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Extended Technology Acceptance Models for Digital Learning: Review of External Factors

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Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022) (NiDS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 556))

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Abstract

The rapid development of information and communication technologies (ICT) has revolutionized teaching and learning strategies, leading to digital learning technologies. Digital learning is any type of learning that uses technology, such as Internet, social media, web technologies, multimedia, mobile devices, etc. Since digital learning has dominated in education nowadays, measuring the acceptance of this technology and predicting the behavioral intention to use it is of great importance. The most established model for this purpose is the Technology Acceptance Model (TAM), consisting of certain constant predictors extended by external variables. To identify the most commonly used external factors of TAM in digital learning, an analysis of 21 studies from 2015 onwards was conducted. These researches were classified into three fields of digital learning, namely e-learning, m-learning, augmented/virtual reality systems, in order to analyze the different variables used depending on the kind of system evaluated. The results show that self-efficacy, perceived enjoyment and system quality are significant predictors of user attitude used regardless of the digital learning technology evaluated, followed by subjective norm, system accessibility and facilitating conditions.

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Authors and Affiliations

  1. Department of Informatics and Computer Engineering, University of West Attica, Ag. Spyridonos Street, 12243, Egaleo, Greece

    Akrivi Krouska, Christos Troussas & Cleo Sgouropoulou

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  1. Akrivi Krouska
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  2. Christos Troussas
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  3. Cleo Sgouropoulou
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Correspondence to Akrivi Krouska .

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Editors and Affiliations

  1. University of West Attica, Aigaleo, Greece

    Akrivi Krouska

  2. University of West Attica, Aigaleo, Greece

    Christos Troussas

  3. College of Engineering, University of the Philippines, Diliman, Philippines

    Jaime Caro

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Krouska, A., Troussas, C., Sgouropoulou, C. (2023). Extended Technology Acceptance Models for Digital Learning: Review of External Factors. In: Krouska, A., Troussas, C., Caro, J. (eds) Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022). NiDS 2022. Lecture Notes in Networks and Systems, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-17601-2_6

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