Trends and Achievements in Learning Technology

Trends and Achievements in Learning Technology

A Systematic Review of the Application of Artificial Intelligence in Representing and Facilitating the Understanding of Abstract Phenomena and Concepts in Science Instruction

Document Type : education

Authors
1 M.A. Student, Department of Educational Foundations, University of Shiraz, Shiraz, Iran
2 Assistant professor of foundation of education of Shiraz University
Abstract
This qualitative study aimed to investigate the mechanisms, effects, and implications of Artificial Intelligence (AI) application in representing and facilitating the understanding of abstract phenomena and concepts in elementary science education. The research design followed a qualitative approach, employing a systematic review and thematic synthesis methodology, guided by the PRISMA statement. The scope of the research encompassed credible studies published between 1390-1404 Solar Hijri (2010-2025 AD). A purposive sampling strategy, based on predefined criteria, was utilized to select the study sample. The search strategy, adhering to PRISMA guidelines, involved searching, screening, and evaluating relevant articles from domestic databases including Magiran, IranDoc, Civilica, and Noormags, as well as international databases such as Web of Science, Scopus, ScienceDirect, and Google Scholar, using specific keywords. After excluding duplicates and applying inclusion/exclusion criteria, 10 articles were selected for final analysis. The data were analyzed using the thematic analysis method to extract the main themes. Findings revealed that AI, through mechanisms such as multimodal representations, interactive simulations, knowledge modeling, and personalized learning, significantly aids in better comprehension of abstract phenomena and concepts in elementary science. Specifically, AI reduces cognitive load, enhances causal reasoning, increases learner motivation and engagement, and elevates learning from rote memorization to deep conceptual and exploratory understanding. Consequently, AI can serve as an effective tool for transforming elementary science education. However, its successful implementation necessitates appropriate instructional design and readiness in terms of infrastructure and professional development for teachers.
Keywords
Subjects

