摘要：The present study uses a text data mining approach to automatically discover learner interests in open
learning environments. We propose a method to construct learner interests automatically from the
combination of learner generated content and their dynamic interactions with other learning resources. We
develop a learner-topic model to discover not only the learner’s knowledge interests (interest in generating
content), but also the learner’s collection interests (interest in collecting content generated by others). Then
we combine the extracted knowledge interests and collection interests to yield a set of interest words for
each learner. Experiments using a dataset from the Learning Cell Knowledge Community demonstrate that
this method is able to discover learners’ interests effectively. In addition, we find that knowledge interests
and collection interests are related and consistent in their subject matter. We further show that learner
interest words discovered by the learner-topic model method include learner self-defined interest tags, but
reflect a broader range of interests.
