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

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرفصلمراجعة النظراء

ملخص

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.
اللغة الأصليةإنجليزيّة أمريكيّة
عنوان منشور المضيفInternational Handbook of Metacognition and Learning Technologies
المحررونRoger Azevedo, Vincent Aleven
مكان النشرNew York, NY
ناشرSpringer New York
الصفحات97-115
عدد الصفحات19
مستوى الصوت28
رقم المعيار الدولي للكتب (الإلكتروني)9781441955463
رقم المعيار الدولي للكتب (المطبوع)9781441955463
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 2013

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