Exploring the Potential of ChatGPT: The AI Revolution in Human and Technology Interaction

Authors

  • Cucu Atikah Universitas Sultan Ageng Tirtayasa Serang, Banten, Indonesia
  • Wawan Hendrawan Universitas Sultan Ageng Tirtayasa Serang, Banten, Indonesia
  • Rudi Haryadi Universitas Sultan Ageng Tirtayasa Serang, Banten, Indonesia

DOI:

https://doi.org/10.35445/alishlah.v17i3.7028

Keywords:

ChatGPT, Adaptive Learning, Tutor Virtual, Education

Abstract

Artificial intelligence (AI), particularly large language models like ChatGPT, is rapidly transforming educational practices. ChatGPT offers new opportunities for enhancing self-directed learning and personalized instruction, yet empirical studies on its effectiveness remain limited. This study employed a mixed-methods approach, combining a systematic literature review (SLR) with a quasi-experimental design involving 36 high school students. Participants completed pretests and posttests measuring conceptual understanding, and a perception survey was administered to assess student experiences using ChatGPT as a virtual tutor. Quantitative findings revealed a significant improvement in learning outcomes, with posttest scores increasing by 15.5 points on average compared to pretest scores. Survey results showed that 89% of students reported improved comprehension of difficult concepts through interactions with ChatGPT. Students also noted increased motivation for independent learning and appreciated the immediate feedback provided by the AI tool, which helped accelerate task completion. The findings suggest that ChatGPT can serve as an effective supplementary learning tool, especially in supporting self-paced learning. However, critical challenges—such as AI bias, data privacy concerns, and limited technological access in remote areas—must be addressed to ensure equitable adoption. ChatGPT holds strong potential to enhance educational outcomes and promote more inclusive learning environments. Future research should explore culturally adaptive implementations, teacher training, and ethical safeguards to maximize its effectiveness in diverse educational contexts.

References

Ahmad, S. F., Han, H., Alam, M. M., Rehmat, M. K., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness and safety in education. Humanities and Social Sciences Communications, 10(1), 1–14. https://doi.org/10.1057/s41599-023-01787-8

Alafnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses. Journal of Artificial Intelligence and Technology, 3(2), 60–68. https://doi.org/10.37965/jait.2023.0184

Alves de Castro, C. (2023). A Discussion about the Impact of ChatGPT in Education: Benefits and Concerns. Journal of Business Theory and Practice, 11(2), p28. https://doi.org/10.22158/jbtp.v11n2p28

Borkowski, A. A. (2023). Applications of ChatGPT and Large Language Models in Medicine and Health Care: Benefits and Pitfalls. Federal Practitioner, 40(6), 170–173. https://doi.org/10.12788/fp.0386

Cao, Y., Zhou, L., Lee, S., Cabello, L., Chen, M., & Hershcovich, D. (2023). Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study. Cross-Cultural Considerations in NLP at EACL, C3NLP 2023 - Proceedings of the Workshop, 53–67. https://doi.org/10.18653/v1/2023.c3nlp-1.7

Chang, J., Park, J., & Park, J. (2023). Using an Artificial Intelligence Chatbot in Scientific Inquiry: Focusing on a Guided-Inquiry Activity Using Inquirybot. In Asia-Pacific Science Education (Vol. 2, Issue 2). https://doi.org/10.1163/23641177-bja10062

Christophe, F. T. J., Bernard, B. B., Henri, M. M., Adeline, O. S., Fabrice, N. T., Roger, D. T. D., & Raymon, P. P. (2023). Thematic Approach of the Competition for Entrance to the First Year of the Secondary Level in the Cameroonian Education System. Asian Journal of Education and Social Studies, 46(1), 55–64. https://doi.org/10.9734/ajess/2023/v46i1996

Eze, C., R C Nurse, J., & Jassim, H. (2018). Kent Academic Repository. Computers in Human Behavior, 2, 197–206.

Ferrara, E. (2023). Challenges and risks of bias in large language models. ArXiv.

Friederici, A. D., Steinhauer, K., & Pfeifer, E. (2002). Brain signatures of artificial language processing: Evidence challenging the critical period hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 99(1), 529–534. https://doi.org/10.1073/pnas.012611199

Jentzsch, S., & Kersting, K. (2023). ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Ml, 325–340. https://doi.org/10.18653/v1/2023.wassa-1.29

Karakose, T. (2023). The Utility of ChatGPT in Educational Research-Potential Opportunities and Pitfalls. Educational Process: International Journal, 12(2), 7–13. https://doi.org/10.22521/edupij.2023.122.1

KATAR, O., ÖZKAN, D., -3, G., YILDIRIM, Ö., & ACHARYA, U. R. (2023). Evaluation of GPT-3 AI Language Model in Research Paper Writing. Turkish Journal of Science and Technology, 18(2), 311–318. https://doi.org/10.55525/tjst.1272369

Khalil, F., & Pipa, G. (2022). Transforming the generative pretrained transformer into augmented business text writer. Journal of Big Data, 9(1). https://doi.org/10.1186/s40537-022-00663-7

Lo, C. K. (2023). What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Sciences, 13(4). https://doi.org/10.3390/educsci13040410

