NDLI: Automatic Group Formation for Informal Collaborative Learning

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Automatic Group Formation for Informal Collaborative Learning

Content Provider	ACM Digital Library
Author	Okamoto, Toshio Rubens, Neil Vilenius, Mikko
Abstract	Ability to find appropriate collaborators and learning materials is crucial for informal collaborative learning. However, traditional group formation models are not applicable/effective in informal learning settings since little is known about learners and learning materials and teacher's assistance is not available. We propose the data-driven group formation model that automatically extracts information about learners and learning materials from multiple data sources (databases of academic publications, wikis, social networking cites, blogs, forums, etc) and automatically forms collaborative learning groups. The open source implementation of the model (a part of WebClass-RAPSODY learning management system) consists of loosely coupled modules (implementing the proposed methods for data mashup, mining and inference) integrated through the web services interface; allowing for easy adaptation, extension and customization of the model.
Starting Page	231
Ending Page	234
Page Count	4
File Format	PDF
ISBN	9780769538013
DOI	10.1109/WI-IAT.2009.270
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-09-15
Access Restriction	Subscribed
Subject Keyword	Automatic group formation computer-supported collaborative learning (cscl) informal learning expertise finding mashup data mining similarity-based learning
Content Type	Text
Resource Type	Article

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