Comprehensive Review on Technology-Based Learning Using Artificial Intelligence for Science Subjects and Its Implications in Teaching and Learning

Authors

  • Adli M Department of Physics, Faculty of Science and Mathematics, Sultan Idris Education University, 35900 Tanjong Malim, Perak, Malaysia.
  • Suriani Abu Bakar Department of Physics, Faculty of Science and Mathematics, Sultan Idris Education University, 35900 Tanjong Malim, Perak, Malaysia.
  • Mohd Mokhzani Ibrahim Department of Chemistry, Faculty of Science and Mathematics, Sultan Idris Education University, 35900 Tanjong Malim, Perak, Malaysia
  • Azzam AB Department of Physics, Faculty of Science and Mathematics, Sultan Idris Education University, 35900 Tanjong Malim, Perak, Malaysia.
  • Fatiatun Department of Physics Education, Faculty of Tarbiyah and Teacher Training, Universitas Sains Al-Qur’an, Wonosobo, Indonesia
  • Hamdan Hadi Kusuma Department of Physics Education, Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang, Semarang, Indonesia
  • Dwandaru WSB Department of Physics Education, Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta, Colombo St., Karangmalang, Yogyakarta, 55281, Indonesia
  • Muhammad Dhanil Department of Physics Education, Faculty of Mathematics and Natural Sciences, Universitas Negeri Padang, Padang, Indonesia.

DOI:

https://doi.org/10.37134/ejsmt.vol11.2.11.2024

Keywords:

Artificial Intelligence, Science Education, physics teaching

Abstract

Awareness of technological advancements in education is crucial to ensure that teaching and learning methods are more relevant and effective. Artificial intelligence (AI) is a new emerging technology in education, enabling computers to have human-like cognition. However, research on the effectiveness of AI technology in teaching and learning (TaL) science subjects is still limited. This literature review aims to identify trends, impacts, and challenges of AI implementation in science learning. The review employs a systematic review method consisting of four steps: framing research questions, searching for relevant articles or journals, reading and analyzing abstracts, and extracting information from the articles or journals. A total of 30 articles were reviewed in this study. The results of the review indicate that AI provides a positive effect on learning. A popular trend in the use of AI technology in science learning is chatbot from ChatGPT. The impact of applying AI in science education includes student motivation and engagement, understanding complex and abstract concepts, improving the quality of science education, personalized learning, and its use in assessment and testing. Challenges in the application of AI in science education include lack of teacher-student interaction, high dependence on AI technology, lack of teacher training, adaptation, and integration of AI technology in the curriculum, variations in accessibility and quality, and ethical challenges. AI has a great opportunity to be implemented in support of science learning, considering its impact and challenges. In general, AI has a significant influence on supporting better learning.

Downloads

Download data is not yet available.

References

Aziz, A., Hussin, A., & Noor, N. (2023). Education 4.0 made simple: Ideas for teaching. International Journal of Education and Literacy Studies, 6(3), 92-100. https://doi.org/10.7575/aiac.ijels.v.6n.3p.92

Jumriani, J., & Prasetyo, K. Z. (2022). Important roles of local potency based science learning to support the 21st century learning. European Journal of Engineering and Formal Sciences, 1(1), 6-16. https://doi.org/10.26417/ejef.v1i1.p6-16

Hallonsten, O. (2021). Stop evaluating science: A historical-sociological argument. Information Sur Les Sciences Sociales/Social Science Information, 60(1), 7–26. doi:10.1177/0539018421992204

OECD (2019). PISA 2018 Results: What Students Know and Can Do. OECD Publishing. Retrieved from OECD iLibrary.

Komatsu, H., & Rappleye, J. (2021). Rearticulating PISA. Globalisation, Societies and Education, 19(2), 245-258. https://doi.org/10.1080/14767724.2021.1878017

Ministry of Education Malaysia. (2022). Laporan awal pencapaian Malaysia dalam Programme for International Student Assessment (PISA) 2022. Bahagian Perancangan dan Penyelidikan Dasar Pendidikan, Kementerian Pendidikan Malaysia.

