Collaborative Learning with Nao Robots in Middle School Mathematics
The goal of this project is to analyze how to support dyads of middle school learners who interact to teach a robot about mathematics. Learning by teaching interactions, where students explain concepts to other people or to intelligent agents, have been shown to foster improved learning, both through cognitive mechanisms and through social mechanisms. While these mechanisms have been explored in either human-human collaborative groups or human-agent dyads, this project takes a step forward by examining how these interactions unfold in more complex scenarios involving collaborative learning groups with intelligent robots. We are particularly interested in how the robot can use dialogue, gaze, and gesture to facilitate the interactions between the two students.
This NSF funded project is a collaboration with Dr. Timothy Nokes-Malach, Dr. Diane Litman, Dr. Adriana Kovashka at the University of Pittsburgh and Dr. Nikki Lobczowski at McGill University. Within the lab, Yuya Asano, Tristan Maidment, and Maria Xu are working on the project.
Publications
Asano, Y., Litman, D., Yu, M., Lobczowski, N. G., Nokes-Malach, T., Kovashka, A., & Walker, E. (2022). Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions. In Proceedings of the SIGDial 2022 Conference, 615-622.
Lobczowski, N. G., Steele, C., Yu, M., Diamond, M., Henriques, K., Kovashka, A., Litman, D. J., Nokes-Malach, T. J., & Walker, E. (2022). Exploring Relationships between Dyadic-Level Factors and Collaborative Learning Outcomes with Social Robots. Paper to be presented at the 2022 annual meeting of the Association for Educational Communications and Technology (AECT), Las Vegas.
Maidment, T., Yu, M., Lobczowski, N. G, Kovashka, A., Walker, E., Litman, D., & Nokes-Malach, T. (2022). Building a reinforcement learning environment from limited data to optimize teachable robot interventions. In Mitrovic, A. & Bosch, N. (Eds.), Proceedings of the 15th International Conference on Educational Data Mining, (pp. 62-74). International Educational Data Mining Society. doi: 10.5281/zenodo.6853129.
Steele, C., Lobczowski, N. G., Davison, T., Yu, M., Diamond, M., Kovashka, A., Litman, D., Nokes-Malach, T., & Walker, E. (2022). It Takes Two: Examining the Effects of Collaborative Teaching of a Robot Learner. In Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. (pp. 604-607). Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6.