Exploring the Potential of ChatGPT to improve experiential learning in Education
Open accessAbstract
Artificial Intelligence (AI) is revolutionizing the field of education by offering new possibilities for personalized and experiential learning along with data-driven insights. The advancement in AI to Generative Artificial Intelligence (GAI) has made the tables turn notably in the field of education. Generative AI application tool ChatGPT is emerging as a game changer offering personalized learning experiences by analyzing huge amounts of student data, generating study materials and pacing to individual needs. Intelligent educational tools powered by AI provide personalized guidance and feedback, adapting to curriculum to address knowledge gaps. GAI also automates the grading process, providing instant feedback and relieving teachers for qualitative assessments. This research paper offers a thorough examination of the potential uses, advantages, difficulties, and moral issues related to implementing ChatGPT in educational contexts. The authors closely analyze how ChatGPT can improve educational experiences, assist personalized learning, and encourage student- teacher interaction, while exploring the drawbacks of using generative AI models in education, such as concerns about bias, data privacy, and over-reliance on technology. This research article intends to offer educators & academicians useful insights into the usage of ChatGPT in the educational field through a critical analysis of the existing literature and real- world experiences.
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In the Academic context, support for planning processes is typically intended to help users connect and structure their own ideas to accomplish complex tasks.
“Support for planning processes are typically intended to help users connect and structure their own ideas to accomplish complex tasks [103,126].”
From Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process (2025) · cites this paper as [103]
The Literature Review mentions chatbots helping manage projects, and Results and Discussion describes ChatGPT fostering discussion and critical thinking. Neither section addresses whether academic planning support is intended to help users connect and structure their own ideas to accomplish complex tasks. Searches for planning processes and organizing ideas found no passage establishing that point. (LLM, conf=0.72)
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What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · see citing works
Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-022-00362-6 · Cited by 428 · see citing works
ChatGPT for Education and Research: A Review of Benefits and Risks
Sok, S., & Heng, K. (2023) · doi:10.2139/ssrn.4378735 · Cited by 386 · see citing works
Sallam, M., Salim, N., Barakat, M., & Al-Tammemi, A. (2023) · Narra J · doi:10.52225/narra.v3i1.103 · Cited by 331 · see citing works
How Chat GPT Can Transform Autodidactic Experiences and Open Education?
Firat, M. (2023) · doi:10.31219/osf.io/9ge8m · Cited by 280 · see citing works
Will ChatGPT get you caught? Rethinking of Plagiarism Detection
Khalil, M., & Er, E. (2023) · doi:10.35542/osf.io/fnh48 · Cited by 259 · see citing works
Kumar, J. A. (2021) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-021-00302-w · Cited by 183 · see citing works
Flagged first, then by citations
Research works printed but not linked: 10
- D Mhlanga, Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning. Education, SSRN Journal, (2, 2023).
- G Eysenbach, The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers. JMIR Medical Education, 9(1), 2023.
- D Baidoo-Anu & L Owusu Ansah, Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. Available at SSRN Journal (2023).
- Zhuo, T. Y., Huang, Y., Chen, C., & Xing, Z, Exploring ai ethics of ChatGPT: A diagnostic analysis.arXiv preprint arXiv:2301.12867(2023). · arXiv
- Ray, Partha Pratim. "ChatGPT: A comprehensive review on background, appli- cations, key challenges, bias, ethics, limitations and future scope. " Internet of Things and Cyber-Physical Systems (2023).
- Rahman, M. M., &Watanobe, Y.,ChatGPT for education and research: Opportuni- ties, threats, and strategies. Applied Sciences, (2023),13(9), 5783.
- Biswas, Som. "Role of Chat GPT in Education. " Available at SSRN 4369981 (2023).
- Suryawanshi R., Rawat S., Singh C., Sammangi H., Akram S.V., Chakravarthi M.K. "Implementation and Enabling Artificial Intelligence in Wireless Communication Networks" (2023) Proceedings of the 17th INDIACom; 2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023, pp. 1325 -1329
- Malik P., Singh A.K., Nautiyal R., Rawat S. "Mapping AICTE cybersecurity cur- riculum onto CyBOK: A case study" (2022) Machine Learning for Cyber Security, pp. 129 -143
- Kukreti A., Painolli A.K., Rana N. "Where do we stand: factors affecting sus- tainable development" (2021) Procedia Environmental Science, Engineering and Management, 8 (2), pp. 583 -589
Cited by
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Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process
Reza, M., Thomas-Mitchell, J., Dushniku, P., Laundry, N., Williams, J. J., & Kuzminykh, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757566 · Cited by 37 · see citing works
- Authors
- Rawat, S., Mittal, S., Nehra, D., Sharma, C., & Kamboj, D.
- Affiliations
- Maharishi Markandeshwar University, Mullana (IN)
- Venue
- Proceedings of the 5th International Conference on Information Management & Machine Intelligence
- Publisher
- ACM
- Published
- 2023-11-23
- Pages
- 1-8
- OpenAlex
- W4396852874
- Cited by
- 7
- References
- 7
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1
- FWCI
- 1.80
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Information Management & Machine Intelligence (ICIMMI) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- ChatGPT, generative AI in education, experiential learning, personalized learning, automated grading, student-teacher interaction, data privacy, algorithmic bias, technology dependence
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