Abstract
Group work is an essential activity during both graduate and undergraduate formation. Although there is a vast theoretical literature and numerous case studies about group work, we haven’t yet seen much development concerning the assessment of individual group participants. The problem relies on the difficulty to have the perception of each student’s contribution towards the whole work. We propose and describe a novel tool to manage and assess individual group. Using the collected interactions from the tool usage we create a model for predicting ill-conditioned interactions which generate alerts. We also describe a functionality to predict the final activity grading, based on the interaction patterns and on an automatic classification of these interactions.
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Acknowledgements
This work is financed by ERDF – European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project «Reminds»/UTAP-ICDT/EEI-CTP/0022/2014.
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Figueira, A. (2015). Predicting Results from Interaction Patterns During Online Group Work. In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, E. (eds) Design for Teaching and Learning in a Networked World. EC-TEL 2015. Lecture Notes in Computer Science(), vol 9307. Springer, Cham. https://doi.org/10.1007/978-3-319-24258-3_33
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DOI: https://doi.org/10.1007/978-3-319-24258-3_33
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