Exploring student information problem solving behaviour using fine-grained concept map and search tool data

Alexander Whitelock-Wainwright, Nathan Laan, Dunwei Wen, Dragan Gašević

    Research output: Contribution to journalJournal Articlepeer-review

    27 Citations (Scopus)

    Abstract

    For learners to be successful in an information problem solving task, they should be able to effectively regulate their own behaviour. Despite views that such behaviour may come naturally to an individual, research generally shows that some learners do experience problems with information problem solving that may stem from such things as limited prior knowledge. As a means of addressing this challenge, the authors explored how the provision of both a concept map and search tool could overcome barriers to effective information problem solving. This was explored in the current study using data collected from 111 undergraduate students who completed an information problem solving activity, wherein a concept map and search tool were provided to help them write two short essays. Through the use of event-sequence analysis and hierarchical clustering, two information problem solving strategy groups were identified (High Engagement and Low Engagement), which differed across time-on-task and essay grades. Additional analyses were undertaken to explore self-reported prior knowledge or motivation as predictors of group assignment. The findings show that even when presented with opportunities (i.e., concept map) to support effective information problem solving, not all learners will take advantage or glean the benefits of such tools. Trace data methodology is shown to be a promising approach to explore information problem solving behaviour that can overcome the limitations of solely relying upon self-report measures.

    Original languageEnglish
    Article number103731
    JournalComputers and Education
    Volume145
    DOIs
    Publication statusPublished - Feb. 2020

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