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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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Al-Dujaily, Amal; Kim, Jieun; Ryu, Hokyoung – Educational Technology & Society, 2013
A concern of computer-based learning system design is how to accommodate learners' individual differences during learning activities. Previous research suggests that adaptive e-learning systems can effectively address such individual differences and, consequently, they enable more directed tutoring via computer-assisted instruction. In this paper,…
Descriptors: Electronic Learning, Extraversion Introversion, Individual Differences, Learning Activities
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Mikropoulos, Tassos A.; Katsikis, Apostolos; Nikolou, Eugenia; Tsakalis, Panayiotis – Journal of Biological Education, 2003
This article reports on the design, development and evaluation of an educational virtual environment for biology teaching. In particular it proposes a highly interactive three-dimensional synthetic environment involving certain learning tasks for the support of teaching plant cell biology and the process of photosynthesis. The environment has been…
Descriptors: Computer Simulation, Cytology, Biology, Virtual Classrooms