Modeling and Studying Gaming the System with Educational Data Mining

Ryan S. J. d. Baker, A. T. Corbett, I. Roll, K. R. Koedinger, V. Aleven, M. Cocea, A. Hershkovitz, A. M. J. B. de Caravalho, A. Mitrovic, M. Mathews

פרסום מחקרי: פרק בספר / בדוח / בכנספרקביקורת עמיתים


In this chapter, we will discuss our work to understand why students game the system. This work leverages models of student gaming, termed “detectors”, which can infer student gaming in log files of student interaction with educational software. These detectors are developed using a combination of human observation and annotation, and educational data mining. We then apply the detectors to large data sets, and analyze the detectors’ predictions, using discovery with models methods, to study the factors associated with gaming behavior. Within this chapter, we will discuss the work to develop these detectors, and what we have discovered through these analyses based on these detectors. We will discuss evidence for how gaming the system impacts learning and evidence for why students choose to game. We will also discuss attempts to address gaming the system through adaptive scaffolding.
שפה מקוריתאנגלית אמריקאית
כותר פרסום המארחInternational Handbook of Metacognition and Learning Technologies
עורכיםRoger Azevedo, Vincent Aleven
מקום הפרסוםNew York, NY
מוציא לאורSpringer New York
מספר עמודים19
מסת"ב (אלקטרוני)9781441955463
מסת"ב (מודפס)9781441955463
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2013

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