Abstract
This paper discusses the data-driven development of a model which predicts whether a student could answer a question correctly without requesting help. This model contributes to a broader piece of research, the primary goal of which was to predict affective characteristics of students working in ILEs. The paper presents the bayesian network which provides adequate predictions, and discusses how its accuracy is taken into account when the model is integrated in an ILE. Future steps to improve the results are briefly discussed. © Springer-Verlag Berlin Heidelberg 2008.
Cite
CITATION STYLE
Mavrikis, M. (2008). Data-driven prediction of the necessity of help requests in ILEs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5149 LNCS, pp. 316–319). https://doi.org/10.1007/978-3-540-70987-9_43
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