Articles
DOI DOI: 10.62441/actainnovations.v63i.1094

BEYOND THE HYPE: A SYSTEMATIC REVIEW OF CHATGPT'S AFFORDANCES AND CHALLENGES FOR FOSTERING BASIC EDUCATION SCIENCE PROCESS SKILLS

Prasart Nuangchalerm1, Titiworada Polyiem1, Veena Prachagool1, Lindelani Mnguni2
  1. 1 Faculty of Education, Mahasarakham University, Thailand.
  2. 2 Faculty of Education, University of Pretoria, South Africa.

Abstract

This study explores the use of ChatGPT for supporting science learning in basic education. A systematic review is employed based on the publications published in Scopus database which gathered data concerning published articles from 2023 to 2026. Eight papers were analyzed in a descriptive study. The process entailed documenting the essential attributes of each study, such as the authors, publication year, and key findings. The data were organized into an informative description and an analytical Table by the PRISMA. The results found that artificial intelligence enhances teaching and learning. ChatGPT supported students in science learning, and it can also promote problem-solving, communication skills, scientific inquiry, and personalized learning experiences. AI-supported environments can provide individualized learning pathways and facilitate inquiry-based learning.

How to Cite

Nuangchalerm, P., Polyiem, T., Prachagool, V., & Mnguni, L. (2026). BEYOND THE HYPE: A SYSTEMATIC REVIEW OF CHATGPT’S AFFORDANCES AND CHALLENGES FOR FOSTERING BASIC EDUCATION SCIENCE PROCESS SKILLS. ACTA INNOVATIONS, 63, 230–236. https://doi.org/10.62441/actainnovations.v63i.1094
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References

