ChatGPT in STEM Classrooms: Students’ Perceptions of Interest, Academic Proficiency, and Learning Independence
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Purpose of the study: To provide K-12 evidence from a low- and middle-income context, this study examines how basic education STEM students use ChatGPT and how it relates to their interest, academic proficiency, and learning independence.
Methodology: Design: descriptive cross-sectional survey in one large public school. Participants: 186 Grade 11–12 STEM students. Instrument: 17-item researcher-developed questionnaire, administered online during class. Tool: ChatGPT (OpenAI). Analysis: item-level frequencies and percentages; reliability and validity checks treated as supportive for a heterogeneous instrument.
Main Findings: ChatGPT use was episodic and concentrated in Research and English. Students reported greater engagement, clearer understanding, and shorter assignment time. Independence gains were modest; textbook reliance declined while tutoring reliance was largely stable. Governance practices were common, including verification and paraphrase-synthesis or inspirational use. Older students emphasized efficiency and integration; younger students reported larger conceptual gains.
Novelty/Originality of this study: This study contributes classroom-proximate, item-level evidence from Philippine basic education, an underrepresented K-12 setting. It characterizes selective, front-end deployment and widespread verification, offering rubric-ready handles for responsible use. It identifies grade-linked orchestration differences and connectivity-aware implications that can guide targeted scaffolds to translate efficiency into competence and independent learning.
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How to cite
[1]“ChatGPT in STEM Classrooms: Students’ Perceptions of Interest, Academic Proficiency, and Learning Independence”, J. Bs. Edu. R, vol. 6, no. 3, pp. 470–480, Sep. 2025, doi: 10.37251/jber.v6i3.2096. -
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- F. Miao and W. Holmes, Guidance for Generative AI in Education and Research. Paris, France: UNESCO, 2023.
- OECD, Education Policy Outlook 2024: Reshaping Teaching into a Thriving Profession—from ABCs to AI. Paris, France: OECD Publishing, 2024.
- OECD, “What should teachers teach and students learn in a future of powerful AI?,” OECD Education Spotlights, no. 20, 2025, doi:10.1787/ca56c7d6-en. DOI: https://doi.org/10.1787/ca56c7d6-en
- Department of Education (DepEd), “K to 12 Senior High School—Applied Track Subject: English for Academic and Professional Purposes (Curriculum Guide),” 2013.
- Department of Education (DepEd), “K to 12 Senior High School—Applied Track Subject: Practical Research 1 (Curriculum Guide),” 2013.
- World Bank, Better Internet for All Filipinos: Reforms Promoting Competition and Increasing Investment for Broadband Infrastructure (Policy Note), 2024.
- World Bank, “Unlocking the Philippines’ digital transformation by increasing internet connectivity,” 2025.
- E. L. Deci and R. M. Ryan, “The ‘what’ and ‘why’ of goal pursuits: Human needs and the self-determination of behavior,” Psychological Inquiry, vol. 11, no. 4, pp. 227–268, 2000, doi:10.1207/S15327965PLI1104_01. DOI: https://doi.org/10.1207/S15327965PLI1104_01
- S. Hidi and K. A. Renninger, “The four-phase model of interest development,” Educational Psychologist, vol. 41, no. 2, pp. 111–127, 2006, doi:10.1207/s15326985ep4102_4. DOI: https://doi.org/10.1207/s15326985ep4102_4
- E. Panadero, “A review of self-regulated learning: Six models and four directions for research,” Frontiers in Psychology, vol. 8, Art. 422, 2017, doi:10.3389/fpsyg.2017.00422. DOI: https://doi.org/10.3389/fpsyg.2017.00422
- A. A. Funa and R. A. E. Gabay, “Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study,” Social Sciences & Humanities Open, vol. 11, p. 101221, 2025, doi: 10.1016/j.ssaho.2024.101221. DOI: https://doi.org/10.1016/j.ssaho.2024.101221
