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Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Kumar, Muthu; Kan, Min-Yen; Tan, Bernard C. Y.; Ragupathi, Kiruthika – International Educational Data Mining Society, 2015
With large student enrollment, MOOC instructors face the unique challenge in deciding when to intervene in forum discussions with their limited bandwidth. We study this problem of "instructor intervention." Using a large sample of forum data culled from 61 courses, we design a binary classifier to predict whether an instructor should…
Descriptors: Intervention, Open Education, Large Group Instruction, Group Discussion
Laru, Jari; Naykki, Piia; Jarvela, Sanna – Internet and Higher Education, 2012
In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students' learning outcomes by studying probabilistic dependencies between the variables.…
Descriptors: Web Sites, Electronic Publishing, Cooperative Learning, Group Activities

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