Learning Analytics for Communities of Lifelong Learners: a Forum Case
This paper describes an experiment investigating interactions in a big forum in order to support students in learning English. Groups of collaborating users form communities that generate a lot of data that can be analyzed. We distinguish different phases of the self-regulated learning process and aim to identify them in learners’ activities. Then we attempt to recognize patterns of their behavior and consequently their roles in a community. Based on this analysis we try to explain a success or failure of a community. We conclude that heterogeneity of members helps a learning community to function.
Proc. ICALT 2011, 11th IEEE International Conference on Advanced Learning Technologies.
ICALT, 2011 , Athens, Georgia , US.
Proc. of the 11th IEEE International Conference on Advanced Learning Technologies , by Ignacio Aedo, Nian-Shing Chen, Demetrios G. Sampson, J. Michael Spector, Kinshuk , p. 609-610 ; IEEE Computer Society , Los Alamitos, California , US .