Description
Despite long-standing awareness that social interaction is an integral part of knowledge construction, efforts to study complex collaborative learning have traditionally been relegated to qualitative and small-scale methodologies. Relatively new data traces left by online learning environments, including massive open online courses (MOOCs), offer the first real hope for scaling up such analyses. The purpose of the proposed research is to develop comprehensive models for collaborative learning which in turn will enable instructional design and the authentic assessment of the individual within the group context. This task is undertaken by an interdisciplinary team of researchers with specializations in natural language processing, discourse analysis, social network analysis, educational data mining and psychometrics.
| Status | Finished |
|---|---|
| Effective start/end date | 9/1/14 → 8/31/17 |
Funding
- National Science Foundation (NSF): $226,587.00
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interaction
network analysis
scaling
discourse analysis
specialization
psychometrics
learning
performance
social network
learning environment
methodology
language
Group