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An Analysis of the Relationship between the Flow Experience and the Lesson Persistence Intention of Robot Programming Lesson Participants

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Computer Applications for Software Engineering, Disaster Recovery, and Business Continuity

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 340))

Abstract

The purpose of this study was to objectively analyze the active and persistent lesson participation attitude and the lesson flow phenomenon of students that are participating in robot programming lesson. The analysis information was used to identify the factors that could affect the lesson participation & flow of learners in order to identify the areas of improvement in programming lesson that is regarded as difficult by students in general. Accordingly, Technology Acceptance Model (TAM) and the Theory of Flow were examined based on which structural equation model was established and analyzed. Consequently, it was found that Perceived Ease of Use and Perceived Usefulness were factors that could affect the lesson persistence intention of learner, among which the Perceived Ease of Use factor affected the flow of learner. Meanwhile, it was also found that the factor of Balance between Challenges and Skills affected the Concentration on the task at Hand factor as well as the Perceived Usefulness factor in the flow of learner. In addition, this study also dealt with information on the relation between TAM and flow.

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Shin, S.Y., Kim, M.R. (2012). An Analysis of the Relationship between the Flow Experience and the Lesson Persistence Intention of Robot Programming Lesson Participants. In: Kim, Th., Ramos, C., Kim, Hk., Kiumi, A., Mohammed, S., Ślęzak, D. (eds) Computer Applications for Software Engineering, Disaster Recovery, and Business Continuity. Communications in Computer and Information Science, vol 340. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35267-6_38

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  • DOI: https://doi.org/10.1007/978-3-642-35267-6_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35266-9

  • Online ISBN: 978-3-642-35267-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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