The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Research trends in the use of augmented reality in science education: Content and bibliometric mapping analysis
Abstract
Abstract The aim of this study was to reveal research trends over the last six years by content analysis and to examine bibliometric results of articles related to the use of augmented reality (AR) in science education. For bibliometric mapping analysis, a total of 147 articles were accessed and for content analysis, a total of 79 articles published between 2013 and 2018 years were included from the Web of Science. From this, a total of 62 articles were selected for analysis. Our results revealed that mobile learning, science education, science learning and e-learning were the most used keywords in articles, while the focus of more recent articles tended to be on mobile learning. The results showed that recent articles have mostly focused on mobile learning and e-learning environments. The most-used words in the abstracts were education, knowledge, science education, experiment and effectiveness. It is evident that recent articles have focused mostly on students' knowledge and achievement. Azuma, Dunleavy and Klopfer are the most cited authors in this field. This is not surprising as they are probably the leading authors on AR in the literature. The most cited journals are Computers & Education, Journal of Science Education & Technology, Educational Technology and Society, Computers in Human Behavior, and British Journal of Educational Technology. These are the most prominent journals on the use of technology in education. Content analysis results showed that “Learning/Academic Achievement”, “Motivation” and “Attitude” have been the most examined variables in the articles. Since academic achievement is highly influenced by motivation and attitude, it is understandable that these variables are considered together in reviewed studies. It was found that mobile applications and marker-based materials on paper have been the most-favored types of materials for AR because these types of materials are easy to use and they can be developed easily and practically. Quantitative studies were the most used research design type but there have been only a limited number of qualitative studies in the last six years. This may be due to the increased tendency to use quantitative and mixed studies in recent years.
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Cites
Azuma, R. T. (1997) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.1997.6.4.355 · Cited by 10,121
Augmented reality for STEM learning: A systematic review
Ibáñez, M.-B., & Delgado-Kloos, C. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.05.002 · Cited by 1,036
Review of trends from mobile learning studies: A meta-analysis
Wu, W.-H., Jim Wu, Y.-C., Chen, C.-Y., Kao, H.-Y., Lin, C.-H., & Huang, S.-H. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.03.016 · Cited by 946
Huang, T.-C., Chen, C.-C., & Chou, Y.-W. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.02.008 · Cited by 453
Applications of augmented reality-based natural interactive learning in magnetic field instruction
Cai, S., Chiang, F.-K., Sun, Y., Lin, C., & Lee, J. J. (2017) · Interactive Learning Environments · doi:10.1080/10494820.2016.1181094 · Cited by 253
An Augmented-Reality-Based Concept Map to Support Mobile Learning for Science
Chen, C.-H., Chou, Y.-Y., & Huang, C.-Y. (2016) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-016-0284-3 · Cited by 149
Cited by
Application and theory gaps during the rise of artificial intelligence in education
Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100002 · Cited by 1,003
AI-enabled adaptive learning systems: A systematic mapping of the literature
Kabudi, T., Pappas, I., & Olsen, D. H. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100017 · Cited by 734
Sahin, D., & Yilmaz, R. M. (2020) · Computers & Education · doi:10.1016/j.compedu.2019.103710 · Cited by 447
Self-citationAlGerafi, M. A. M., Zhou, Y., Oubibi, M., & Wijaya, T. T. (2023) · Electronics · doi:10.3390/electronics12183953 · Cited by 373
Agbo, F. J., Oyelere, S. S., Suhonen, J., & Tukiainen, M. (2021) · Smart Learning Environments · doi:10.1186/s40561-020-00145-4 · Cited by 325
Metadata
- Authors
- Arici, F., Yildirim, P., Caliklar, Ş., & Yilmaz, R. M.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 142
- Pages
- 103647
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2968007757
- Cited by
- 442
- References
- 6
- FWCI
- 22.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- Arici, F., Yildirim, P., Caliklar, Ş., & Yilmaz, R. M. (2019). Research trends in the use of augmented reality in science education: Content and bibliometric mapping analysis. Computers & Education. https://doi.org/10.1016/j.compedu.2019.103647
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.