Abstract
This paper presents the case study of collaboration analysis in the context of an undergraduate student engineering project. Shared Wiki spaces used by students in collaborative project teams were analyzed and the paper presents new techniques, based on descriptive statistics and the Labeled Latent Dirichlet Allocation (LLDA) model for multi-label document classification, to assess quality of student work in shared wiki spaces. A link is shown between processes of collaboration, performance and work pace.
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© 2011 Springer-Verlag Berlin Heidelberg
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Ganapathy, C., Kang, JH., Shaw, E., Kim, J. (2011). Classification Techniques for Assessing Student Collaboration in Shared Wiki Spaces. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_68
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DOI: https://doi.org/10.1007/978-3-642-21869-9_68
Publisher Name: Springer, Berlin, Heidelberg
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