Preference for Open Access Resources and AI tools for academic research among postgraduate students in universities in Nigeria

to open access journals, and university management should support library users by developing an intrinsic drive for knowledge creation and publishing research output through internet subscriptions for use of open access journals. Toyo (2016) examined the relevance of the use of open access publications by undergraduate Library and Information Science Students in Delta State University, Abraka. Questionnaire was designed to elicit information from the respondents. The sample size for the study was 121 undergraduate LIS students which is 20% of the total population of 610. Findings revealed that undergraduate LIS students are aware of various open access publications which include theses and dissertations, electronic books, open access journals, conference papers, author personal websites amongst others; that open access is usually the first priority for undergraduate LIS students when sourcing for materials for assignments; LIS students make use of open access publications for their course works, to update their knowledge, to meet their research needs etc. Improvement in academic performance, personal growth, career development, easy accessibility and high-quality scholarly work are some of the benefits of using open access publications by undergraduate LIS students. Challenges such as retrieval of too much irrelevant information, inadequate skills to navigate the internet and lack of knowledge of the existence of open access publications, download delay and insufficient bandwidth were identified to militate against the use of open access publications by undergraduate LIS students. Giray, Canlas, Labanjo and Matiencio (2025) observed that AI is already influencing academic writing and research, improving efficiency in tasks like literature reviews and manuscript drafting. Artificial intelligence tools offer undeniable scholarly productivity benefits such as rapidly producing well-structured text, translating or summarising literature and serving as a conversational assistant during the writing process. According to the authors, students and researchers are using tools like ChatGPT as writing tutors, for brainstorming and even for generating early drafts of papers. These capabilities have prompted some educators to explore how AI might be constructively integrated into academic curricula. Kurniawan, Wahyuni, Sosang and Iryas (2026) investigated the role of Artificial Intelligence in modern academic research: a systematic review of contemporary literature (2015–2025). The study systematically mapped the contexts in which AI has been applied in modern academic research during 2015–2025 and examines how AI has influenced the process and outputs of educational research over the past decade. Findings from the study revealed that AI has been applied across a broad and continuously expanding range of academic contexts, including automated writing assessment, citation prediction, AI-generated instructional content, academic integrity evaluation and AI literacy development, with ChatGPT and similar LLMs serving as the primary catalysts of this expansion from 2022 onward. The influence of AI on educational research processes and outputs is simultaneously accelerative and disruptive. Findings from the study also revealed that while AI demonstrably enhances efficiency, consistency and productivity, it also poses serious threats to assessment integrity, authorship norms and equity of access, particularly for international students and institutions from the Global South. The study concluded that AI is not merely a technical tool but a transformative force that demands systemic, ethical and pedagogical responses across the entire academic ecosystem, including assessment redesign, integrated AI literacy curricula and the development of coherent global ethical governance frameworks for AI use in academic research. The study by Onobrakpor (2022) examined the extent of utilisation and satisfaction of open access resources by Postgraduate students of federal Universities in South South, Nigeria. Descriptive survey design was used, while the instrument for data collection was the questionnaire. The findings of the study revealed that M. Ed Postgraduate students of Federal Universities in South South, Nigeria utilised Open-Access e-resources to a high extent with a pooled mean of 2.56 while the PhD Postgraduate students utilised them to low extent with a pooled mean of 2.22. The finding also revealed that the level of satisfaction derived by both the M. Ed and PhD Postgraduate students