  1. 1. Altan, E. B., Coşkun, T. K., Öztürk, N., & Hacıoğlu, Y. (2025). Science teachers’ mentoring support experiences when integrating technology in design-based learning STEM activities. PLOS One, 20(9), e0332047. https://doi.org/10.1371/journal.pone.0332047
  2. 2. Asad, M. M., & Ajaz, A. (2024). Impact of ChatGPT and generative AI on lifelong learning and upskilling learners in higher education: Unveiling the challenges and opportunities globally. The International Journal of Information and Learning Technology, 41(5), 507-523. https://doi.org/10.1108/ijilt-06-2024-0103
  3. 3. Barrera Castro G. P., Chiappe A., Becerra Rodríguez D.F., Sepúlveda F. (2026). Artificial intelligence and learning gaps: Evaluating the effectiveness of personalized pathways. Applied Sciences, 16(3), 1302. https://doi.org/10.3390/app16031302
  4. 4. Buyel J.F. (2024). How digital transformation can influence workflows, teaching practices and curricula in (bio)process science and engineering-An interview series with stakeholders. Future in Educational Research, 2(3), 205-224. https://doi.org/10.1002/fer3.40
  5. 5. Chavez J. V., Cuilan J. T., Mannan S. S., Ibrahim N. U., Carolino A. A., Radjuni A., Albani S. E., & Garil B. A. (2024). Discourse analysis on the ethical dilemmas on the use of AI in academic settings from ICT, science, and language instructors. Forum for Linguistic Studies, 6(5), 349-363. https://doi.org/10.30564/fls.v6i5.6765
  6. 6. Fayzullina, A. R., Filippova, A. A., & Zaripova, Z. F. (2025). Artificial intelligence in science education: A systematic review of applications, impacts, and challenges. Contemporary Educational Technology, 17(4), ep613. https://doi.org/10.30935/cedtech/17519
  7. 7. Gandhi A., & Muldner K. (2026). Beyond verbal self-explanations: Student annotations of a code-tracing solution produced by ChatGPT. British Journal of Educational Technology, 57(1), 112-137. https://doi.org/10.1111/bjet.13600
  8. 8. Garzón, J., Eddy, P., & Camilo, M. (2025). Systematic review of artificial intelligence in education: Trends, benefits, and challenges. Multimodal Technologies and Interaction, 9(8), 84. https://doi.org/10.3390/mti9080084
  9. 9. Gizaw, G., & Sota, S. (2023). Improving science process skills of students: A review of literature. Science Education International, 34(3), 216-224. https://doi.org/10.33828/sei.v34.i3.5
  10. 10. Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
  11. 11. Halaweh, M. (2023). ChatGPT in education: Strategies for responsible implementation. Contemporary Educational Technology, 15(2), ep421. https://doi.org/10.30935/cedtech/13036
  12. 12. He, P., & Krajcik, J. (2026). Artificial intelligence in science education: Global insights and future directions. Disciplinary and Interdisciplinary Science Education Research, 8(1), 6. https://doi.org/10.1186/s43031-026-00154-2
  13. 13. Juntapan, S., & Nuangchalerm, P. (2025). In-service teachers’ perceptions of the nature of science in instructional contexts. Asian Journal of Education and Social Studies, 51(11), 616-622. https://doi.org/10.9734/ajess/2025/v51i112638
  14. 14. Kyambade, M., Namatovu, A., & Male Ssentumbwe, A. (2025). Exploring the evolution of artificial intelligence in education: From AI-guided learning to learner-personalized paradigms. Cogent Education, 12(1), 2505297. https://doi.org/10.1080/2331186x.2025.2505297
  15. 15. Lee, G., Yun, M., Zhai, X., & Crippen, K. (2026). Artificial intelligence in science education research: Current states and challenges. Journal of Science Education and Technology, 35(1), 110-127. https://doi.org/10.1007/s10956-025-10239-8
  16. 16. Legvart, P., Kordigel Aberšek, M., & Kerneža, M. (2022). Developing communication competence in digital learning environments for primary science students. Journal of Baltic Science Education, 21(5), 836-848. https://doi.org/10.33225/jbse/22.21.836
  17. 17. Lomkate, C., Phuaphuang, C., Sangjam, T., Chaimung, P., & Nuangchalerm, P. (2026). A Systematic review of AI-enhanced learning in science classrooms. Research and Development Journal Suan Sunandha Rajabhat University, 18(1), 1-14.
  18. 18. Luo Y. T., Liu T., Pang P., Mckay D., Chang S., & Buchanan G. (2026). Inquiry-based learning patterns in large language model-driven learning environments: An exploratory study from Bloom's perspective. Australasian Journal of Educational Technology, 42(1), 38-57. https://doi.org10.14742/ajet.10773
  19. 19. Mnguni, L., Nuangchalerm, P., Islami, R., Sibanda, D., Sari, I. J., & Ramulumo, M. (2024). The behavioural intentions for integrating artificial intelligence in science teaching among pre-service science teachers in South Africa and Thailand. Computers and Education: Artificial Intelligence, 7, 100334. https://doi.org/10.1016/j.caeai.2024.100334
  20. 20. Momani, M. A. K. A., Alharahasheh, K. A., & Alqudah, M. (2023). Digital learning in sciences education: A literature review. Cogent Education, 10(2), 2277007. https://doi.org/10.1080/2331186x.2023.2277007
  21. 21. Nuangchalerm, P., Prachagool, V., Saregar, A., & Yunus, Y. M. (2024). Fostering pre-service teachers’ AI literacy through school implications. Journal of Philology and Educational Sciences, 3(2), 77-86. https://doi.org/10.53898/jpes2024327
  22. 22. Ognibene D., Donabauer G., Theophilou E., Koyuturk C., Yavari M., Bursic S., Telari A., Testa A., Boiano R., Taibi D., Hernandez-Leo D., Kruschwitz U., & Ruskov M. (2025). Use me wisely: AI-driven assessment for LLM prompting skills development. Educational Technology and Society, 28(3), 184-201. https://doi.org/10.30191/ETS.202507_28(3).SP12
  23. 23. Paola, B. C. G., Andrés, C., Fernando, B. R. D., & Sepúlveda, F. (2026). Artificial intelligence and learning gaps: evaluating the effectiveness of personalized pathways. Applied Sciences, 16(3), 1302. https://doi.org/10.3390/app16031302
  24. 24. Pejman, E., Hoffmann, S., & Johannes, S. (2026). Opening the black box: How reasoning-enabled AI agents influence user perceptions and behavior in sustainable consumption. International Journal of Information Management, 90, 103075. https://doi.org/10.1016/j.ijinfomgt.2026.103075
  25. 25. Prachagool, V., Nuangchalerm, P., & Vetsawat, C. (2026). Teachers' attitude towards the instructional role of AI technologies. World Journal of Education, 16(1), 15-21. https://doi.org/10.5430/wje.v16n1p15
  26. 26. Rahayu, A. S., Hernawati, D., & Agustian, D. (2026). Enhancing science process skills and learning outcomes: The impact of ChatGPT-assisted inquiry learning on environmental change education. Bioeduca: Journal of Biology Education, 8(1), 72-86. https://doi.org/10.21580/bioeduca.v8i1.29538
  27. 27. Rajput, R. (2025). Use of artificial intelligence to solve problems in the classroom. In New Technological Applications in the Flipped Learning Model (pp. 137-168). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-0437-3.ch005
  28. 28. Ramaila, S., & Molwele, A. J. (2022). The role of technology integration in the development of 21st century skills and competencies in life sciences teaching and learning. International Journal of Higher Education, 11(5), 9-17.
  29. 29. Shofiyah, N., Jatmiko, B., Suprapto, N., Prahani, B. K., & Anggraeni, D. M. (2025). The use of technology to scientific reasoning in science education: A bibliometric and content analysis of research papers. Social Sciences & Humanities Open, 11, 101534.
  30. 30. https://doi.org/10.1016/j.ssaho.2025.101534
  31. 31. Suebsing, S., & Nuangchalerm, P. (2021). Understanding and Satisfaction towards STEM Education of Primary School Teachers through Professional Development Program. Jurnal Pendidikan IPA Indonesia, 10(2), 171–177. https://doi.org/10.15294/jpii.v10i2.25369
  32. 32. Yadav, S. (2025). Leveraging AI to enhance teaching and learning in education: The role of artificial intelligence in modernizing classroom practices. In Optimizing research techniques and learning strategies with digital technologies (pp. 211-238). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-7863-2.ch008
  33. 33. Yulianti, A., Andrijati, N., Wijayati, N., & Avrilianda, D. (2026). Elementary school students’ readiness to adopt artificial intelligence (AI)-based learning. Cybersecurity and Innovative Technology Journal, 4(1), 1-16. https://doi.org/10.53889/citj.v4i1.879