Analyzing ChatGPT Impact on Student Productivity in Information Technology Program at Politeknik Negeri Tanah Laut
DOI:
https://doi.org/10.30865/json.v7i2.9495Keywords:
ChatGPT, Student Productivity, Artificial Intelligence, Information Technology, Higher EducationAbstract
The rapid development of generative artificial intelligence, particularly ChatGPT, has transformed the way students complete academic tasks, especially in the field of Information Technology. Despite its widespread adoption, concerns remain regarding its impact on students’ productivity and learning quality. This study aims to analyze the effect of ChatGPT usage on the productivity of students in the Information Technology Study Program at Politeknik Negeri Tanah Laut. A quantitative research approach with a survey method was employed. Data were collected through a Likert-scale questionnaire distributed to active students who had used ChatGPT for academic purposes. The collected data were analyzed using validity and reliability tests, followed by simple linear regression analysis to examine the effect of ChatGPT usage on student productivity. The results indicate that ChatGPT usage has a positive and significant effect on student productivity. Productivity improvements are mainly observed in task efficiency and timely task completion. However, the quality of academic outputs remains highly dependent on students’ ability to critically evaluate, verify, and further develop the outputs generated by ChatGPT. These findings suggest that ChatGPT functions effectively as an academic assistant rather than a substitute for critical thinking and independent learning. This study concludes that ChatGPT can be utilized as a supportive academic tool to enhance student productivity when used appropriately and responsibly, supported by adequate AI literacy and academic supervision. The findings are expected to provide empirical insights for higher education institutions in formulating policies and guidelines for the ethical and productive use of ChatGPT in academic activities.
References
S. Noy and W. Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science, vol. 381, no. 6654, pp. 187–192, 2023.
E. Brynjolfsson, D. Li, and L. Raymond, “Generative AI at Work,” Q. J. Econ., vol. 140, no. 2, pp. 889–942, 2025.
M. I. Baig et al., “ChatGPT in higher education: A systematic literature review,” Int. J. Educ. Res., 2024.
L. Labadze, M. Grigolia, and L. Machaidze, “Role of AI chatbots in education: A systematic literature review,” Int. J. Educ. Technol. High. Educ., vol. 20, no. 1, 2023.
M. Imran and N. Almusharraf, “ChatGPT as a writing assistant: A systematic review,” Contemp. Educ. Technol., vol. 15, no. 4, 2023.
Y. Y. Munaye et al., “ChatGPT in education: Opportunities and challenges,” Algorithms, vol. 18, no. 6, 2025.
T. Debets et al., “Chatbots in education: Impacts and challenges,” Comput. Educ., vol. 234, 2025.
S. A. Bin-Nashwan, M. Sadallah, and M. Bouteraa, “Use of ChatGPT in academia: Academic integrity hangs in the balance,” Technol. Soc., 2023.
J. Eaton, “Academic integrity in the age of artificial intelligence,” Educ. Rev., 2023.
D. Cotton, J. Cotton, and P. Shipway, “ChatGPT and assessment integrity,” Assess. Eval. High. Educ., 2024.
UNESCO, Guidance for Generative AI in Education and Research, Paris, 2023.
OECD, OECD Digital Education Outlook 2023, Paris, 2023.
A. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learn. Individ. Differ., 2023.
R. Bringula, “ChatGPT in a programming course: Benefits and limitations,” Front. Educ., 2024.
S. Malik et al., “Impact of generative AI tools on student creativity and teamwork,” Educ. Sci., vol. 16, no. 1, 2026.
S. Noy and W. Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science, vol. 381, no. 6654, pp. 187–192, 2023.
E. Brynjolfsson, D. Li, and L. Raymond, “Generative AI at Work,” The Quarterly Journal of Economics, vol. 140, no. 2, pp. 889–942, 2025.
L. Labadze, M. Grigolia, and L. Machaidze, “Role of AI chatbots in education: A systematic literature review,” Int. J. Educ. Technol. High. Educ., vol. 20, no. 1, 2023.
A. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol. 103, 2023.
M. Imran and N. Almusharraf, “Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review,” Contemporary Educational Technology, vol. 15, no. 4, 2023.
R. Bringula, “ChatGPT in a programming course: Benefits and limitations,” Frontiers in Education, 2024.
S. A. Bin-Nashwan, M. Sadallah, and M. Bouteraa, “Use of ChatGPT in academia: Academic integrity hangs in the balance,” Technology in Society, 2023.
D. Cotton, J. Cotton, and P. Shipway, “ChatGPT and assessment integrity in higher education,” Assessment & Evaluation in Higher Education, 2024.
UNESCO, Guidance for Generative AI in Education and Research, Paris, 2023.
OECD, OECD Digital Education Outlook 2023, Paris, 2023.
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