Artificial Intelligence for Academic Research Assistance: An Empirical Study of Academic Users in Higher Institutions

Authors

  • Smita S. Patil
  • Pallavi D. Mundhe
  • Shankar H. Kadekar
  • Anil B. Alde
  • Syeda Sarwat Farheen
  • Swapna P. Gaikwad
  • Jayshila Khandare

Keywords:

Artificial Intelligence; Academic Research; Research Assistance; Technology Acceptance Model; AI Literacy; Higher Education; Generative AI; Research Ethics; User Acceptance

Abstract

Artificial Intelligence (AI) is increasingly used to support academic research through literature discovery, writing assistance, citation management, information retrieval, and data analysis support [1]–[4]. This study focuses on the awareness, usage, acceptance, perceived benefits, challenges, and training needs associated with AI-based research-assistance tools among academic users in the institutions of Latur district, Maharashtra, India. A descriptive and analytical research design was adopted, and a questionnaire substantially based upon the Technology Acceptance Model (TAM) was administered to 175 selected respondents through purposive and convenience sampling. Faculty members, postgraduate students, and research scholars were included in the respondent group. The paper illustrates a high level of awareness of mainstream tools, particularly ChatGPT (95.4%) and Grammarly (83.4%), whereas the use of several other research-specific tools appears to be under-recognized. According to the descriptive statistics, AI is primarily used for literature review, writing and editing, citation and referencing, and data analysis. Among user perception categories, perceived usefulness, perceived ease of use, and trust were identified as key adoption factors. In addition, the inadequate access to advanced tools, over-dependence, technical-skill gaps, difficulty interpreting AI outputs, privacy concerns, plagiarism risk, and insufficient training were also noted as critical adoption barriers. Hence, the study hypothesized that access to AI is not sufficient for academic users, and institutions should foster AI literacy, practical training, source verification, research-integrity guidance, and ethical governance to enable responsible adoption of AI in academic research. A five-layer responsible-adoption framework – Access, Literacy, Application, Verification, and Ethical Governance – was developed for this purpose.

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Published

2026-09-28

How to Cite

Patil, S. S., Mundhe, P. D., Kadekar, S. H., Alde, A. B., Farheen, S. S., Gaikwad, S. P., & Khandare, J. (2026). Artificial Intelligence for Academic Research Assistance: An Empirical Study of Academic Users in Higher Institutions . International Journal of Artificial Intelligence and Machine Learning, 6(12s), 677–685. Retrieved from https://www.svedbergopen.com/index.php/ijaiml/article/view/2465