Abstract
It might be highly effective if students could transition dynamically between individual and collaborative learning activities, but how could teachers manage such complex classroom scenarios? Although recent work in AIED has focused on teacher tools, little is known about how to orchestrate dynamic transitions between individual and collaborative learning. We created a novel technology ecosystem that supports these dynamic transitions. The ecosystem integrates a novel teacher orchestration tool that provides monitoring support and pairing suggestions with two AI-based tutoring systems that support individual and collaborative learning, respectively. We tested the feasibility of this ecosystem in a classroom study with 5 teachers and 199 students over 22 class sessions. We found that the teachers were able to manage the dynamic transitions and valued them. The study contributes a new technology ecosystem for dynamically transitioning between individual and collaborative learning, plus insight into the orchestration functionality that makes these transitions feasible.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Echeverria, V., Holstein, K., Huang, J., Sewall, J., Rummel, N., Aleven, V.: Exploring human–AI control over dynamic transitions between individual and collaborative learning. In: Alario-Hoyos, C., Rodríguez-Triana, M.J., Scheffel, M., Arnedillo-Sánchez, I., Dennerlein, S.M. (eds.) EC-TEL 2020. LNCS, vol. 12315, pp. 230–243. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-57717-9_17
Holstein, K., Hong, G., Tegene, M., McLaren, B., Aleven, V.: The classroom as a dashboard: co-designing wearable cognitive augmentation for K-12 teachers. In: Proceedings of LAK, pp. 79–88 (2018)
Holstein, K., McLaren, B.M., Aleven, V.: Student learning benefits of a mixed-reality teacher awareness tool in AI-enhanced classrooms. In: Penstein Rosé, C., et al. (eds.) AIED 2018. LNCS (LNAI), vol. 10947, pp. 154–168. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93843-1_12
Kothiyal, A., Murthy, S., Iyer, S.: Think-pair-share in a large CS1 class: does learning really happen? In: Proceedings of ITiCSE, pp. 51–56 (2014)
Van Leeuwen, A., Janssen, J., Erkens, G., Brekelmans, M.: Teacher regulation of multiple computer-supported collaborating groups. Comput. Hum. Behav. 52, 233–242 (2015)
Olsen, J.K., Rummel, N., Aleven, V.: It is not either or: an initial investigation into combining collaborative and individual learning using an ITS. Int. J. Comput. Support. Collab. Learn. 14(3), 353–381 (2019). https://doi.org/10.1007/s11412-019-09307-0
Olsen, J., Rummel, N., Aleven, V.: Designing for the co-orchestration of social transitions between individual, small-group and whole-class learning in the classroom. Int. J. Artif. Intell. Educ. 31, 24–56 (2021). https://doi.org/10.1007/s40593-020-00228-w
Sergis, S., Sampson, D.G.: Teaching and learning analytics to support teacher inquiry: a systematic literature review. In: Peña-Ayala, A. (ed.) Learning Analytics: Fundaments, Applications, and Trends. SSDC, vol. 94, pp. 25–63. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-52977-6_2
Tissenbaum, M., Slotta, J.: Supporting classroom orchestration with real-time feedback: a role for teacher dashboards and real-time agents. Int. J. Comput.-Support. Collab. Learn. 14(3), 325–351 (2019). https://doi.org/10.1007/s11412-019-09306-1
Walker, E., Rummel, N., Koedinger, K.: Adaptive intelligent support to improve peer tutoring in algebra. Int. J. Artif. Intell. Educ. 24, 33–61 (2014). https://doi.org/10.1007/s40593-013-0001-9
Yang, K.B., et al.: Exploring policies for dynamically teaming up students through log data simulation. In: Proceedings of EDM (2021)
Yang, K.B., Lawrence, L., Echeverria, V., Guo, B., Rummel, N., Aleven, V.: Surveying teachers’ preferences and boundaries regarding human-AI control in dynamic pairing of students for collaborative learning. In: De Laet, T., Klemke, R., Alario-Hoyos, C., Hilliger, I., Ortega-Arranz, A. (eds.) EC-TEL 2021. LNCS, vol. 12884, pp. 260–274. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-86436-1_20
Lawrence, L., et al.: Co-designing AI-based orchestration tools to support dynamic transitions: design narratives through conjecture mapping. In: Proceedings of ISLS (2022)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Yang, K.B. et al. (2022). Technology Ecosystem for Orchestrating Dynamic Transitions Between Individual and Collaborative AI-Tutored Problem Solving. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2022. Lecture Notes in Computer Science, vol 13355. Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_66
Download citation
DOI: https://doi.org/10.1007/978-3-031-11644-5_66
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-11643-8
Online ISBN: 978-3-031-11644-5
eBook Packages: Computer ScienceComputer Science (R0)