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      • HARVEST
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      Using data mining to dynamically build up just in time learner models

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      thesis_wengang.pdf (2.244Mb)
      Date
      2009-12
      Author
      Liu, Wengang
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      Using rich data collected from e-learning systems, it may be possible to build up just in time dynamic learner models to analyze learners' behaviours and to evaluate learners' performance in online education systems. The goal is to create metrics to measure learners' characteristics from usage data. To achieve this goal we need to use data mining methods, especially clustering algorithms, to find patterns from which metrics can be derived from usage data. In this thesis, we propose a six layer model (raw data layer, fact data layer, data mining layer, measurement layer, metric layer and pedagogical application layer) to create a just in time learner model which draws inferences from usage data. In this approach, we collect raw data from online systems, filter fact data from raw data, and then use clustering mining methods to create measurements and metrics. In a pilot study, we used usage data collected from the iHelp system to create measurements and metrics to observe learners' behaviours in a real online system. The measurements and metrics relate to a learner's sociability, activity levels, learning styles, and knowledge levels. To validate the approach we designed two experiments to compare the metrics and measurements extracted from the iHelp system: expert evaluations and learner self evaluations. Even though the experiments did not produce statistically significant results, this approach shows promise to describe learners' behaviours through dynamically generated measurements and metric. Continued research on these kinds of methodologies is promising.
      Degree
      Master of Science (M.Sc.)
      Department
      Computer Science
      Program
      Computer Science
      Supervisor
      McCalla, Gordon
      Committee
      Vassileva, Julita; Ludwig, Simone; Morrison, Dirk
      Copyright Date
      December 2009
      URI
      http://hdl.handle.net/10388/etd-01272010-215639
      Subject
      Educational Data Mining
      Learner Model
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