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Title:
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CLUSTERING OF LEARNERS BASED ON KNOWLEDGE MAPS |
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Author(s):
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Akira Onoue, Atsushi Shimada, Tsubasa Minematsu and Rin-ichiro Taniguchi |
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ISBN:
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978-989-8533-93-7 |
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Editors:
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Demetrios G. Sampson, Dirk Ifenthaler, Pedro Isaías and Maria Lidia Mascia |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Knowledge Map, Similarity, Pagerank, Netsimile, Clustering, Infinite Relational Model
1. |
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Type:
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Full Paper |
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First Page:
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363 |
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Last Page:
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370 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This study aimed to cluster learners based on the structures of the knowledge maps they created. Learners drew their own
knowledge maps to reflect their learning activities. Our system collected individual knowledge maps from many learners
and clustered them to generate an integrated version of the knowledge maps of each cluster. We applied the graph
analysis method to extract important keywords from the knowledge map. The results of the analysis showed that the
utilization of the knowledge map helped to improve lectures and grasp the learners level of understanding. We
conducted surveys asking course managers to evaluate the effectiveness of the integrated knowledge maps of learners
included in the cluster and received both positive and negative responses. |
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