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Investigation on the Relationships among Media Characteristics, Presence, Flow, and Learning Effects in Augmented Reality Based Learning

  • Kye Bokyung

Abstract

This study’s goal is to examine which factors of augmented reality (AR), the fruit of future technologies, help to improve learning effects and reveal the relationships of those factors. To that end, we studied preceding researches and selected five factors which can influence learning effects in augmented reality based learning. We discovered the effectiveness structure of media utilization in augmented reality based learning through investigating relations of those factors. The five factors selected were: sensory immersion, navigation, manipulation, presence, and flow. A questionnaire was made based on these research questions and a survey was conducted on 290 fifth graders at two elementary schools. A total of 272 cases were examined for this study (incomplete and untrustworthy questionnaires were excluded) and analyzed using a structural equation model. The results showed that with the exception of navigation, all the factors such as sensory immersion, manipulation, presence, and flow had meaningful influence on satisfaction, knowledge & understanding, and learning effects of application. In particular, manipulation factor was proved to have a direct effect on satisfaction and the application aspect of learning effects, indicating that strengthening manipulation through the tangible interface of augmented reality can be an important factor in learning satisfaction and application fields. In addition, sensory immersion was proved to have a meaningful influence on immersion in learning and learning effects. In terms of learning effects, application of augmented reality media was shown to have more influence on application factors than on knowledge & understanding. Based on such study results, we propose the following tasks

Keywords

Confirmatory Factor Analysis Virtual Reality Virtual Environment Augmented Reality Learning Effect 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Vieweg+Teubner | GWV Fachverlage GmbH, Wiesbaden 2008

Authors and Affiliations

  • Kye Bokyung
    • 1
  1. 1.Republic of Korea

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