of Federal Universities in South South, Nigeria on the use of Open-Access e-resources were all to high extent. The study recommended among other things that libraries should organise more awareness programme on the availability of Open Access resources and encourage students to use them. Dwivedi et. al. (2023) explored the opportunities, challenges and implications of generative AI (ChatGPT) from multidisciplinary perspectives for research, practice and policy. The study was a multidisciplinary opinion paper based on conceptual analysis and a review of perspectives from more than 80 scholars across fields such as management, education, health, and law. The study found that generative AI has had a substantial influence on research processes, including writing, analysis and literature review, as well as on academic outputs, but also poses serious challenges related to academic integrity, privacy, bias and trust. It highlighted the need for clear institutional policies and ethical guidelines for the use of AI in research and education. Feng, Zhu, Wu, Wei, Huang and Wang (2025) explored how Chinese postgraduate students view the benefits and risks of using AI for academic writing. The combined in-depth interviews with a large student survey to understand their choices. Students saw clear benefits which include AI can speed up academic writing, help with grammar and suggest ideas. But respondents also reported concerns. Two main risks stood out. Security risks (such as inaccurate or unreliable outputs) worried them more than privacy risks (such as data collection), because security problems directly threatened the quality of their work. Many students also expressed distrust, often based on past negative experiences, but this tended to affect their attitudes rather than directly stopping them from using AI. The survey confirmed these insights. Students’ attitudes, whether they felt positive or negative about AI were the strongest factor shaping their intention to use these tools. Perceived usefulness and supportive study conditions (like good internet access) encouraged adoption, while security concerns reduced trust and confidence. Overall, the study shows that students weigh the value of efficiency against the risks of reliability when deciding to use AI. These findings suggest that universities should provide clear guidance, technical support, and ethical safeguards to help students use AI responsibly and effectively in academic writing. Methodology The descriptive survey research design was adopted for the study. The population comprised 133 postgraduate students in three universities in Oyo State, Nigeria which are: University of Ibadan, Ibadan, Oyo State, Ladoke Akintola University of Technology, Ogbomoso and Lead City University, Challenge, Ibadan. Convenience sampling was used to achieve a sample of 133 postgraduate students in three universities in Oyo State. The questionnaire was the chief data collection instrument. Convenience sampling was adopted for the study as most postgraduate students were in their research project semester and were not always physically present in the university environment due to fieldwork, data collection, consultations with supervisors and other research-related activities. Consequently, the researchers relied on those students who were available and accessible at the time of data collection to ensure adequate participation and successful completion of the study. Data gathered was analysed using the Statistical Product and Service Solution software version 21. Demography of respondents and research questions was equally analysed with descriptive statistics, using the simple percentages, frequency count and standard deviation as well as correlating analysis. The analyses is presented in tables. Results Research Question 1: What are the types of artificial intelligence tools used for academic research among postgraduate students in universities in Oyo state, Nigeria? Table 1 Types of artificial intelligence tools used for academic research S/N Artificial intelligence tools used SA F % A F % D F % SD F % Mean SD 1 Semantic Scholar 77 57.9 22 16.5 28 21.1 6 4.5 3.28 .948 2 Scite 50 37.6 63 47.4 16 12.0 4 3.0 3.20 .763 3 Research Rabbit 96 72.2 21 15.8 12 9.0 4 3.0 3.57 .781 4 Perplexity AI 105 78.9 19 14.3 7 5.3 2 1.5 3.71 .637 5 Open AI (Chat GPT) 121 91.0 10 7.5 1 0.8 1 0.8 3.89 .402 6 Connected papers 74 55.6 40 30.1 15 11.3 4 3.0 3.38 .805 7 Grammarly 106 79.7 16 12.0 9 6.8 2 1.5 3.70 .663 8 Writefull 30 22.6 16 12.0 82 61.7 5 3.8 2.53 .884 9 Paperpal 49 36.8 17 12.8 62 46.6 5 3.8 2.83 .981 10 Quilbot 101 75.9 19 14.3 11 8.3 2 1.5 3.65 .698 11 Mendeley 80 