- A. A. Funa and R. A. E. Gabay, “Exploring perspectives toward artificial intelligence integration in science education: A cross-generational study,” SSRN preprint, 2025, doi:10.2139/ssrn.5243807. DOI: https://doi.org/10.2139/ssrn.5240513
- Ofcom, “Children and parents: Media use and attitudes report 2024,” Apr. 19, 2024. [Online]. Available: https://www.ofcom.org.uk/siteassets/resources/documents/research-and-data/media-literacy-research/children/children-media-literacy-report-2024/childrens-media-literacy-report-2024.pdf
- R. Deng, “Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies,” Computers & Education, vol. 207, p. 105224, 2024, doi:10.1016/j.compedu.2024.105224. DOI: https://doi.org/10.1016/j.compedu.2024.105224
- J. Wang, Y. Liu, and X. Zhang, “The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: A meta-analysis,” Humanities and Social Sciences Communications, vol. 12, p. 399, 2025, doi:10.1057/s41599-025-04787-y. DOI: https://doi.org/10.1057/s41599-025-04787-y
- L. Casal-Otero, A. Catala, C. Fernández-Morante, M. Taboada, B. Cebreiro, and S. Barro, “AI literacy in K–12: A systematic literature review,” International Journal of STEM Education, vol. 10, p. 29, 2023, doi: 10.1186/s40594-023-00418-7. DOI: https://doi.org/10.1186/s40594-023-00418-7
- J. H. Kaufman, A. Woo, J. Eagan, S. Lee, and E. B. Kassan, Uneven Adoption of Artificial Intelligence Tools Among U.S. Teachers and Principals in the 2023–2024 School Year, RR-A134-25. Santa Monica, CA, USA: RAND Corporation, 2025, doi:10.7249/RRA134-25. DOI: https://doi.org/10.7249/RRA134-25
- O. Sidoti, E. Park, and J. Gottfried, “About a quarter of U.S. teens have used ChatGPT for schoolwork—double the share in 2023,” Pew Research Center, Jan. 15, 2025.
- J. W. Creswell and J. D. Creswell, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5th ed. Thousand Oaks, CA, USA: SAGE Publications, 2018.
- E. von Elm, D. G. Altman, M. Egger, S. J. Pocock, P. C. Gøtzsche, and J. P. Vandenbroucke, “The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies,” PLoS Medicine, vol. 4, no. 10, e296, 2007, doi:10.1371/journal.pmed.0040296. DOI: https://doi.org/10.1371/journal.pmed.0040296
- D. F. Polit and C. T. Beck, “The content validity index: Are you sure you know what’s being reported?,” Research in Nursing & Health, vol. 29, no. 5, pp. 489–497, 2006, doi:10.1002/nur.20147. DOI: https://doi.org/10.1002/nur.20147
- R. F. DeVellis and C. T. Thorpe, Scale Development: Theory and Applications, 4th ed. Thousand Oaks, CA, USA: SAGE Publications, 2016.
- G. F. Kuder and M. W. Richardson, “The theory of the estimation of test reliability,” Psychometrika, vol. 2, no. 3, pp. 151–160, 1937, doi:10.1007/BF02288391. DOI: https://doi.org/10.1007/BF02288391
- A. Agresti, Analysis of Ordinal Categorical Data, 2nd ed. Hoboken, NJ, USA: John Wiley & Sons, 2010, doi:10.1002/9780470594001. DOI: https://doi.org/10.1002/9780470594001
- M. S. Setia, “Methodology Series Module 3: Cross-sectional studies,” Indian Journal of Dermatology, vol. 61, no. 3, pp. 261–264, 2016, doi:10.4103/0019-5154.182410. DOI: https://doi.org/10.4103/0019-5154.182410
- A. A. Funa, “Digital badges as rewards in science education: Students’ perceptions and experiences,” Dalat University Journal of Science, vol. 14, no. 2, pp. 107–127, 2024, doi:10.37569/dalatuniversity.14.2.1212(2024). DOI: https://doi.org/10.37569/DalatUniversity.14.2.1212(2024)
- S. Noy and W. Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science, vol. 381, no. 6654, pp. 187–192, 2023, doi:10.1126/science.adh2586. DOI: https://doi.org/10.1126/science.adh2586
- A. A. Funa, L. S. Roleda, and M. S. Prudente, “Integrated science, technology, engineering, and mathematics—problem-based learning—education for sustainable development (I-STEM-PBL-ESD) framework,” in A Diversity of Pathways Through Science Education, Singapore: Springer Nature Singapore, 2024, pp. 151–172, doi:10.1007/978-981-97-2607-3_9. DOI: https://doi.org/10.1007/978-981-97-2607-3_9