Amanor-Mfoafo, N. K., Edonu, K. K., Akrofi, O., & Dowuona, E. N. (2020). Towards e-learning in basic schools during COVID-19: Insights from Ghanaian teachers. European Journal of Open Education and E-learning Studies, 5(2). https://doi.org/10.46827/EJOE.V5I2.3476

Rejekiningsih, T., Maulana, I., Budiarto, M., & Subhanul Qodr, T. (2023). Android-based augmented reality in science learning for junior high schools: Preliminary study. International Journal of Evaluation and Research in Education (IJERE), 12(2), 926–935. https://doi.org/10.11591/ijere.v12i2.23886

Zubaidah Amir Mz, Risnawati, & Muhandaz, R. (2019). Konsep Sunnah dalam pembelajaran sains. Journal of Natural Science and Integration, 1(2), 185–185. https://doi.org/10.24014/jnsi.v1i2.6597

Nordin, A. S. M., Alias, B. S., & Mahamod, Z. (2023). Pendigitalan pendidikan. Jurnal Penyelidikan Pendidikan dan Teknologi Malaysia (JPPTM), 1(1), 66. ICBE Publication. ISSN (Online): 2976-2634

Mustapha, I., Van, N., Shahverdi, M., Qureshi, M. I., & Khan, N. (2021). Effectiveness of Digital Technology in Education During COVID-19 Pandemic: A Bibliometric Analysis. International Journal of Interactive Mobile Technologies (iJIM), 15(8), 72-90. https://doi.org/10.3991/ijim.v15i08.20415

Maxliyo, T. (2024). THE USE OF TECHNOLOGY IN EDUCATIONAL TEACHING. Journal of new century innovations, 50(3), 89-92.

Nurmatova, F. B., Xuan, R., & Fazilova, L. A. (2024). THE ADVANTAGES OF IMPLEMENTING DIGITAL TECHNOLOGY IN EDUCATION. Innovations in Science and Technologies, 1(3), 192-195.

Pongtambing, Y. S., Appa, F. E., Siddik, A. M. A., Sampetoding, E. A., Admawati, H., Purba, A. A., & Manapa, E. S. (2023). Peluang dan Tantangan Kecerdasan Buatan Bagi Generasi Muda. Bakti Sekawan: Jurnal Pengabdian Masyarakat, 3(1), 23-28.

Zhai, X., Wang, M., & Zhai, Y. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54(2), 391-412. https://doi.org/10.1007/s11165-024-10176-3

Basu, A. (2017). How to conduct meta-analysis: A basic tutorial.

Schardt, C., Adams, M. B., Owens, T., Keitz, S., & Fontelo, P. (2007). Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Medical Informatics and Decision Making, 7(1), 16. https://doi.org/10.1186/1472-6947-7-16

Amin, N. F., Garancang, S., & Abunawas, K. (2023). Konsep umum populasi dan sampel dalam penelitian. JURNAL PILAR, 14(1), 15-31.

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

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., & Jeyaraj, A. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research. International Journal of Information Management, 70, 102659. https://doi.org/10.1016/j.ijinfomgt.2023.102659

Van den Berg, G., & Du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998. https://doi.org/10.3390/educsci13100998

Karaman, M. R., & Göksu, A. (2024). Are lesson plans created by ChatGPT more effective? An experimental study. International Journal of Technology in Education. https://files.eric.ed.gov/fulltext/EJ1415069.pdf

Fauzi, F., Tuhuteru, L., Sampe, F., & Ausat, A. M. A. (2023). Analysing the role of ChatGPT in improving student productivity in higher education. Journal of Education. http://jonedu.org/index.php/joe/article/download/2563/2162

Yunarzat, E., Sida, S. C. N., & Kasman, K. (2024). Pengaruh penggunaan ChatGPT terhadap motivasi belajar siswa di Sekolah Menengah Kejuruan. EDUKATIF: Jurnal Ilmu Pendidikan. https://edukatif.org/index.php/edukatif/article/view/6489

Ab Hamid, E. A. H., Maskur, H., & Mutalib, M. A. (2023). The use of ChatGPT applications in learning: Impact on understanding and student engagement in TVET institutions. Malaysian Journal of Information and Communication Technology.

Makransky, G., & Lilleholt, L. (2018). A structural equation modeling investigation of the emotional engagement and cognitive load factors that affect the efficacy of virtual reality learning environments. Computers & Education, 127, 1-12. https://doi.org/10.1016/j.compedu.2018.08.002

Makransky, G., & Petersen, G. B. (2021). Investigating the effect of immersive virtual reality on attention in the classroom. Educational Technology Research and Development, 69(1), 163-178. https://doi.org/10.1007/s11423-020-09783-w

Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2020). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225-236. https://doi.org/10.1016/j.learninstruc.2017.12.007

Kibuku, R. N., Ochieng, D. O., & Wausi, A. N. (2020). E-learning challenges faced by universities in Kenya: A literature review. The Electronic Journal of e-Learning, 18(2), 150-161. https://doi.org/10.34190/EJEL.20.18.2.002

Harry, L. (2023). Role of AI in Education. Injuruty: Interdiciplinary Journal and Humanity, 2(3). https://doi.org/10.58631/injurity.v2i3.52

Wu, S.-Y., & Yang, K.-K. (2022). The effectiveness of teacher support for students’ learning of artificial intelligence popular science activities. Frontiers in Psychology, 13, Article 868623. https://doi.org/10.3389/fpsyg.2022.868623

Iyamuremye, A., & Ndihokubwayo, K. (2024). Exploring secondary school students’ interest and mastery of atomic structure and chemical bonding through the use of artificial intelligence chatbot. Educational Journal of Artificial Intelligence and Machine Learning, 1(1), 1-13. https://doi.org/10.58197/9hk37296

Hallal, K., Hamdan, R., & Tlais, S. (2023). Exploring the potential of AI-Chatbots in organic chemistry: An assessment of ChatGPT and Bard. Computers and Education: Artificial Intelligence, 5, Article 100170. https://doi.org/10.1016/j.caeai.2023.100170

West, J. K., Franz, J. L., Hein, S. M., Leverentz-Culp, H. R., Mauser, J. F., Ruff, E. F., & Zemke, J. M. (2023). An analysis of AI-generated laboratory reports across the chemistry curriculum and student perceptions of ChatGPT. Journal of Chemical Education, 100(10), 4351-4359. https://doi.org/10.1021/acs.jchemed.3c00581

Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: Revolutionizing student achievement in the electronic magnetism unit for eleventh-grade students in Emirates schools. Eurasia Journal of Mathematics, Science and Technology Education, 19(7), em2286. https://doi.org/10.29333/ejmste/13272

Suhonen, S. (2024). Navigating the AI era: Analyzing the impact of artificial intelligence on learning and teaching engineering physics. In Proceedings of the 12th International Conference on Physics Teaching in Engineering Education (PTEE 2024). Rosenheim Technical University of Applied Sciences, Germany.

Erduran, S., & Levrini, O. (2024). The impact of artificial intelligence on scientific practices: An emergent area of research for science education. International Journal of Science Education, 46(2), 1-20. https://doi.org/10.1080/09500693.2024.2306604

Selvam, A. A. A. (2024). Exploring the impact of artificial intelligence on transforming physics, chemistry, and biology education. The Cuvette. https://doi.org/10.3390/pr9101726

Ezquerra, Á., Agen, F., Rodríguez Arteche, Í., & Ezquerra-Romano, I. (2022). Integrating artificial intelligence into research on emotions and behaviors in science education. Eurasia Journal of Mathematics, Science and Technology Education, 18(4). https://doi.org/10.29333/ejmste/11927

Sanchez-Gonzalez, M., & Terrell, M. (2023). Flipped classroom with artificial intelligence: Educational effectiveness of combining voice-over presentations and AI. Cureus, 15(11), e48354. https://doi.org/10.7759/cureus.48354

Cooper, G., & Tang, K. (2024). Pixels and pedagogy: Examining science education imagery by generative artificial intelligence. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-024-10104-0

A’ini, Q. & Khoiriyah, R. (2024). Merevolusi pendidikan dengan kecerdasan buatan chatbots: Meningkatkan pembelajaran dan penilaian. Jurnal Multidisiplin Ibrahimy, 2(1), 54-71. https://doi.org/10.35316/jummy.v2i1.5510

Tan, D. Y., & Cheah, C. W. (2021). Developing a gamified AI-enabled online learning application to improve students’ perception of university physics. Computers and Education: Artificial Intelligence, 2, 100032. https://doi.org/10.1016/j.caeai.2021.100032

Ghariz, G., Seghir, H., Boucetta, N., Boubih, S., Janati-Idrissi, R., & El Alaoui, M. (2024). The impact of artificial intelligence on improving text in the process of conceptualization in biology: Case of education sector. Journal of Theoretical and Applied Information Technology, 102(13), 5203-5214. https://www.jatit.org

Maestrales, S., Zhai, X., Touitou, I., Baker, Q., Schneider, B., & Krajcik, J. (2021). Using machine learning to score multi-dimensional assessments of chemistry and physics. Journal of Science Education and Technology, 30(2), 239–254. https://doi.org/10.1007/s10956-020-09895-9

Chan, Y. L., & Norlizah, C. H. (2017). Students’ motivation towards science learning and students’ science achievement. International Journal of Academic Research in Progressive Education and Development, 6(4), 178-182. https://doi.org/10.6007/IJARPED/v6-i4/3716

Nuraysha, A. D., Winarno, N., Fadly, W., Hakim, L., & Emiliannur, E. (2024). Analyzing student’s motivation towards science learning in junior high school. Jurnal Penelitian Pendidikan IPA, 10(7), 4139–4148. https://doi.org/10.29303/jppipa.v10i7.7297

Ihsan, M. S., & Jannah, S. W. (2021). Analysis of students' scientific literacy skills in chemistry learning using blended learning-based interactive multimedia. Edumatsains, 6(1), 197-206.

Mahmudi, A. A., Fionasari, R., Mardikawati, B., & Judijanto, L. (2023). Integration of artificial intelligence technology in distance learning in higher education. Journal of Social Science Utilizing Technology, 1(4), 190–201. https://doi.org/10.70177/jssut.v1i4.661

Mezghanni, N., Rekik, G., Crowley-McHattan, Z. J., Belkhir, Y., Ben Ayed, R., Hadadi, A., Alzahrani, T. M., Kuo, C.-D., & Chen, Y.-S. (2022). Using coordinated visual and verbal cues in complex multimedia materials to improve tactical learning in soccer. International Journal of Environmental Research and Public Health, 19(6), 3365. https://doi.org/10.3390/ijerph19063365

Artanto, H., & Arifin, F. (2023). Emotions and gesture recognition using affective computing assessment with deep learning. International Journal of Artificial Intelligence, 12(3), 1419-1427. https://doi.org/10.11591/ijai.v12i3.44433

Epler, P., & Tenon, S. (2019). What is Personalized Learning in Secondary Schools? Journal of Information Technologies and Lifelong Learning, 2(1), 70–73. doi:10.20533/jitll.2633.7681.2019.0011

Jian, M. J. K. O. (2023). Personalized learning through AI. University of North Florida.

Anggoro, K. J., & Pratiwi, D. I. (2023). Fostering self-assessment in English learning with a generative AI platform: A case of Quizizz AI. Studies in Self-Access Learning Journal, 14(4), 489–501. https://doi.org/10.37237/140406

Săseanu, A. S., Gogonea, R.-M., & Ghiţă, S. I. (2023). The social impact of using artificial intelligence in education. Amfiteatru Economic, 25(57), 98-104. https://doi.org/10.24818/EA/2023/57/98

Erbaş, İ., & Maksuti, E. (2024). The impact of artificial intelligence on education. International Journal of Innovative Research in Multidisciplinary Education, 3(4). https://doi.org/10.58806/ijirme.2024.v3i4n01

Bagir, M., Onal-Karakoyun, G., & Asilturk, E. (2022). Views of science teachers on the use of artificial intelligence in education. International Online Journal of Educational Sciences, 14(5), 1223-1234. https://doi.org/10.15345/iojes.2022.05.007

Vorotnykova, I. P. (2023). Professional development of science and mathematics teachers using artificial intelligence. Open Educational E-Environment of Modern University, 15, 18-34. https://doi.org/10.28925/2414-0325.2023.152

Romanov, D. V., Filatov, T. V., & Zudilina, I. Y. (2022). Specificity of using artificial intelligence in science and education. European Proceedings of Social and Behavioural Sciences, 2022, 1-9. https://doi.org/10.15405/epsbs.2022.03.28

Ju, Q. (2023). Experimental evidence on negative impact of generative AI on scientific learning outcomes. Duke University.

Park, J., Teo, T. W., Teo, A., Chang, J., Huang, J. S., & Koo, S. (2023). Integrating artificial intelligence into science lessons: Teachers’ experiences and views. International Journal of STEM Education, 10(1), 61. https://doi.org/10.1186/s40594-023-00454-3

ECD. (2023). Artificial intelligence in science: Challenges, opportunities and the future of research. OECD Publishing. https://doi.org/10.1787/a8d820bd-en

Gunawan, K. D. H., Liliasari, Kaniawati, I., & Setiawan, W. (2021). The responses to artificial intelligence in teacher integrated science learning training program. Journal of Physics: Conference Series, 2098, 012034. https://doi.org/10.1088/1742-6596/2098/1/012034

AlKanaan, H. M. N. (2022). Awareness regarding the implication of artificial intelligence in science education. International Journal of Instruction, 15(3), 901-910. https://doi.org/10.29333/iji.2022.15353a

Baum, D., Yu, X., Ayala, P. Y., Zhao, Y., Watkins, S. P., & Zhou, Q. (2021). The application of artificial intelligence (AI) to chemistry: Current trends and future directions. Journal of Chemical Information and Modeling, 61(7), 3197–3212. https://doi.org/10.1021/acs.jcim.1c00619

Akyüz, H. İ., & Erdemir, M. (2022). Preservice science teachers’ views of a web-based intelligent tutoring system. International Journal of Technology in Education, 5(1), 67-87. https://doi.org/10.46328/ijte.233

Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10001-2

Lee, I., & Perret, B. (2023). Preparing high school teachers to integrate AI methods into STEM classrooms. Education Development Center, Inc.

Mahmudah, R. (2023). Peluang dan tantangan penggunaan artificial intelligence dalam pembelajaran biokimia. Hybrid: Jurnal Pendidikan dan Pembelajaran Sains, 2(2), 20-29.

Taruklimbong, E. S. W., & Sihotang, H. (2023). Peluang dan tantangan penggunaan AI (Artificial Intelligence) dalam pembelajaran kimia. Jurnal Pendidikan Tambusai, 7(3), 26745-26757. https://doi.org/10.31237/osf.io/vpsjz

Zukorlić, M. S., & Pavlović, S. L. (2023). Student–teacher interaction. Zbornik Radova, 26(25), 183–198. https://doi.org/10.5937/ZRPFU2325159Z

Tisnés, H. M. (2023). Teacher-student interaction. INTERDISCIPLINARIA, 40(2), 23-40. https://doi.org/10.16888/interd.2023.40.2.2

Sukumaran, S., & Khair, N. S. (2024). Exploring the Role of AI Platforms in Improving English-Speaking Skills in Malaysian Higher Education Institutions. In Pedagogical Practices for Higher Education 4.0. Retrieved from Taylor & Francis.

Li, Z. (2024). Generative AI in Higher Education Academic Assignments: Policy Implications from a Systematic Review of Student and Teacher Perceptions. Retrieved from MIT DSpace.

Ramírez-Montoya, M. S., & Oliva-Córdova, L. M. (2023). Training Teaching Personnel in Incorporating Educational Perspectives on Artificial Intelligence. Proceedings of TEEM 2023. Retrieved from Google Books.

Downloads

Published

2024-10-21

How to Cite

Adli, M., Suriani, A. B., Ibrahim, M. M., Azzam, A. B., Fatiatun, Kusuma, H. H., Dwandaru, W. S. B., & Muhammad Dhanil. (2024). Comprehensive Review on Technology-Based Learning Using Artificial Intelligence for Science Subjects and Its Implications in Teaching and Learning. EDUCATUM Journal of Science, Mathematics and Technology, 11(2), 100–113. https://doi.org/10.37134/ejsmt.vol11.2.11.2024