Generative Artificial Intelligence's Integration for Data Analysis in Conducting Academic Research: Understanding the Perspective of Research Supervisors
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| Title: | Generative Artificial Intelligence's Integration for Data Analysis in Conducting Academic Research: Understanding the Perspective of Research Supervisors |
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| Language: | English |
| Authors: | Amandeep Sehmi (ORCID |
| Source: | Journal of Advanced Academics. 2025 36(4):788-815. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 28 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Technology Integration, Data Analysis, Educational Research, Higher Education, Ethics, Supervisors, Research Methodology, Graduate Students, Student Research, Foreign Countries |
| Geographic Terms: | Australia |
| DOI: | 10.1177/1932202X251365312 |
| ISSN: | 1932-202X 2162-9536 |
| Abstract: | This special issue article explores the role of generative artificial intelligence (GenAI) in the data analysis phase of academic research degrees, focusing on its adoption by research students in master's and doctor of philosophy programmes in the business and management disciplines, as viewed through the lens of research supervisors. A qualitative research methodology was adopted, involving semi-structured interviews with research supervisors. The findings revealed that while current familiarity with the use of GenAI tools for data analysis is limited among research supervisors, there is a growing recognition of their potential value and anticipated future acceptance in academic research. The findings of this study recommend the integration of GenAI training modules into research degrees. Furthermore, this study serves as a guide for future research studies exploring the role of GenAI in the data analysis processes of academic research. This study proposes guidelines to raise awareness and educate research students on the ethical use of GenAI, aiming to maintain integrity and enabling them to understand the scope and potential of emerging technologies for data analysis. Emphasising the ethical integration of GenAI, the enhancement of critical thinking, and the development of clear institutional policies are identified as key strategies to support the responsible use of GenAI in research and education. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1485752 |
| Database: | ERIC |
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| Abstract: | This special issue article explores the role of generative artificial intelligence (GenAI) in the data analysis phase of academic research degrees, focusing on its adoption by research students in master's and doctor of philosophy programmes in the business and management disciplines, as viewed through the lens of research supervisors. A qualitative research methodology was adopted, involving semi-structured interviews with research supervisors. The findings revealed that while current familiarity with the use of GenAI tools for data analysis is limited among research supervisors, there is a growing recognition of their potential value and anticipated future acceptance in academic research. The findings of this study recommend the integration of GenAI training modules into research degrees. Furthermore, this study serves as a guide for future research studies exploring the role of GenAI in the data analysis processes of academic research. This study proposes guidelines to raise awareness and educate research students on the ethical use of GenAI, aiming to maintain integrity and enabling them to understand the scope and potential of emerging technologies for data analysis. Emphasising the ethical integration of GenAI, the enhancement of critical thinking, and the development of clear institutional policies are identified as key strategies to support the responsible use of GenAI in research and education. |
|---|---|
| ISSN: | 1932-202X 2162-9536 |
| DOI: | 10.1177/1932202X251365312 |
