Markov chain and classification of difficulty levels enhances the learning path in one digit multiplication

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Abstract

In this work we focus on a specific application named "1x1 trainer" that has been designed to assist children in primary school to learn one digit multiplications. We investigate the database of learners' answers to the asked questions by applying Markov chain and classification algorithms. The analysis identifies different clusters of one digit multiplication problems in respect to their difficulty for the learners. Next we present and discuss the outcomes of our analysis considering Markov chain of different orders for each question. The results of the analysis influence the learning path for every pupil and offer a personalized recommendation proposal that optimizes the way questions are asked to each pupil individually. © 2014 Springer International Publishing.

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Taraghi, B., Saranti, A., Ebner, M., & Schön, M. (2014). Markov chain and classification of difficulty levels enhances the learning path in one digit multiplication. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8523 LNCS, pp. 322–333). Springer Verlag. https://doi.org/10.1007/978-3-319-07482-5_31

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