ISSN: 2222-6990
Open access
The integration of artificial intelligence in education is a significant advancement that fundamentally transforms education delivery and reception. Artificial intelligence relies on technologies like machine learning and big data analysis to offer customized and interactive learning experiences. Analyzing students' performance and providing individualized advice may improve their knowledge. Artificial intelligence (AI) may also enhance the creation of cutting-edge educational materials using technologies like augmented and virtual reality, making the learning experience more engaging and interesting. Nevertheless, further comprehensive research is necessary to fully understand the lasting impact of AI approaches on student learning results. In order to address this deficiency, the present work proposes a novel strategy that integrates bibliometric analysis with systematic literature review (SLR) utilizing the PRISMA methodology. The first stage focused on a comprehensive bibliometric, which included key nations, educational establishments, publications, keywords, and influential authors in the realm of artificial intelligence in education. This phase facilitated a comprehensive understanding of the overall state of this field across different disciplines. The subsequent phase was a systematic literature review (SLR) of 12 specifically chosen scholarly articles. This review focused on the current use of artificial intelligence (AI) in education. This review also examined the impact of implementing artificial intelligence (AI) in education, specifically focusing on its influence on student motivation and the desire to learn.The present study aims to implement artificial intelligence (AI) technology in education and explore strategies for achieving sustainable education for future generations.
Abalkheel, A. (2022). Amalgamating Bloom's taxonomy and artificial intelligence to face the challenges of online EFL learning amid post-COVID-19 in Saudi Arabia. International Journal of English Language and Literature Studies, 11(1), 16-30.
Al-Qarni, S., & Omran, A. (2021). The effect of artificial intelligence (Microboit) in raising the motivation toward learning programming among the students of educational technology at King University in Jeddah. Journal, 5(30), 58-76.
Alshahrani, A. (2023). The impact of ChatGPT on blended learning: Current trends and future research directions. International Journal of Data and Network Science, 2029–2040.
Amirbekova, E., Shertayeva, N., & Mironova, E. (2024). Teaching chemistry in the metaverse: The effectiveness of using virtual and augmented reality for visualization. Frontiers in Education.
Chrysafadi, K., Virvou, M., Tsihrintzis, G. A., & Hatzilygeroudis, I. (2023). Evaluating the user’s experience, adaptivity, and learning outcomes of a fuzzy-based intelligent tutoring system for computer programming for academic students in Greece. Education and Information Technologies, 28, 6453–6483.
Hodges, S., Sentence, S., Waite, J., MacLeod, E., & Yeomans, L. (2017). Creating cool stuff: Pupils' experience of the BBC micro: bit. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 531-536). ACM.
Karal, H., Nabiyev, V., Erümit, A. K., Arslan, S., & Çebi, A. (2014). Students' opinions on artificial intelligence-based distance education system (Artimat). Procedia-Social and Behavioral Sciences, 136, 549-553.
Hsieh, Y.-Z., Lin, S. S., Luo, Y.-C., Jeng, Y.-L., Tan, S. W., Chen, C. R., & Chiang, P. Y. (2020). ARCS-assisted teaching robots based on anticipatory computing and emotional big data for improving sustainable learning efficiency and motivation. Sustainability Journal, 5605.
Ili?, M. P., P?un, D., Ševi?, P. N., Hadži?, A., & Jianu, A. (2021). Needs and performance analysis for changes in higher education and implementation of artificial intelligence, machine learning, and extended reality. Education Sciences, 11, 568.
Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(37).
Koc-Januchta, M. M., Schonborn, K. J., Tibell, L. A. E., Chaudhri, V. K., & Heller, H. C. (2020). Engaging with biology by asking questions: Investigating students’ interaction and learning with an artificial intelligence-enriched textbook. Journal of Educational Computing Research, 58(6), 1190–1224.
Li, P., Fang, Z., & Jiang, T. (2022). Research into improved distance learning using VR technology. Frontiers in Education Journal, 7, 757874.
Li, K. (2023). Determinants of college students’ actual use of AI-based systems: An extension of the technology acceptance model. Sustainability, 15, 5221.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., & Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. International Journal of Surgery, 88, 105906.
Pu, S., Ahmad, N. A., Md, M. N., Khambari, M., Yap, N. K., & Ahrari, S. (2021). Improvement of pre-service teachers' practical knowledge and motivation about artificial intelligence through a service-learning-based module in Guizhou, China: A quasi-experimental study. Asian Journal of University Education (AJUE), 17(3).
Sumakul, D. T. Y. G., & Hamied, F. A. (2023). Amotivation in AI injected EFL classrooms: Implications for teachers. Indonesian Journal of Applied Linguistics, 13(1), 26-34.
(Nabhani et al., 2024)
Nabhani, F. Al, Hamzah, M. bin, & Hassna, H. A. (2024). Learning Motivation via Artificial Intelligence: A Bibliometric and Systematic Literature Analysis. International Journal of Academic Research in Business and Social Sciences, 14(7), 952–970.
Copyright: © 2024 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode