Expert concept mapping study on mobile learning

Dirk Börner, Christian Glahn, Slavi Stoyanov, Marco Kalz, Marcus Specht

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    Abstract

    Purpose – The present paper introduces concept mapping as a structured participative conceptualization approach to identify clusters of ideas and opinions generated by experts within the domain of mobile learning. Utilizing this approach, the paper aims to contribute to a definition of key domain characteristics by identifying the main educational concepts related to mobile learning. Design/methodology/approach – A short literature review points out the attempts to find a clear definition for mobile learning as well as the different perspectives taken. Based on this an explorative case study was conducted, focusing on the educational problems that underpin the expectations on mobile learning. Using the concept mapping approach the study identified these educational problems and the related domain concepts. The respective results were then analyzed and discussed. Findings – The chosen approach produced several means to interpret the experts' ideas and opinions, such as a cluster map illustrating and structuring substantial accordances. These means help to gain new insights on the emphasis and relation of the core educational concepts of mobile learning. The core educational concepts of mobile learning identified are: “access to learning”, “contextual learning”, “orchestrating learning across contexts”, “personalization”, and “collaboration”. Originality/value – The paper is original as it uses a unique conceptualization approach to work out the educational problems that can be addressed by mobile learning and thus contributes to a domain definition based on identified issues, featured concepts, and derived challenges. In contrast to existing approaches for defining mobile learning, the present approach relies completely on the expertise of domain experts.
    Original languageEnglish
    Pages (from-to)240-253
    Number of pages14
    JournalCampus-Wide Information Systems
    Volume27
    Issue number4
    DOIs
    Publication statusPublished - 2010

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    Keywords

    • learning
    • cluster analysis

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