60.2 36 27.1 13 9.8 4 3.0 3.44 .792 12 Elicit 97 72.9 12 9.0 19 14.3 5 3.8 3.51 .876 Key: Strongly Agree (SA), Agree (A), Disagree (D) and Strongly Disagree (SD) Findings from Table 1 showed that the most used AI tools by majority of the respondents were; Open AI (Chat GPT) (x̅=3.89), Perplexity AI (x̅=3.71), Grammarly (x̅=3.70), Quilbot (x̅=3.65) and Research Rabbit (x̅=3.57). On the other hand, the least used AI tools were; Writefull (x̅=2.53) and Paperpal (x̅=2.83). Research question 2: What is the frequency of artificial intelligence tools used for academic research among postgraduate students in universities in Oyo state, Nigeria? Table 2 Frequency of artificial intelligence tools used for academic research S/N Artificial intelligence tools used Daily F % Weekly F % Monthly F % Never F % Mean SD 1 Semantic Scholar 28 21.1 70 52.6 7 5.3 28 21.1 2.74 1.022 2 Scite 11 8.3 73 54.9 26 19.5 23 17.3 2.54 .875 3 Research Rabbit 46 34.6 57 42.9 11 8.3 19 14.3 2.98 1.004 4 Perplexity AI 98 73.7 12 9.0 10 7.5 13 9.8 3.47 .997 5 Open AI (Chat GPT) 122 91.7 9 6.8 1 0.8 1 0.8 3.89 .394 6 Connected papers 33 24.8 75 56.4 8 6.0 17 12.8 2.93 .906 7 Grammarly 60 45.1 53 39.8 11 8.3 9 6.8 3.23 .869 8 Writefull 13 9.8 28 21.1 8 6.0 84 63.2 1.77 1.091 9 Paperpal 24 18.0 34 25.6 7 5.3 68 51.1 2.11 1.220 10 Quilbot 96 72.2 14 10.5 9 6.8 14 10.5 3.44 1.011 11 Mendeley 6 4.5 76 57.1 27 20.3 24 18.0 2.48 .840 12 Elicit 9 6.8 94 70.7 5 3.8 25 18.8 2.65 .862 Weighted mean=2.85; Std. Dev.=0.92 Results on the frequency of use of AI tools revealed that most of the respondents 122 (91.7%) used Open AI (Chat GPT) on a daily basis. Others used daily were; Perplexity AI as indicated by the respondents 98 (73.7%) and Quilbot as noted by a notable number of the respondents 96 (72.2%). Majority of the respondents 94 (70.7%), 76 (57.1%) and 75 (56.4%) used Elicit, Mendeley and Connected Papers on a weekly basis respectively. The AI tools that were never used by most of the respondents 84 (63.2%) and 68 (51.1%) were Writefull and Paperpal (Table 2). Research Question 3: What are the types of open access resources used for academic research among postgraduate students in universities in Oyo state, Nigeria? Table 3 Types of open access resources used for academic research S/N Types of open access resources SA F % A F % SD F % D F % Mean SD 1 I use open access journal 91 68.4 37 27.8 2 1.5 3 2.3 3.62 .635 2 I use open access books 36 27.1 19 14.3 44 33.1 34 25.6 2.43 1.143 3 I consult e-databases 21 15.8 96 72.2 9 6.8 7 5.3 2.98 .663 4 I make use of electronic thesis and dissertations 21 15.8 73 54.9 38 28.6 1 0.8 2.86 .676 5 I visit open access website 17 12.8 97 72.9 17 12.8 2 1.5 2.97 .563 6 I consult open access software 12 9.0 33 24.8 65 48.9 23 17.3 2.26 .850 7 I use open access magazine/newspaper 10 7.5 26 19.5 31 23.3 66 49.6 1.85 .989 8 I consult e-proceedings 7 5.3 17 12.8 60 45.1 49 36.8 1.86 .833 9 I make use of e-reports 10 7.5 37 27.8 54 40.6 32 24.1 2.19 .889 10 I use search engines 108 81.2 14 10.5 3 4.0 7 5.3 3.68 .774 11 I use e-directories 15 11.3 18 13.5 32 24.1 68 51.1 1.85 1.041 12 I consult institutional repositories 96 72.2 22 16.5 10 7.5 5 3.8 3.57 .791 Key: Strongly Agree (SA), Agree (A), Disagree (D) and Strongly Disagree (SD) Table 3 showed that the most used open access resources were; search engines (x̅=3.68), open access journals (x̅=3.62), institutional repositories (x̅=3.57), e-databases (x̅=2.98) and open access websites (x̅=2.97). While the least used were; directories (x̅=1.85), open access magazines and newspapers (x̅=1.85), e-proceedings (x̅=1.86) and e-reports (x̅=2.19). Research question 4: What is the frequency of open access resources used for academic research among postgraduate students in universities in Oyo state, Nigeria? Table 4 Frequency of open access resources used for academic research S/N Frequency of use of open access resources D F % W F % M F % N F % Mean SD 1 I use open access journal 35 26.3 66 49.6 31 23.3 1 0.8 3.02 .728 2 I use open access books 15 11.3 21 15.8 16 12.0 81 60.9 1.77 1.084 3 I consult e-databases 15 11.3 18 13.5 93 69.9 7 5.3 2.31 .740 4 I make use of electronic thesis and dissertations 14 10.5 36 27.1 61 45.9 22 16.5 2.32 .874 5 I visit open access website 13 9.8 21 15.8 62 46.6 37 27.8 2.08 .910 6 I consult open access software 12 9.0 17 12.8 13 9.8 91 68.4 1.62 1.020 7 I use open access magazine/newspaper 11 8.3 16 12.0 9 6.8 97 72.9 1.56 .996 8 I consult e-proceedings 2 1.5 14 10.5 17 12.8 100 75.2 1.38 .736 9 I make use of e-reports 8 6.0 13 9.8 31 23.3 81 60.9 1.61 .895 10 I use search engines 92 69.2 32 24.1 6 4.5 3 2.3 3.60 .685 11 I use e-directories 2 1.5 14 10.5 18 13.5 99 74.4 1.39 .737 12 I consult institutional repositories 13 9.8 82 61.7 16 12.0 22 16.5 2.65 .872 Weighted mean=2.11; Std. Dev.