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Direct linkKapelner, Adam; Soterwood, Jeanine; Nessaiver, Shalev; Adlof, Suzanne – IEEE Transactions on Learning Technologies, 2018
Vocabulary knowledge is essential to educational progress. High quality vocabulary instruction requires supportive contextual examples to teach word meaning and proper usage. Identifying such contexts by hand for a large number of words can be difficult. In this work, we take a statistical learning approach to engineer a system that predicts…
Descriptors: Vocabulary Development, Databases, Training, Models
Whitehill, Jacob; Movellan, Javier – IEEE Transactions on Learning Technologies, 2018
We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Educational Policy, Comparative Analysis
Kaser, Tanja; Klingler, Severin; Schwing, Alexander G.; Gross, Markus – IEEE Transactions on Learning Technologies, 2017
Intelligent tutoring systems adapt the curriculum to the needs of the individual student. Therefore, an accurate representation and prediction of student knowledge is essential. Bayesian Knowledge Tracing (BKT) is a popular approach for student modeling. The structure of BKT models, however, makes it impossible to represent the hierarchy and…
Descriptors: Bayesian Statistics, Models, Intelligent Tutoring Systems, Networks
