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Barata, Gabriel; Gama, Sandra; Jorge, Joaquim; Gonçalves, Daniel – IEEE Transactions on Learning Technologies, 2016
State of the art research shows that gamified learning can be used to engage students and help them perform better. However, most studies use a one-size-fits-all approach to gamification, where individual differences and needs are ignored. In a previous study, we identified four types of students attending a gamified college course, characterized…
Descriptors: Prediction, Performance, Profiles, Games
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Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
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Kaschig, A.; Maier, R.; Sandow, A.; Lazoi, M.; Schmidt, A.; Barnes, S.-A.; Bimrose, J.; Brown, A.; Bradley, C.; Kunzmann, C.; Mazarakis, A. – IEEE Transactions on Learning Technologies, 2013
The level of similarity of knowledge work across occupations and industries allows for the design of supportive information and communication technology (ICT) that can be widely used. In a previous ethnographically informed study, we identified activities that can be supported to increase knowledge maturing, conceptualized as goal-oriented…
Descriptors: Learning Activities, Technology Uses in Education, Best Practices, Telephone Surveys