ISSN: 2226-6348
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The integration of artificial intelligence (AI) applications into science education can serve as an effective teaching aid to develop 21st-century skills among science students. The use of AI in science education is driven by the need to enhance student engagement, personalised learning, and address persistent conceptual misunderstandings.This study aims to review the strategies employed by teachers in conducting AI-assisted teaching and learning in science education to provide authentic learning experiences while fostering skills such as creativity, collaboration, communication, and critical thinking among primary and secondary school students worldwide. This literature review follows the PRISMA model, analysing 20 articles to address the research questions. The selected articles focus on empirical studies published between 2019 and 2024, sourced from databases such as Scopus, Web of Science (WoS), and ERIC. The findings indicate that AI has the potential to enhance digital-assisted science learning without disregarding the concept of inquiry-based learning, which forms the foundation of modern science education.
Acisli Celik, S., & Ergin, I. (2022). Opinions of Middle School Students on the Concept of Science and the Use of Robotic Systems. International Journal of Technology in Education, 5(1), 154–170. https://doi.org/10.46328/ijte.232
Barell, J. (2012). How Do We Know They’re Getting Better? Assessment for 21st Century Minds, K-8. Corwin Press. https://doi.org/10.4135/9781452275376
Billings, K., Chang, H. Y., Lim-Breitbart, J. M., & Linn, M. C. (2024). Using Artificial Intelligence to Support Peer-to-Peer Discussions in Science Classrooms. Education Sciences, 14(12), 1441. https://doi.org/10.3390/educsci14121411
Burgin, S. R. (2020). A three-dimensional conceptualization of authentic inquiry-based practices: a reflective tool for science educators. International Journal of Science Education, 42(9), 1465–1484. https://doi.org/10.1080/09500693.2020.1766152
Callaghan, N. I., Khaira, S., Ouyang, A., Cadavid, J. L., Chang, H. H., Co, I. L., Diep, P., Ivanov, N., Li, G., Li, N. T., Tran-Nguyen, N., Smith, C., Davenport Huyer, L., & Kilkenny, D. M. (2021). Discovery: Virtual Implementation of Inquiry-Based Remote Learning for Secondary STEM Students During the COVID-19 Pandemic. Biomedical Engineering Education, 1(1), 87–94. https://doi.org/10.1007/s43683-020-00014-z
Celik, I., Gedrimiene, E., Siklander, S., & Muukkonen, H. (2024). The affordances of artificial intelligence-based tools for supporting 21st-century skills: A Systematic Literature Review. Australasian Journal of Educational Technology, 40(3), 19–38. https://doi.org/10.14742/ajet.9069
Chang, J., Park, J., & Park, J. (2023). Using an Artificial Intelligence Chatbot in Scientific Inquiry: Focusing on a Guided-Inquiry Activity Using Inquirybot. Asia-Pacific Science Education, 2(2), 1–31. https://doi.org/10.1163/23641177-bja10062
Chen, P. Y., & Liu, Y. C. (2024). Impact of AI Robot Image Recognition Technology on Improving Students’ Conceptual Understanding of Cell Division and Science Learning Motivation. Journal of Baltic Science Education, 23(2), 208–220. https://doi.org/10.33225/jbse/24.23.208
Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically Authentic Inquiry in Schools: A Theoretical Framework for Evaluating Inquiry Tasks. Science Education, 86(2), 175–218. https://doi.org/10.1002/sce.10001
Constantinou, C. P., Tsivitanidou, O. E., & Rybska, E. (2018). What Is Inquiry-Based Science Teaching and Learning? In Contributions from Science Education Research (Vol. 5, pp. 1–23). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-319-91406-0_1
EPPI-Centre. (2003). Review Guidelines for Extracting Data and Quality Assessing Primary Studies in Educational Research.