- H. S. Almarashdi and A. Jaber, “Unveiling the potential: A systematic review of ChatGPT in transforming mathematics teaching and learning,” EURASIA Journal of Mathematics, Science and Technology Education, vol. 20, no. 12, em2555, 2024, doi:10.29333/ejmste/15739. DOI: https://doi.org/10.29333/ejmste/15739
- D. Ravšelj, D. Keržič, N. Tomaževič, et al., “Higher education students’ perceptions of ChatGPT: A global study of early reactions,” PLOS ONE, vol. 20, no. 2, e0315011, 2025, doi:10.1371/journal.pone.0315011. DOI: https://doi.org/10.1371/journal.pone.0315011
- L. Huang, W. Yu, W. Ma, et al., “A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,” ACM Computing Surveys, 2025, doi:10.1145/3703155. DOI: https://doi.org/10.1145/3703155
- M. T. H. Chi and R. Wylie, “The ICAP framework: Linking cognitive engagement to active learning outcomes,” Educational Psychologist, vol. 49, no. 4, pp. 219–243, 2014, doi:10.1080/00461520.2014.965823. DOI: https://doi.org/10.1080/00461520.2014.965823
- J. Hattie and H. Timperley, “The power of feedback,” Review of Educational Research, vol. 77, no. 1, pp. 81–112, 2007, doi:10.3102/003465430298487. DOI: https://doi.org/10.3102/003465430298487
- R. A. E. Gabay, A. A. Funa, and J. D. Ricafort, “Generative Artificial Intelligence (GenAI) for Academic Writing in Higher Education: A scoping review of applications, challenges, and implications,” Research Square, preprint, Aug. 26, 2025, doi:10.21203/rs.3.rs-7440784/v1. DOI: https://doi.org/10.21203/rs.3.rs-7440784/v1
- A. A. Funa, E. C. B. Deblois, L. D. Lerios, F. G. J. Jetomo, and R. A. E. Gabay, “Exploring Filipino preservice teachers’ online self-regulated learning skills and strategies amid the COVID-19 pandemic,” Social Sciences & Humanities Open, vol. 7, no. 1, p. 100470, 2023, doi:10.1016/j.ssaho.2023.100470. DOI: https://doi.org/10.1016/j.ssaho.2023.100470
- M. A. Largo, T. M. Sederia, F. C. Villadores, and M. Andrada, “Smart chat, bright minds: Does ChatGPT propel students to academic heights?,” Journal of Education and Learning Advancements, vol. 1, no. 1, pp. 8–21, 2024. [Online]. Available: https://jelamagste.org/journalofed/index.php/jela/article/view/14
- A. A. Funa and R. A. E. Gabay, “Bridging the gap among knowledge, attitudes, and behaviors toward sustainable development through I-STEM-PBL-ESD,” International Journal on Studies in Education, vol. 7, no. 2, pp. 288–303, 2025, doi:10.46328/ijonse.317. DOI: https://doi.org/10.46328/ijonse.317
- A. A. Funa, R. A. E. Gabay, K. A. Esdicul, and M. S. Prudente, “Secondary teachers’ and students’ perceptions of distance education in science: Focus on learner-centered, action-oriented, and transformative learning,” Dalat University Journal of Science, vol. 13, no. 3, pp. 156–181, 2023, doi:10.37569/DalatUniversity.13.3.1108(2023). DOI: https://doi.org/10.37569/DalatUniversity.13.3.1108(2023)
- B. J. Zimmerman, “Becoming a self-regulated learner: An overview,” Theory Into Practice, vol. 41, no. 2, pp. 64–70, 2002, doi:10.1207/s15430421tip4102_2. DOI: https://doi.org/10.1207/s15430421tip4102_2
- N. L. Mediana Jr., A. A. Funa, and R. V. Dio, “Effectiveness of inquiry-based learning (IbL) on improving students’ conceptual understanding in science and mathematics: A meta-analysis,” International Journal of Education in Mathematics, Science and Technology, vol. 13, no. 2, pp. 532–552, 2025, doi:10.46328/ijemst.4769. DOI: https://doi.org/10.46328/ijemst.4769
- J. M. Ramallosa, A. A. Funa, A. T. Geron, R. T. Ibardaloza, and M. S. Prudente, “Meta-analysis on the effectiveness of argument-based learning on students’ conceptual understanding,” in Proc. 13th Int. Conf. E-Education, E-Business, E-Management and E-Learning (IC4E), 2022, pp. 315–323, doi:10.1145/3514262.3514305. DOI: https://doi.org/10.1145/3514262.3514305