شمس، عارف، امین‌موسوی، سید عبداله، و ملکی‌نیا، محمد. (۱۴۰۵). پیشران‌های بنیادین پذیرش هوش مصنوعی در سازمان‌های آموزش‌محور: یک مدل علّی غیرخطی مبتنی بر ISM–MICMAC. روندها و دستاوردها در فناوری یادگیری، ۱(۳)، ۱۰۷–۱۴۲. https://doi.org/10.22034/jlt.2026.2081055.1072
محمدی‌نژاد، علی‌رضا، و نیکبخت، امید. (۱۴۰۰). تحلیل تأثیر برنامه‌های آموزشی مبتنی بر فناوری‌های واقعیت مجازی در بهبود یادگیری مفاهیم پیچیده. پژوهش و نوآوری در تربیت و توسعه، ۱(۱)، ۱–۱۲. https://doi.org/10.61838/jsied.1.1.1
مصرآبادی، جواد، فرید، ابوالفضل، و باغبانی، زهرا. (۱۳۹۹). اثربخشی سازمان‌دهنده‌های تصویری بر دانش، درک و کاربرد مفاهیم علوم تجربی. آموزش و ارزشیابی، ۱۳(۵۲)، ۱۳–۳۶. https://doi.org/10.30495/jinev.2021.680634
هاشمی، نوروز، و میرزایی‌علیعربی، روح‌الله. (۱۴۰۵). ارزشیابی یادگیری مفهوم حد با استفاده از هوش مصنوعی. روندها و دستاوردها در فناوری یادگیری، ۱(۳)، ۳۳–۶۹. https://doi.org/10.22034/jlt.2026.2078437.1064
Anderson, J. E., Nguyen, C. A., & Moreira, G. (2025). Generative AI-driven personalization of the Community of Inquiry model: Enhancing individualized learning experiences in digital classrooms. International Journal of Information and Learning Technology, 42(3), 296–310. https://doi.org/10.1108/IJILT-10-2024-0240
Arici, F., & Yilmaz, M. (2023). An examination of the effectiveness of problem-based learning method supported by augmented reality in science education. Journal of Computer Assisted Learning, 39(2), 446–476. https://doi.org/10.1111/jcal.12752
Azevedo, R., & Aleven, V. (2013). Metacognition and learning technologies: An overview of current interdisciplinary research. Springer. https://doi.org/10.1007/978-1-4419-5546-3
Banda, H., & Nzabahimana, J. (2022). The impact of Physics Education Technology (PhET) interactive simulation based learning on motivation and academic achievement among Malawian physics students. Journal of Science Education and Technology, 32, 127–141. https://doi.org/10.1007/s10956-022-10010-3
Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. National Academy Press. https://doi.org/10.17226/9853
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
de Jong, T., & van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179–201. https://doi.org/10.3102/00346543068002179
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Medaglia, R., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, Article 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Farrokhnia, M., Pijeira-Díaz, H. J., Noroozi, O., & Hatami, J. (2019). Computer-supported collaborative concept mapping: The effects of different instructional designs on conceptual understanding and knowledge co-construction. Computers & Education, 142, Article 103640. https://doi.org/10.1016/j.compedu.2019.103640
Ghazi, S. R., & Ullah, K. (2015). Concrete operational stage of Piaget's cognitive development theory: An implication in learning general science. Gomal University Journal of Research, 31(1), 78–89. http://purl.org/coar/version/c_970fb48d4fbd8a85
Hashemi, N., & Mirzaei Aliarabi, R. (2026). Assessment of learning the concept of limits using artificial intelligence. Journal of Trends and Achievement in Learning Technology, 3(1), 33–69. https://doi.org/10.22034/jlt.2026.2078437.1064 [In Persian]
Haug, B. S., & Odegaard, M. (2014). From words to concepts: Focusing on word knowledge when teaching for conceptual understanding within an inquiry-based science setting. Journal of Science Education and Technology, 23(4), 524–537. https://doi.org/10.1007/s11165-014-9402-5
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Holzinger, A., Langs, G., Denk, H., Zatloukal, K., & Müller, H. (2019). Causability and explainability of artificial intelligence in medicine. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(4), e1312. https://doi.org/10.1002/widm.1312
Jiang, H., Zhu, D., Chugh, R., et al. (2025). Virtual reality and augmented reality-supported K-12 STEM learning: Trends, advantages and challenges. Education and Information Technologies, 30, 12827–12863. https://doi.org/10.1007/s10639-024-13210-z
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Mayer, R. E. (2021). Multimedia learning (3rd ed.). Cambridge University Press.
Mesrabadi, J., Farid, A., & Baghbani, Z. (2020). The effectiveness of graphic organizers on knowledge, comprehension, and application of science concepts. Journal of Instruction and Evaluation, 13(52), 13–36. https://doi.org/10.30495/jinev.2021.680634 [In Persian]
Mohammadi-Nejad, A. R., & Nikbakht, O. (2021). Analysis of the effects of educational programs based on virtual reality technologies on improving the learning of complex concepts. Journal of Research and Innovation in Education and Development, 1(1), 1–12. https://doi.org/10.61838/jsied.1.1.1 [In Persian]
Potter, T. S. (2024). Applying causal reasoning to investigate multicausality in microbial systems. Ecosphere, 15(5), e4782. https://doi.org/10.1002/ecs2.4782
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
Rutten, N., van Joolingen, W. R., & van der Veen, J. T. (2012). The learning effects of computer simulations in science education. Computers & Education, 58(1), 136–153. https://doi.org/10.1016/j.compedu.2011.07.017
Shams, A., Amin Mousavi, S. A., & Maleki Nia, M. (2026). Fundamental drivers of artificial intelligence adoption in education-oriented organizations: A nonlinear causal model based on ISM–MICMAC. Journal of Trends and Achievement in Learning Technology, 3(1), 107–142. https://doi.org/10.22034/jlt.2026.2081055.1072 [In Persian]
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8, Article 45. https://doi.org/10.1186/1471-2288-8-45
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369
Vosniadou, S. (2013). International handbook of research on conceptual change (2nd ed.). Routledge. https://doi.org/10.4324/9780203154472
Woolf, B. P. (2021). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann.
Xue, Y., & Wang, Y. (2022). Artificial intelligence for education and teaching. Wireless Communications and Mobile Computing, 2022, Article 4750018. https://doi.org/10.1155/2022/4750018
Yufei, L., Saleh, S., Jiahui, H., & Abdullah, S. M. S. (2020). Review of the application of artificial intelligence in education. International Journal of Innovation, Creativity and Change, 12(8), 548–562. https://doi.org/10.53333/ijicc2013/12850
Zarnik, E., Schwendimann, B. A., & Linn, M. C. (2017). Drawing to learn: How diagramming supports memory and understanding in STEM learning. Learning and Instruction, 49, 30–40. https://doi.org/10.1016/j.learninstruc.2017.01.002
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

  • Receive Date 24 May 2026
  • Revise Date 10 July 2026
  • Accept Date 07 September 2026
  • Publish Date 27 September 2026