Grangeat, M. (2016). Dimensions and Modalities of Inquiry-Based Teaching: Understanding the Variety of Practices. Education Inquiry, 7(4), 29863. https://doi.org/10.3402/edui.v7.29863
Gupta, A., Lee, S., Mott, B., Chakraburty, S., Glazewski, K., Ottenbreit-Leftwich, A., Scribner, A., Hmelo-Silver, C. E., & Lester, J. (2024). Supporting Upper Elementary Students in Learning AI Concepts with Story-Driven Game-Based Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23092–23100. www.aaai.org
Haudek, K. C., & Zhai, X. (2023). Examining the Effect of Assessment Construct Characteristics on Machine Learning Scoring of Scientific Argumentation. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00385-8
Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M.-P., Griffiths, F., Nicolau, B., O’Cathain, A., Rousseau, M.-C., Vedel, I., & Pluye, P. (2018). The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information, 34(4), 285–291. https://doi.org/10.3233/EFI-180221
Hsu, T.-C., Abelson, H., & Van Brummelen, J. (2022). The Effects on Secondary School Students of Applying Experiential Learning to the Conversational AI Learning Curriculum The Effects on Secondary School Students of Applying Experiential Learning to the Conversational AI Learning Curriculum. International Review of Research in Open and Distributed Learning, 23(1), 82–103.
Huang, X., & Qiao, C. (2024). Enhancing Computational Thinking Skills Through Artificial Intelligence Education at a STEAM High School. Science and Education, 33(2), 383–403. https://doi.org/10.1007/s11191-022-00392-6
Jeon, M., Jantaraweragul, K., Ottenbreit-Leftwich, A., Hmelo-Silver, C., Glazewski, K., Mott, B., Lester, J., & Ringstaff, C. (2024). Inquiry-based Artificial Intelligence Curriculum for Upper Elementary Students: A Design Case of PrimaryAI. International Journal of Designs for Learning, 15(3), 94–108. https://doi.org/10.14434/ijdl.v15i3.36757
Ješková, Z., Luká?, S., Šnajder, ?., Guniš, J., Klein, D., & Kireš, M. (2022). Active Learning in STEM Education with Regard to the Development of Inquiry Skills. Education Sciences, 12(10), 686. https://doi.org/10.3390/educsci12100686
Ketak, R., Mittal, S., Gupta, V., & Gupta, H. (2024). Online Edtech Platform with AI Doubt Assistance. 2024 2nd International Conference on Disruptive Technologies (ICDT), 1395–1399. https://doi.org/10.1109/ICDT61202.2024.10489310
Kim, W. J. (2022). AI-Integrated Science Teaching Through Facilitating Epistemic Discourse in the Classroom. Asia-Pacific Science Education, 8(1), 9–42. https://doi.org/10.1163/23641177-bja10041
Kumar, I., & Mohd, N. (2024). Ways of Using Computational Thinking to Improve Students’ Ability to Think Critically. In Infrastructure Possibilities and Human-Centered Approaches With Industry 5.0 (pp. 253–266). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-0782-3.ch015
Kusuma, A. A. K., Maharani, W. A. D., Wibowo, F. C., Nasbey, H., & Costu, B. (2024). Effectiveness of Artificial Intelligent Independent Learning (AIIL) with physics chatbot of global warming concept. Momentum: Physics Education Journal, 8(1), 42–54. https://doi.org/10.21067/mpej.v8i1.8942
Lee, J., An, T., Chu, H. E., Hong, H. G., & Martin, S. N. (2023). Improving Science Conceptual Understanding and Attitudes in Elementary Science Classes through the Development and Application of a Rule-Based AI Chatbot. Asia-Pacific Science Education, 13(2), 365–412. https://doi.org/10.1163/23641177-bja10070
Lee, S., Mott, B., Ottenbreit-Leftwich, A., Scribner, A., Taylor, S., Park, K., Rowe, J., Glazewski, K., Hmelo-Silver, C. E., & Lester, J. (2021). AI-Infused Collaborative Inquiry in Upper Elementary School: A Game-Based Learning Approach. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 35(17), 15591–15599. www.aaai.org
Lin, C.-C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y
Lockwood, C., Munn, Z., & Porritt, K. (2015). Qualitative research synthesis. International Journal of Evidence-Based Healthcare, 13(3), 179–187. https://doi.org/10.1097/XEB.0000000000000062
Magee, D., & Meier, A. J. (2011). Science Education and Culture: Inquiry-Based Learning. Journal of Intercultural Communication, 11(3), 1–14. https://doi.org/10.36923/jicc.v11i3.538
