Abstract
One of the main concerns of user modelling for adaptive hypermedia deals with automatic user profile acquisition. In this paper we present a new approach to predict sequential/global dimension of Felder-Silverman’s learning style model that only makes use of mouse movement patterns. The results obtained in a case study with 18 students are very promising. We found a strong correlation between maximum vertical speed and sequential/global dimension score. Moreover, it was possible to predict whether students’ learning styles are global or sequential with high accuracy (94.4%). This suggests that mouse movement patterns can be a powerful source of information about certain user features.
This work is supported by the Spanish Ministry of Science and Education, projects TIN2007-64718, TEC2006-13141-C03-03 and BFU2006-07902/BFI. We are also grateful to GHIA and ATVS groups of Escuela Politécnica Superior (UAM) for their comments.
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Spada, D., Sánchez-Montañés, M., Paredes, P., Carro, R.M. (2008). Towards Inferring Sequential-Global Dimension of Learning Styles from Mouse Movement Patterns. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2008. Lecture Notes in Computer Science, vol 5149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70987-9_48
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DOI: https://doi.org/10.1007/978-3-540-70987-9_48
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