Generative AI and ChatGPT
in Industry and Education: Perspectives from Students, Educators and Industry Leaders
Manisha M More* and Shivaji Bothe**
Abstract
This research study investigates the perspectives of educators, industry leaders, and students on Generative AI technology, particularly ChatGPT. It addresses a research gap in understanding the varied attitudes and experiences associated with the technology. The motivation for this study stems from the need to explore the implications of Generative AI for education and industry. Using a mixed method approach, qualitative and quantitative data were gathered from 30 educators, 40 business executives, and 108 students of the total 178 samples through structured questionnaires. The data were analyzed using Natural Language Processing and Machine Learning to classify positive, negative, or neutral perceptions. Power BI and Python Programming were used for quantitative analysis. The findings reveal insights into the technology’s strengths and weaknesses, adoption purposes, challenges, and integration benefits, with significant implications for personalized learning and professional use. This study contributes uniquely to the field by offering a comprehensive understanding of the benefits, limitations, and future potential of Generative AI, aiming to disseminate the best practices for responsible integration.
Key words
Generative AI, ChatGPT, Natural language processing, Sentiment analysis, Perception analysis
Author Biography
Manisha M More*
Sr. Assistant Professor, School of Computer Studies, Sri Balaji University, Pune , Maharashtra.
E-mail:
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Shivaji Bothe**
Asst. Professor, School of Computer Studies , Sri Balaji University, Pune, Maharashtra.
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REFERENCES
- Aydin, O., & Karaarslan, E. (2023).Is ChatGPT leadinggenerating AI? What is beyond expectations? Academic Platform Journal of Engineering and Smart Systems, 11(3), 118-134.
- Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran,J. R., Boselie, P., & Cooke, F. L. (2023,July 10). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal.
- Chan,C. K. Y., & Hu,W. (2023). Students’voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, ArticleNo. 43, July.
- Conroy, G. (2023). Scientists used ChatGPT to generate an entire paper from scratch, but is there any good news about nature? Nature, July 7.
- Cress, U., & Kimmerle, J. (2023). Co-constructing knowledge with generative AI tools:Reflections from a CSCL perspective. International Journal of Computer Supported Collaborative Learning, October 20.
- De Silva, D., Mills, N., EI-Ayoubi, M., Manic, M., & Alahkoon, D. (2023). ChatGPT and generative AI guidelines for addressing academic integrity and augmenting pre-existing chatbots. IEEE International Conference on Industrial Technology (ICIT). IEEE Xplore, June 9.
- Dempere, J., Modugu, K., Allam, H., & Kumar, L. (2023). Impact of ChatGPTon higher education: A systematic review. Frontiers in Education, September 8.
- Devika, P., & Sandhya, S. (2024). Technical and scale efficiency of inpatient services in district hospitals in Kerala during 2014-2019. South Asian Journal of Management, 31(2), 2024.
- Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghvan,V., Ahuja, M., & Albanna, H. (2023). Opinion paper—So what if ChatGPT wroteit: Multidisciplinary perspectives on opportunities, challenges,and implications of generative AI for research, practice,and policy. International Journal of Information Management, 71(August), 102642.
- Eke,D. O. (2023). ChatGPT and the rise of generative AI: Threat to academicintegrity? Journal of Responsible Technology, February.
- Garrido-Merchan, E. C. (2023). Best uses of ChatGPT and generative AI for computer science research, CornellUniversity, November18.
- Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26-29.
- Lund, B. D., Wang, T., Mannuru,N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and new academic reality: AI-written research papers and ethics of large language models in scholarly publishing. Journal of the Association for Information Science and Technology. Available at SSRN, March 15.
- Mishra, P. K., Bardhan,A., & Das, A. (2024). Predicting scheduled block time (SBT) of airlines:A case study. South Asian Journal of Management, 30(5), 2023.
- Nah, F. F.-H., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, July, 227-304.
- Pramod, K., Mishra, Amit, Bardhan., & Amit, Das. (2024, June). Predicting scheduled block time (SBT) of airlines: A case study, South Asian Journal of Management, 30(5),205-230.
- Rohan,R., Dutsinma, L. I., Puapholthep, K., & Pal, D. (2023). Unlocking the black box: Exploring the use of generative AI (ChatGPT) in information systems research. Proceedings ofthe 13th International Conferenceon Advances in InformationTechnology, ACM Digital Library, 13, Article No. 17, December, 1-9.
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