference on Technology Enhanced Learning. Springer, Cham.
Yang, K., Wang, X., Echeverria, V., Lawrence, L., Holstein, K., Rummel, K., & Aleven, V. (2021). SimPairing - Exploring the coverage of dynamic pairing policies through historical data simulation and user-centered research.