Description
Computer supported collaborative learning (CSCL) has made great inroads in classroom teaching marked by the use of tools and technologies to support and enhance collaborative learning. Computer mediated learning environments produce large amounts of data, capturing student interactions, which can be used to analyze students’ learning behaviors (Martinez-Maldonado et al., 2013a). The analysis of the process of collaboration is an active area of research in CSCL. Contributing towards this area, Meier et al. (2007) defined nine dimensions and gave a rating scheme to assess the quality of collaboration. This thesis aims to extract and examine frequent patterns of students’ interactions that characterize strong and weak groups across the above dimensions. To achieve this, an exploratory data mining technique, differential sequence mining, was employed using data from a collaborative concept mapping activity where collaboration amongst students was facilitated by an interactive tabletop. The results associate frequent patterns of collaborative concept mapping process with some of the dimensions assessing the quality of collaboration. The analysis of associating these patterns with the dimensions of collaboration is theoretically grounded, considering aspects of collaborative learning, concept mapping, communication, group cognition and information processing. The results are preliminary but still demonstrate the potential of associating frequent patterns of interactions with strong and weak groups across specific dimensions of collaboration, which is relevant for students, teachers, and researchers to monitor the process of collaborative learning. The frequent patterns for strong groups reflected conformance to the process of conversation for dimensions related to “communication” aspect of collaboration. In terms of the concept mapping sub-processes the frequent patterns for strong groups reflect the presentation phase of conversation with processes like talking, sharing individual maps while constructing the groups concept map followed by short utterances which represents the acceptance phase. For “joint information processing” aspect of collaboration, the frequent patterns for strong groups were marked by learners’ contributing more upon each other’s work. In terms of the concept mapping sub-processes the frequent patterns were marked by learners adding links to each other’s concepts or working with each other’s concepts, while revising the group concept map.
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Title
- Using differential sequence mining to associate patterns of interactions in concept mapping activity with dimensions of collaborative process
Contributors
- Chaudhry, Rishabh (Author)
- Walker, Erin A (Thesis advisor)
- Maldonado-Martinez, Roberto (Committee member)
- Hsiao, Ihan (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2015
Subjects
Resource Type
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Note
- thesisPartial requirement for: M.S., Arizona State University, 2015
- bibliographyIncludes bibliographical references (pages 63-67)
- Field of study: Computer science
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Statement of Responsibility
by Rishabh Chaudhry