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Spatial reasoning is an important skillset that is malleable to training interventions. One possible context for intervention is the popular video game Minecraft. Minecraft encourages users to engage in spatial manipulation of 3D objects. However, few papers have chronicled any in-game practices that might evidence spatial reasoning, or how we might study its development through the game. In this paper, we report on 11 middle school students’ spatial reasoning practices while playing Minecraft. We use audio and video data of student gameplay to delineate five in-game practices that align with spatial reasoning. We expand on a student case study, to explicate these practices. The identified practices may be beneficial for studying spatial reasoning development in game-based environments and contribute to a growing body of research on ways games support development of important and transferable skills.
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Investigating Student Interest in a Minecraft Game-Based Learning Environment: A Changepoint Detection Analysis
Extensive research underscores the importance of stimulating students' interest in learning, as it can improve key educational outcomes such as self-regulation, collaboration, problem-solving, and overall enjoyment. Yet, the mechanisms through which interest manifests and impacts learning remain less explored, particularly in open-ended game-based learning environments like Minecraft. The unstructured nature of gameplay data in such settings poses analytical challenges. This study employed advanced data mining techniques, including changepoint detection and clustering, to extract meaningful patterns from students' movement data. Changepoint detection allows us to pinpoint significant shifts in behavior and segment unstructured gameplay data into distinct phases characterized by unique movement patterns. This research goes beyond traditional session-level analysis, offering a dynamic view of the learning process as it captures changes in student behaviors while they navigate challenges and interact with the environment. Three distinct exploration patterns emerged: surface-level exploration, in-depth exploration, and dynamic exploration. Notably, we found a negative correlation between surface-level exploration and interest development, whereas dynamic exploration positively correlated with interest development, regardless of initial interest levels. In addition to providing insights into how interest can manifest in Minecraft gameplay behavior, this paper makes significant methodological contributions by showcasing innovative approaches for extracting meaningful patterns from unstructured behavioral data within game-based learning environments. The implications of our research extend beyond Minecraft, offering valuable insights into the applications of changepoint detection in educational research to investigate student behavior in open-ended and complex learning settings.
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- PAR ID:
- 10600279
- Editor(s):
- Benjamin, Paaßen; Carrie, Demmans Epp
- Publisher / Repository:
- International Educational Data Mining Society
- Date Published:
- ISSN:
- DOI: 10.5281/zenodo.12729844
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5281/zenodo.12729844
