Analysis the Flexibility of ChatGPT Use in Chemistry Learning Among 12th Grade Students at Senior High School in Samarinda

Frederich Pakaenoni, Usman Usman, Agung Rahmadani, Sudjanani Ulfa, Kevin Tiurma Dame

Abstract


The rapid development of artificial intelligence has influenced learning practices in chemistry, particularly through the use of ChatGPT as an adaptive learning tool. This study aims to explore how students interpret the flexibility of ChatGPT in supporting chemistry learning, focusing on flexibility of time, place, learning pace, interaction, and adaptation to individual needs. The study employed a qualitative research design with a phenomenological approach to capture students lived experiences in using ChatGPT during chemistry learning. Participants consisted of 122 twelfth grade students from SMAN 5 Samarinda and SMAK Sunodia Samarinda who actively used ChatGPT in their chemistry studies. Data were collected through open-ended questionnaires distributed via Google Forms. Data analysis followed the interactive qualitative analysis model of Miles, Huberman, and Saldaña, which includes data condensation, data display, and conclusion drawing or verification. The findings reveal that students perceive ChatGPT as a flexible learning facilitator that allows learning anytime and anywhere, supports self paced learning, enables repeated explanation without pressure, and provides dialogic and responsive interaction tailored to individual understanding levels. ChatGPT also helps students regulate their learning, maintain learning continuity, and create a psychologically safe learning environment. Overall, ChatGPT is interpreted not as a replacement for teachers, but as a complementary learning support that enhances student independence, self-regulated, and conceptual understanding in chemistry. These results highlight the potential role of ChatGPT in supporting adaptive, personalized, and student centered chemistry learning.

Keywords


Artificial Intelligence; ChatGPT; Chemistry Learning; Flexibility; Qualitative Study

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References


Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), 1–13. https://doi.org/10.30935/cedtech/13152

Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 1–24. https://doi.org/10.1186/s41239-021-00282-x

Creswell, J. W., & Poth, C. N. (2016). Qualitative inquiry and research design: Choosing among five approaches. Sage Publications.

Crompton, H., & Burke, D. (2020). Mobile learning and pedagogical opportunities: A configurative systematic review of PreK-12 research using the SAMR framework. Computers & Education, 156, 103945. https://doi.org/https://doi.org/10.1016/j.compedu.2020.103945

Faza, A., & Lestari, I. A. (2025). Self-Regulated Learning in the Digital Age: A Systematic Review of Strategies, Technologies, Benefits, and Challenges. The International Review of Research in Open and Distributed Learning, 26(2), 23–58. https://doi.org/10.19173/irrodl.v26i2.8119

Hastuti, P., Rahmawati, U. E., Sakkinah, I. S., Arief Pratama, R., Hasanah, Q., Yunita, T., & Wulandari, L. (2025). Adaptive E-Learning: A systematic review of interactive and flexible learning aligned with student styles. International Journal of Studies in Social Sciences and Humanities IJOSSH, 2(2), 66–73. https://doi.org/10.25047/ijossh.v2i2.5588

Holmes, W. (2020). Artificial intelligence in education. In Encyclopedia of Education and Information Technologies (pp. 88–103). Springer International Publishing.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274–102285. https://doi.org/https://doi.org/10.1016/j.lindif.2023.102274

Kassab, S. E., Rathan, R., Taylor, D. C. M., & Hamdy, H. (2024). The impact of the educational environment on student engagement and academic performance in health professions education. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-06270-9

Luckin, R., Holmes, W., Griffiths, M., & Pearson, L. B. F. (2016). Intelligence Unleashed An argument for AI in Education. Pearson.

Mahmudah, R. (2023). Dalam Pembelajaran Biokimia. Jurnal Pendidikan Dan Pembelajaran, 2(2), 20–29. https://doi.org/https://doi.org/10.51574/hybrid.v2i2.1361

Martin, F., & Borup, J. (2022). Online learner engagement: Conceptual definitions, research themes, and supportive practices. Educational Psychologist, 57(3), 162–177. https://doi.org/https://doi.org/10.1080/00461520.2022.2089147

Mayer, R. E. (2024). The Past, Present, and Future of the Cognitive Theory of Multimedia Learning. Educational Psychology Review, 36(1), 1–25. https://doi.org/10.1007/s10648-023-09842-1

Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). Sage Publications.

Nursafitri, R., & Munajat, N. (2025). Penggunaan Teknologi Chatgpt Terhadap Efisiensi Penyelesaian Tugas Karya Ilimiah di Kalangan Mahasiswa (Mahasiswa UIN Sunan Kalijaga). Pendas: Jurnal Ilmiah Pendidikan Dasar, 10(01), 86–98. https://doi.org/https://doi.org/10.23969/jp.v10i01.23347

Ocak, C., Kopcha, T. J., & Dey, R. (2023). An AI-enhanced pattern recognition approach to temporal and spatial analysis of children’s embodied interactions. Computers and Education: Artificial Intelligence, 5, 100146. https://doi.org/https://doi.org/10.1016/j.caeai.2023.100146

Prastika, N. D., Anjarwati, D., Awaliah, M. A. S., Hartandi, D., Rahmadani, A., & Erika, F. (2024). Kajian Literatur Pemanfaatan Teknologi Artificial Intelligence untuk Meningkatkan Keterampilan Abad 21 Siswa dalam Pembelajaran Kimia. Jambura Journal of Educational Chemistry, 6(1), 47–60. https://doi.org/10.37905/jjec.v6i1.23644

Qudratuddarsi, H., Agung, A., & Yanti, M. (2025). “Status Quo” ChatGPT Dalam Pengajaran dan Pembelajaran Fisika: systematic literature review. phydagogic : Jurnal Fisika Dan Pembelajarannya, 7(2), 111–118. https://doi.org/10.31605/phy.v7i1.4645

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/https://doi.org/10.31004/jptam.v7i3.11167

Turan, Z., Kucuk, S., & Cilligol Karabey, S. (2022). The university students’ self-regulated effort, flexibility and satisfaction in distance education. International Journal of Educational Technology in Higher Education, 19(1), 1–19. https://doi.org/10.1186/s41239-022-00342-w

Urbina, S., Villatoro, S., & Salinas, J. (2021). Self-regulated learning and technology-enhanced learning environments in higher education: A scoping review. Sustainability (Switzerland), 13(13), 1–12. https://doi.org/10.3390/su13137281

Yaseen, H., Mohammad, A. S., Ashal, N., Abusaimeh, H., Ali, A., & Sharabati, A. A. A. (2025). The Impact of Adaptive Learning Technologies, Personalized Feedback, and Interactive AI Tools on Student Engagement: The Moderating Role of Digital Literacy. Sustainability (Switzerland), 17(3), 1–27. https://doi.org/10.3390/su17031133

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Zhai, X. (2023). ChatGPT User Experience: Implications for Education. Journal of the Association for Information Science and Technology, 3(01), 1–18. https://orcid.org/0000-0003-4519-1931




DOI: https://doi.org/10.37905/jjec.v8i2.37894

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