A key challenge for interactive learning environments is how to automatically co-regulate, balancing learners’ autonomy and the pedagogical processes intended by educators. In order to achieve personalized and dynamic co-regulation, we explore the use of artificial intelligence (AI) techniques of experience management (EM) in combination with a play-based pedagogical model. As a first step, this NSF-funded exploratory project seeks to collect preliminary data about 1) the relationship between a learner’s achievement goal orientations (learning orientation) and play style, and 2) the impact of dynamically adjusting the learning environment using EM on learner’s autonomy and learning outcomes.
- G. Mushio, J. Zhu and A. Foster, “Revitalizing Peale’s Museum as a Digital Interactive Learning Environment,” in Proceedings the Digital Heritage International Congress 2015 (DH’15), Granada, Spain, 2015, in press.
- J. Valls-Vargas, S. Ontañón and J. Zhu and, “Exploring Player Trace Segmentation for Dynamic Play Style Prediction,” in Proceedings the Eleventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-15), Santa Cruz, 2015, in press.
- J. Valls-Vargas, A. Khal, J. Patterson, G. Muschio, A. Foster, J. Zhu, “Designing and Tracking Play Styles in Solving the Incognitum,” in Proceedings of the Games+Learning+Society 11 Conference (GLS 11), 2015, in press. [PDF]
- J. Zhu, A. Foster, G. Mushio, J. Patterson, J. Valls-Vargas, D. Newman, “Designing Solving the Incognitum: Toward Automatic Co-regulation based on Play Style in Educational Games,” in Proceedings of the 2014 International Academic Conference on Meaningful Play, in press.
- J. Zhu, A. Foster, G. Mushio, J. Patterson, J. Valls- Vargas, D. Newman, “Towards Balancing Learner Autonomy and Pedagogical Process in Educational Games,” in Proceedings of the 2014 ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play (CHI PLAY), 2014, pp. 455-6. [PDF]