Towards Sharing Student Models Across Learning Systems

Author:

Baker Ryan S.,McLaren Bruce M.,Hutt Stephen,Richey J. Elizabeth,Rowe Elizabeth,Almeda Ma. Victoria,Mogessie Michael,Andres Juliana M. AL.

Publisher

Springer International Publishing

Reference19 articles.

1. Aleven, V., et al.: Towards deeper integration of intelligent tutoring systems: one-way student model sharing between GIFT and CTAT. In: Proceedings of the 7th Annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium (2019)

2. Arroyo, I., Woolf, B.P.: Inferring learning and attitudes from a Bayesian Network of log file data. In: Proceedings of the International Conference on Artificial Intelligence and Education, pp. 33–40 (2005)

3. Baker, R.S.: Challenges for the future of educational data mining: the Baker learning analytics prizes. J. Educ. Data Mining 11(1), 1–17 (2019)

4. Baker, R.S., Gowda, S.M.: The 2018 technology & learning insights report: towards understanding app effectiveness and cost. BrightBytes, Inc., San Francisco, CA (2018)

5. Berking, P., Gallagher, S.: Choosing a learning management system. In: Advanced Distributed Learning (ADL) Co-Laboratories, pp. 40–62 (2013)

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