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A Derivation of Factors Influencing the Innovation Diffusion of the OpenStreetMap in STEM Education

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  • Steven J. H. Shiau

    (Department of Engineering Science, National Cheng Kung University, No.1, University Road, Tainan City 701, Taiwan
    National Center for High-Performance Computing, No. 7, R&D Rd. VI, Hsinchu 30076, Taiwan)

  • Chi-Yo Huang

    (Department of Industrial Education, National Taiwan Normal University, Taipei 106, Taiwan)

  • Chia-Lee Yang

    (National Center for High-Performance Computing, No. 7, R&D Rd. VI, Hsinchu 30076, Taiwan)

  • Jer-Nan Juang

    (Department of Engineering Science, National Cheng Kung University, No.1, University Road, Tainan City 701, Taiwan)

Abstract

Geographic information is a confluence of knowledge from spatial science, information technologies, engineering, and mathematics, etc. Effective spatial training can enhance achievement in science, technology, engineering, and mathematics (STEM) education. Therefore, the geographic information system (GIS) plays a daily role in modern STEM education. Volunteered Geographical Information (VGI) is characterized by the openness of the geographic information being generated and accumulated by volunteers. Within the VGI sphere, OpenStreetMap (OSM) is one of the most well-known VGI due to its openness, flexibility, cost-effectiveness, and web-based mapping capability, making it one of the best alternatives for use as the mapping application for STEM education. However, very few or no prior works have investigated the factors influencing the innovation diffusion of OSM in STEM education. Therefore, to fill this gap, this work aims to investigate these factors. To achieve this purpose, the authors have defined an analytic framework based on innovation diffusion theory (IDT) and the technology acceptance model (TAM). The factors influencing students’ acceptance and intention to continue using and diffusing OSM in STEM education will be investigated. Partial least squares structural equation modeling (PLS-SEM) was used to confirm the hypothesized IDT–TAM integrated model. An empirical study based on sample data collected from 145 Taiwanese undergraduate and graduate students from engineering-related institutes was used to demonstrate the feasibility of the proposed analytic framework and to derive the factors related to the adoption and diffusion of OSM in STEM education. The proposed theoretical framework forged in this study was proven to be successful. Based on the empirical study results, ease of use, observability, and compatibility are the most influential factors in OSM diffusion. Therefore, activities that enhance the ease of use, observability, and compatibility of OSM should be emphasized so that STEM students’ perception of the usefulness of the technology and their perceived attitude towards it leads to the intention to continue the use of OSM. The analytic results can serve as a foundation for the design, development, and accelerated adoption and diffusion of OSM in STEM education.

Suggested Citation

  • Steven J. H. Shiau & Chi-Yo Huang & Chia-Lee Yang & Jer-Nan Juang, 2018. "A Derivation of Factors Influencing the Innovation Diffusion of the OpenStreetMap in STEM Education," Sustainability, MDPI, vol. 10(10), pages 1-29, September.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3447-:d:172368
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    References listed on IDEAS

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    1. Chi-Yo Huang & Hui-Ya Wang & Chia-Lee Yang & Steven J. H. Shiau, 2020. "A Derivation of Factors Influencing the Diffusion and Adoption of an Open Source Learning Platform," Sustainability, MDPI, vol. 12(18), pages 1-27, September.
    2. Chi-Yo Huang & Min-Jen Yang & Jeen-Fong Li & Hueiling Chen, 2021. "A DANP-Based NDEA-MOP Approach to Evaluating the Patent Commercialization Performance of Industry–Academic Collaborations," Mathematics, MDPI, vol. 9(18), pages 1-26, September.
    3. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    4. Chi-Yo Huang & Liang-Chieh Wang & Ying-Ting Kuo & Wei-Ti Huang, 2021. "A Novel Analytic Framework of Technology Mining Using the Main Path Analysis and the Decision-Making Trial and Evaluation Laboratory-Based Analytic Network Process," Mathematics, MDPI, vol. 9(19), pages 1-24, October.
    5. Chih-Hsing Liu & Quoc Phong La & Yen-Ling Ng & Rullyana Puspitaningrum Mamengko, 2023. "Discovering the Sustainable Innovation Service Process of Organizational Environment, Information Sharing and Satisfaction: The Moderating Roles of Pressure," Sustainability, MDPI, vol. 15(14), pages 1-26, July.

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