Luo, R., Sun, L., Xia, Y., Qin, T., Zhang, S., Poon, H., & Liu, T. Y. (2022). BioGPT: generative pre-trained transformer for biomedical text generation and mining. Briefings in Bioinformatics, 23(6), 1–12. https://doi.org/10.1093/bib/bbac409

Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI Chatbots for Content and Language Integrated Learning. Applied Sciences (Switzerland), 12(7). https://doi.org/10.3390/app12073239

Mattas, P. S. (2023). ChatGPT: A Study of AI Language Processing and its Implications. International Journal of Research Publication and Reviews, 04(02), 435–440. https://doi.org/10.55248/gengpi.2023.4218

Mendoza, S., Sánchez-adame, L. M., Urquiza-yllescas, J. F., González-beltrán, B. A., & Decouchant, D. (2024). Learning Process. 1–21.

Neji, W., Boughattas, N., & Ziadi, F. (2023). Exploring New AI-Based Technologies to Enhance Students’ Motivation. Issues in Informing Science and Information Technology, 20, 095–110. https://doi.org/10.28945/5149

Neo, M., Lee, C. P., Tan, H. Y. J., Neo, T. K., Tan, Y. X., Mahendru, N., & Ismat, Z. (2022). Enhancing Students’ Online Learning Experiences with Artificial Intelligence (AI): The MERLIN Project. International Journal of Technology, 13(5), 1023–1034. https://doi.org/10.14716/ijtech.v13i5.5843

Nguyen, V. T., & Nguyen, C. T. H. (2023). The Effect of Structural Equation Modeling on Chatbot Usage: An Investigation of Dialogflow. IJAIT (International Journal of Applied Information Technology), 06(01), 38. https://doi.org/10.25124/ijait.v6i01.4840

Olsina, L., Becker, P., Peppino, D., & Tebes, G. (2019). Specifying the Process Model for Systematic Reviews: An Augmented Proposal. Journal of Software Engineering Research and Development, 7(2007), 7. https://doi.org/10.5753/jserd.2019.460

Parra, C. M., Gupta, M., & Dennehy, D. (2021). Likelihood of Questioning AI-Based Recommendations Due to Perceived Racial/Gender Bias. IEEE Transactions on Technology and Society, 3(1), 41–45. https://doi.org/10.1109/tts.2021.3120303

Prabhakaran, V., Qadri, R., & Hutchinson, B. (2022). Cultural Incongruencies in Artificial Intelligence. http://arxiv.org/abs/2211.13069

Qasem, F., Ghaleb, M., Mahdi, H. S., Al Khateeb, A., & Al Fadda, H. (2023). Dialog chatbot as an interactive online tool in enhancing ESP vocabulary learning. Saudi Journal of Language Studies, 3(2), 76–86. https://doi.org/10.1108/sjls-10-2022-0072

Rodríguez-Oramas, A., Alvarez, P., Ramis-Salas, M., & Ruiz-Eugenio, L. (2021). The Impact of Evidence-Based Dialogic Training of Special Education Teachers on the Creation of More Inclusive and Interactive Learning Environments. Frontiers in Psychology, 12(March). https://doi.org/10.3389/fpsyg.2021.641426

Rogozinska, E., Gargon, E., Olmedo-Requena, R., Asour, A., Cooper, N. A. M., Vale, C. L., & Hooft, J. V. t. (2020). Methods used to assess outcome consistency in clinical studies: A literature-based evaluation. PLoS ONE, 15(7 July 2020), 1–12. https://doi.org/10.1371/journal.pone.0235485

Saxena, A. (2022). AI-Based Chatbot. December.

Thirunavukarasu, A. J. (2023). Large language models will not replace healthcare professionals: curbing popular fears and hype. Journal of the Royal Society of Medicine, 116(5), 181–182. https://doi.org/10.1177/01410768231173123

Waheed, N., Ikram, M., Hashmi, S. S., He, X., & Nanda, P. (2022). An Empirical Assessment of Security and Privacy Risks of Web-Based Chatbots. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13724 LNCS, 325–339. https://doi.org/10.1007/978-3-031-20891-1_23

Zhou, L., & Li, J. (2023). The Impact of ChatGPT on Learning Motivation: A Study Based on Self-Determination Theory. Education Science and Management, 1(1), 19–29. https://doi.org/10.56578/esm010103

Zhu, C., & Wang, M. (2023). How to harness the potential of ChatGPT in education ? Recommended citation : Zhu , C ., Sun , M ., Luo , J ., Li , T ., & Wang , M . ( 2023 ). How to harness the How to harness the potential of ChatGPT in education ? Chenjia Zhu Jiutong Luo Tianyi Li Min. 15(2), 133–152.

Downloads

Published

2025-09-30

How to Cite

Atikah, C., Hendrawan, W., & Haryadi, R. (2025). Exploring the Potential of ChatGPT: The AI Revolution in Human and Technology Interaction. AL-ISHLAH: Jurnal Pendidikan, 17(3), 4869–4878. https://doi.org/10.35445/alishlah.v17i3.7028

Issue

Vol. 17 No. 3 (2025): SEPTEMBER 2025

Section

Articles

Citation Check

License

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.