=0.86 Key: Daily (D), Weekly (W). Monthly (M) and Never (N) Results in Table 4 revealed that the open access resources that were used daily by more than three-fifths of the respondents 92 (69.2%) were search engines. Majority of the respondents 82 (61.7%) and close to half 66 (49.6%) used institutional repositories and open access journals on a weekly basis. Electronic databases 93 (69.9%), open access websites 62 (46.6%) and e-theses and dissertations 61 (45.9%) were used monthly by most of the respondents. The open access resources that were never used by majority of the respondents 100 (75.2%), 99 (74.4%) and 97 (72.9%) were e-proceedings, e-directories and open access magazines and newspapers respectively. Discussion of Findings Based on the results from Table 2 and Table 4, respondents showed a greater preference for the use of AI tools (Weighted mean=2.85; Std. Dev.= 0.92) compared to open access resources (weighted mean=2.11; Std. Dev. = 0.86). This implies that AI tools were frequently used and relatively more preferred by the respondents, suggesting a shift towards AI-assisted research practices over open access resources. The difference of 0.74 in the weighted means indicates a statistically meaningful divergence in usage patterns, signaling a clear shift in the research behaviour of postgraduate students towards AI-assisted practices. This implies that AI tools were not only more frequently used but were also relatively more preferred by the respondents, suggesting a structural transition away from open access resources in everyday academic work. Kell, Kraeer and Cain (2025) described the experiences of students who used generative AI while writing their practice-based dissertations. The students found AI helpful for tasks such as refining research questions, generating example text and proofreading, essentially as a transformative support throughout the dissertation journey. A closer examination of the frequency data further reinforces this preference. In Table 2, Open AI (ChatGPT) was used daily by 122 (91.7%) of respondents, Perplexity AI by 98 (73.7%), and Quilbot by 96 (72.2%), yielding individual means of 3.89, 3.47, and 3.44 respectively. In contrast, Table 4 reveals that only search engines approached a comparable level of daily use among open access resources, with 92 (69.2%) of respondents engaging with them daily (mean=3.60). Other open access resources such as e-databases (mean=2.31), electronic theses and dissertations (mean=2.32), and open access websites (mean=2.08) were predominantly used on a monthly basis, reflecting lower engagement intensity. This pattern confirms that while certain open access resources remain in use, their frequency of access is considerably lower than that recorded for leading AI tools. The preference for AI tools over open access resources may be attributable to several factors. AI tools offer immediate, conversational and synthesised responses to research queries, reducing the time and effort required to locate, evaluate and interpret information from multiple open access sources. This corroborates Kurniawan, Wahyuni, Sosang and Iryas (2026) who investigated the role of Artificial Intelligence in modern academic research: a systematic review of contemporary literature (2015–2025). Findings from the study revealed that AI has been applied across a broad and continuously expanding range of academic contexts, including automated writing assessment, citation prediction and AI-generated instructional content, with ChatGPT and similar LLMs serving as the primary catalysts of this expansion from 2022 onward. Findings from the study also revealed that AI demonstrably enhances efficiency, consistency and productivity. Similarly, Anthony, Sharma and Sharma (2025) assessed scholars’ views on ChatGPT's efficiency, usefulness and effectiveness in academic research writing. The findings revealed that research scholars generally perceive ChatGPT as moderately effective and useful in academic writing The versatility of AI tools spanning literature discovery (Research Rabbit, Semantic Scholar), writing assistance (Grammarly, Quilbot) and citation management (Mendeley) positions them as comprehensive, one-stop platforms that rival the specialised functions of distinct open access resources. This assertion agrees with that of Hajkowicz et al. (2023) who opined that AI tools support a wide range of research activities, including automated data analysis, literature synthesis, AI-assisted academic writing and adaptive intelligent tutoring systems. This expansion reflects a fundamental methodological shift that not only improves research efficiency but also opens new forms of cross-disciplinary knowledge production. Artificial Intelligence tools also offer widespread and often unrestricted accessibility of tools such as ChatGPT and Perplexity AI increases high utilisation among postgraduates who may lack institutional access to premium open access resources or databases. Despite the overall preference for AI tools, it is noteworthy that certain open access resources maintained relatively strong engagement. Search engines, open access journals and institutional repositories recorded the highest means among open access resources, suggesting that respondents still value credible, peer-reviewed scholarly content. This indicates that AI tools and open access resources may function complementarily rather than mutually exclusive manner with AI tools facilitating rapid information retrieval and synthesis, while open access resources supply the authoritative academic content that underpins rigorous scholarly work. These findings have important implications for academic libraries and university administrators. The demonstrated preference for AI tools suggests that AI and information literacy programmes should be expanded to include ethical use and critical evaluation of AI- generated content alongside open access resource use. Postgraduate students need to be equipped with skills ethically use AI tools, identify the limitations of AI tools including risks of hallucination, lack of citation traceability and potential academic integrity concerns. These skills will also help them to judiciously use and appreciate the evidential rigour that peer-reviewed open access resources provide. Institutions should therefore adopt an integrated approach that promotes the ethical, judicious and informed use of both AI tools and open access resources as complementary components of a robust research practice. Conclusion AI tools were frequently used and relatively more preferred by the respondents, suggesting a shift towards AI-assisted research practices over open access resources. Respondents showed a greater preference for the use of AI tools compared to open access resources. Postgraduate students are increasingly integrating artificial intelligence tools into academic research activities, reflecting a significant transformation in contemporary research practices. The growing reliance on AI-driven platforms suggests that students value the speed, convenience and multifunctional capabilities these tools provide in supporting information discovery, writing and other research activities. Nevertheless, open access resources continue to play an essential role by providing credible, scholarly and authoritative information necessary for academic rigor. Recommendations Based on the findings of this study, the following recommendations are made: 1. Universities should promote the complementary use of AI tools and open access resources by encouraging postgraduate students to use AI technologies to complement, rather than completely replace credible information resources during research process. 2. Academic libraries should strengthen information and digital literacy programmes to equip postgraduate students with the skills required to effectively identify, access, use and manage open access resources and AI-generated information. 3. Universities should provide training on research, information retrieval and critical evaluation skills to enable postgraduate students to assess the accuracy, relevance, credibility and scholarly value of information obtained through AI tools and open access resources. 4. Universities should establish guidelines for the ethical and responsible use of AI tools in research, with emphasis on issues such as academic honesty, verification of AI-generated texts, data privacy and avoidance of plagiarism. References Amponsah, E., Madukoma, E. and Unegbu, V.E., 2021. Open Access Electronic Resources Use and Research Productivity of Faculty Members: A Case Study of a Selected University in Ghana. World Journal of Education, 11(6), pp.18-30. Anthony, A., Sharma, S. and Sharma, S., 2025. Is ChatGPT the future of academic writing? A sequential explanatory study to explore generative conversational AI as an academic writing support tool for research scholars. 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The Relevance of the Use of Open Access Publications by Undergraduates of Library and Information Science in Delta State University, Abraka. International Journal of Education and Evaluation, 22: 66-78