Volume 02, Issue 9
Published on: September 2026
AN ANALYSIS OF ARTIFICIAL INTELLIGENCE TOOLS USED BY DATA SCIENCE STUDENTS
Sujal Prashant Bhingawade
Kandivali Education Society’s BK Shroff College of Arts and MH Shroff College of Commerce (Autonomous)
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Abstract
This research paper discusses the use of Artificial Intelligence (AI) tools by Data Science students and examines their applications, benefits and challenges in academic learning. Artificial Intelligence is playing a growing role in modern technology in education, particularly in Data Science, where students regularly work with programming, data analysis, problem-solving and research activities. The availability of AI-based tools such as ChatGPT, Gemini, Claude and GitHub Copilot has provided students with new ways to understand concepts, generate ideas, write and explain code, identify programming errors, conduct research and improve their academic productivity.
The research focuses on understanding how Data Science students use different AI tools according to their academic requirements and the purposes for which these tools are preferred. It covers applications such as coding assistance, debugging, learning technical concepts, generating examples, research support, data-related problem-solving and content preparation. The study also examines the benefits of using AI tools, including faster access to information, learning support, improved productivity and assistance in understanding complex topics. Along with these benefits, the research considers challenges such as inaccurate or misleading information, limitations in understanding context, overdependence on AI-generated solutions and reduced involvement in independent thinking. The study further focuses on the academic and ethical concerns related to the use of AI tools. Excessive or inappropriate use of AI-generated content may raise concerns regarding academic integrity, originality, authorship, privacy and responsible use of technology. For this reason, it is important to understand how these tools should be used responsibly.AI tools is important to maintain a balance between technological assistance and students' own learning and skills. This study follows a descriptive research approach and is based on secondary data collected from research papers, journals, academic publications and reliable online sources. Overall, the research aims to provide an understanding of the growing use of AI tools among Data Science students, their applications, benefits and limitations, while highlighting the importance of responsible and effective use of AI in Data Science education.
Keywords: Artificial Intelligence, AI Tools, Data Science Students, AI in Education, Generative AI, ChatGPT, Google Gemini, Claude, GitHub Copilot, AI Coding Tools, AI Research Tools, Machine Learning, Data Analysis, Academic Learning, Student Productivity, AI-Assisted Learning, Academic Integrity, Ethical AI, Responsible AI, AI Dependence, AI Limitations
The research focuses on understanding how Data Science students use different AI tools according to their academic requirements and the purposes for which these tools are preferred. It covers applications such as coding assistance, debugging, learning technical concepts, generating examples, research support, data-related problem-solving and content preparation. The study also examines the benefits of using AI tools, including faster access to information, learning support, improved productivity and assistance in understanding complex topics. Along with these benefits, the research considers challenges such as inaccurate or misleading information, limitations in understanding context, overdependence on AI-generated solutions and reduced involvement in independent thinking. The study further focuses on the academic and ethical concerns related to the use of AI tools. Excessive or inappropriate use of AI-generated content may raise concerns regarding academic integrity, originality, authorship, privacy and responsible use of technology. For this reason, it is important to understand how these tools should be used responsibly.AI tools is important to maintain a balance between technological assistance and students' own learning and skills. This study follows a descriptive research approach and is based on secondary data collected from research papers, journals, academic publications and reliable online sources. Overall, the research aims to provide an understanding of the growing use of AI tools among Data Science students, their applications, benefits and limitations, while highlighting the importance of responsible and effective use of AI in Data Science education.
Keywords: Artificial Intelligence, AI Tools, Data Science Students, AI in Education, Generative AI, ChatGPT, Google Gemini, Claude, GitHub Copilot, AI Coding Tools, AI Research Tools, Machine Learning, Data Analysis, Academic Learning, Student Productivity, AI-Assisted Learning, Academic Integrity, Ethical AI, Responsible AI, AI Dependence, AI Limitations
How to Cite this Paper
Bhingawade, S. P. (2026). An Analysis of Artificial Intelligence Tools Used by Data Science Students. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(9), 1-9. https://doi.org/10.55041/ijcope.v2i9.237
Bhingawade, Sujal. "An Analysis of Artificial Intelligence Tools Used by Data Science Students." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 9, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i9.237.
Bhingawade, Sujal. "An Analysis of Artificial Intelligence Tools Used by Data Science Students." International Journal of Creative and Open Research in Engineering and Management 02, no. 9 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i9.237.
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References
- · Almasri, Firas. “Exploring the Impact of Artificial Intelligence in Teaching and Learning of Science: A Systematic Review of
- Empirical Research.” Research in Science Education, vol. 54, 2024, pp. 977–997.
- https://link.springer.com/article/10.1007/s11165-024-10176-3
- Chan, Cecilia Ka Yuk, and Wenjie Hu. “Students’ Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education.” International Journal of Educational Technology in Higher Education, vol. 20, article 43, 2023. https://link.springer.com/article/10.1186/s41239-023-00411-8
- Baig, Maria Ijaz, and Elaheh Yadegaridehkordi. “ChatGPT in Higher Education: A Systematic Literature Review and Research Challenges.” International Journal of Educational Research, vol. 127, 2024, article 102411. https://www.sciencedirect.com/science/article/pii/S088303552400 0971
- Browning, Jonathan W., John Bustard, Neil Anderson, and Leo Galway. “A Data Science Course Utilizing GenAI.” Queen’s University Belfast, https://pure.qub.ac.uk/en/publications/a-data-science-course-utilizing-genai/
- Letteri, Ivan, and Pierpaolo Vittorini. “Enhancing Student Feedback in Data Science Education: Harnessing the Power of AI-Generated Approaches.” International Journal of Artificial Intelligence in Education, vol. 35, 2025, pp. 3071–3094. https://link.springer.com/article/10.1007/s40593-025-00492-8
- · Kohen-Vacs, Dan, Maya Usher, and Marc Jansen. “Integrating Generative AI into Programming Education: Student
- Perceptions and the Challenge of Correcting AI Errors.” International Journal of Artificial Intelligence in Education, vol. 35, 2025, pp. 3166–3184.
- https://link.springer.com/article/10.1007/s40593-025-00496-4
- Gardella, Nicholas, Raymond Pettit, and Sara L. Riggs. “Performance, Workload, Emotion, and Self-Efficacy of Novice Programmers Using AI Code Generation.” Proceedings of the 2024 ACM Conference on Innovation and Technology in Computer Science Education, 2024, pp. 290–
- 296.https://doi.org/10.1145/3649217.3653615
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- •Peer Review Type: Double-Blind Peer Review
- •Published on: Sep 30 2026
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