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Rahimi, Seyedahmad; Shute, Valerie; Zhang, Qian – International Journal of Technology in Education and Science, 2021
Persistence is an important part of student success--both in and out of school. To enhance persistence, we first need to assess it accurately. Digital games can be used as vehicles for measuring and enhancing persistence. The purpose of this study is to test the effects of (a) game-level characteristics (i.e., game mechanics and conceptual…
Descriptors: Educational Games, Computer Games, Game Based Learning, Problem Solving
Rahimi, Seyedahmad; Shute, Valerie; Zhang, Qian – Grantee Submission, 2021
Persistence is an important part of student success--both in and out of school. To enhance persistence, we first need to assess it accurately. Digital games can be used as vehicles for measuring and enhancing persistence. The purpose of this study is to test the effects of (a) game-level characteristics (i.e., game mechanics and conceptual…
Descriptors: Educational Games, Computer Games, Game Based Learning, Problem Solving
Karumbaiah, Shamya; Baker, Ryan S.; Shute, Valerie – International Educational Data Mining Society, 2018
Identifying struggling students in real-time provides a virtual learning environment with an opportunity to intervene meaningfully with supports aimed at improving student learning and engagement. In this paper, we present a detailed analysis of quit prediction modeling in students playing a learning game called Physics Playground. From the…
Descriptors: Predictor Variables, Academic Persistence, Educational Games, Play
Malkiewich, Laura; Baker, Ryan S.; Shute, Valerie; Kai, Shimin; Paquette, Luc – International Educational Data Mining Society, 2016
Educational games have become hugely popular, and educational data mining has been used to predict student performance in the context of these games. However, models built on student behavior in educational games rarely differentiate between the types of problem solving that students employ and fail to address how efficacious student problem…
Descriptors: Classification, Problem Solving, Educational Games, Models
Kai, Shiming; Paquette, Luc; Baker, Ryan S.; Bosch, Nigel; D'Mello, Sidney; Ocumpaugh, Jaclyn; Shute, Valerie; Ventura, Matthew – International Educational Data Mining Society, 2015
Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students' affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of…
Descriptors: Video Technology, Interaction, Physics, Affective Behavior