Abstract
Simulations that combine real world components with interactive digital media provide a rich setting for students with the potential to assist knowledge building and understanding of complex physical processes. This paper addresses the problem of modeling the effects of multiple students’ simultaneous interactions on the complex and exploratory environments such simulations provide. We work towards assisting educators with the difficult task of interpreting student exploration. We represent the system dynamics that result from student actions with a complex time series and use switch based models to decompose the time series into individual periods that target interpretability for teachers. The model learns the transition points between successive periods in the time series as well as the internal dynamics that govern each period. This model differs from other switch based models in that it decomposes the time series in a way that is human interpretable. This approach was applied to data that was obtained from an existing multi-person simulation with pedagogical goals of teaching sustainability and systems thinking. A visualization of the model was designed to validate the interpretability of the generated text-based descriptions when compared to a movie representation of the system dynamics. A pilot study using this visualization indicates that the switch based model finds relevant boundaries between salient periods of student work.
Original language | English |
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State | Published - 1 Jan 2018 |
Event | 11th International Conference on Educational Data Mining, EDM 2018 - Buffalo, United States Duration: 15 Jul 2018 → 18 Jul 2018 |
Conference
Conference | 11th International Conference on Educational Data Mining, EDM 2018 |
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Country/Territory | United States |
City | Buffalo |
Period | 15/07/18 → 18/07/18 |
Keywords
- Bayesian inference
- Exploratory learning environment
- Interpretability
- Markov chain Monte Carlo
- Switching state space models
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems