The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Use of the ARCS model in education: A literature review
Abstract
Abstract This article reviews empirical research on applying the Attention, Relevance, Confidence, and Satisfaction (ARCS) model to real educational settings, including computer-based learning approaches. This review focuses on three aspects: (1) how the ARCS model was applied to what specific educational settings; (2) what research methods were used; and (3) what outcomes were reported in these studies. Our findings indicate that the ARCS model was applied to a variety of countries and educational settings. The course component(s) in which the ARCS model was incorporated included single course component (e.g. course email), multiple course components, and other programs (e.g. specific software or game). Quantitative methods were used more than qualitative and mixed methods in these reviewed studies. Four major research outcomes were found in regard to participants’ affective domain, cognitive domain, learning behaviors, and psychological traits. We also summarized the studies in this review and provided future research directions. The latter includes applications of design-based research to educational problems that the ARCS model might address, especially in the context of computer-based learning.
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Cites
Three Approaches to Qualitative Content Analysis
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Design-Based Research: An Emerging Paradigm for Educational Inquiry
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Development and use of the ARCS model of instructional design
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Self-citationInterest, Learning, and Motivation
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Toward a Design Science of Education
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Motivational Design for Learning and Performance: The ARCS Model Approach
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Self-citationEducational Data Mining and Learning Analytics
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Conceptual and Empirical Issues in the Estimation of Educational Production Functions
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AI-based personalized E-learning systems: Issues, challenges, and solutions
Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022) · IEEE Access · doi:10.1109/access.2022.3193938 · Cited by 386
Kong, S.-C., & Yang, Y. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3392830 · Cited by 298
Theories of motivation: A comprehensive analysis of human behavior drivers
Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104177 · Cited by 555
Lin, P.-Y., Chai, C.-S., Jong, M. S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100006 · Cited by 171
Evaluating the effectiveness of blended learning using the ARCS model
Ma, L., & Lee, C. S. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12579 · Cited by 132
Metadata
- Authors
- Li, K., & Keller, J. M.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 122
- Pages
- 54-62
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2794495222
- Cited by
- 292
- References
- 48
- FWCI
- 24.68
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