Mahroof, A., Gamage, V., Rajendran, K., Rajkumar, S., Rajapaksha, S., & Wijendra, D. (2020). An AI based chatbot to self-learn and self-assess performance in ordinary level chemistry. ICAC 2020 - 2nd International Conference on Advancements in Computing, Proceedings, 216–221. https://doi.org/10.1109/ICAC51239.2020.9357131
MOE. (2023). Digital Education Policy (Dasar Pendidikan Digital). Ministry of Education Malaysia. https://www.moe.gov.my/storage/files/shares/Dasar/Dasar%20Pendidikan%20Digital/Digital%20Education%20Policy.pdf
MOE. (2024a). KPM Sambut Baik Pelaburan Google di Malaysia, Perkukuhkan Pelaksanaan Dasar Pendidikan Digital. Ministry of Education Malaysia. Press Release . https://www.moe.gov.my/storage/files/shares/Kenyataan%20Media/KM2024/KM%20KPM%20Sambut%20Baik%20Pelaburan%20Google%20Di%20Malaysia%2C%20Perkukuhkan%20Pelaksanaan%20Dasar%20Pendidikan%20Digital.pdf
MOE. (2024b). Apple Learning Coach Perkasakan Kompetensi Digital Guru. Ministry of EducationMalaysia. Press Release. https://www.moe.gov.my/storage/files/shares/Kenyataan%20Media/KM2024/KM%20Apple%20Learning%20Coach%20Perkasakan%20Kompetensi%20Digital%20Guru.pdf
Mohamed Shaffril, H. A., Samsuddin, S. F., & Abu Samah, A. (2021). The ABC of systematic literature review: the basic methodological guidance for beginners. Quality & Quantity, 55(4), 1319–1346. https://doi.org/10.1007/s11135-020-01059-6
Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., Mcdonald, S., … Mckenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. In The BMJ (Vol. 372). BMJ Publishing Group. https://doi.org/10.1136/bmj.n160
Radif, M. (2024). Artificial Intelligence in Education: Transforming Learning Environments and Enhancing Student Engagement. Educational Sciences: Theory and Practice, 24(1), 93–103.
Ruži?i?, V. (2024). Overview and Implementation of Artificial Intelligence in the Improvement of Educational Process. Journal of Scientific & Industrial Research, 83(5). https://doi.org/10.56042/jsir.v83i5.3192
Suto, I., & Eccles, H. (2014). The Cambridge approach to 21 st Century skills: definitions, development and dilemmas for assessment IAEA Conference, Singapore, 2014 Irenka Suto and Helen Eccles, Cambridge Assessment. IAEA Conference, 1–10.
Topal, A. D., Dilek Eren, C., & Kolburan Geçer, A. (2021). Chatbot application in a 5th grade science course. Education and Information Technologies, 26(5), 6241–6265. https://doi.org/10.1007/s10639-021-10627-8
Watters, J., Liu, C., Hill, A., & Jiang, F. (2020). An artificial intelligence tool for accessible science education. IMCIC 2020 - 11th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings, 1, 147–150. https://doi.org/10.14448/jsesd.13.0010
Williams, P. J., Nguyen, N., & Mangan, J. (2017). Using technology to support science inquiry learning. Journal of Technology and Science Education, 7(1), 26–57. https://doi.org/10.3926/jotse.234
Wu, T., & Tegmark, M. (2019). Toward an artificial intelligence physicist for unsupervised learning. Physical Review E, 100(3), 033311.
Y?lmaz, Ö. (2024). Personalised learning and artificial intelligence in science education: current state and future perspectives. Educational Technology Quarterly, 2024(3), 255–274. https://doi.org/10.55056/etq.744
Zhai, X., He, P., & Krajcik, J. (2022). Applying machine learning to automatically assess scientific models. Journal of Research in Science Teaching, 59(10), 1765–1794. https://doi.org/10.1002/tea.21773
Zhou, X., Tang, J., Lyu, H., Liu, X., Zhang, Z., Qin, L., Au, F., Sarkar, A., & Bai, Z. (2024). Creating an Authoring Tool for K-12 Teachers to Design ML-Supported Scientific Inquiry Learning. Conference on Human Factors in Computing Systems - Proceedings, 1–7. https://doi.org/10.1145/3613905.3650762
Ramli, N. A., & Mahmud, S. N. D. (2025). Integration of Artificial Intelligence to Support Inquiry-Based Science Teaching and Learning: A Systematic Literature Review. International Journal of Academic Research in Progressive Education and Development, 14(2), 893–911.
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