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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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Bañeres, David; Clarisó, Robert; Jorba, Josep; Serra, Montse – IEEE Transactions on Learning Technologies, 2014
The synthesis of digital circuits is a basic skill in all the bachelor programmes around the ICT area of knowledge, such as Computer Science, Telecommunication Engineering or Electrical Engineering. An important hindrance in the learning process of this skill is that the existing educational tools for the design of circuits do not allow the…
Descriptors: Electronics, Design, Program Validation, Electronic Learning
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Cocea, M.; Weibelzahl, S. – IEEE Transactions on Learning Technologies, 2011
Learning environments aim to deliver efficacious instruction, but rarely take into consideration the motivational factors involved in the learning process. However, motivational aspects like engagement play an important role in effective learning-engaged learners gain more. E-Learning systems could be improved by tracking students' disengagement…
Descriptors: Prediction, Electronic Learning, Online Courses, Delivery Systems