The role of generative AI search tools in educational research productivity among early-career scholars: A mediation-based multi-method study
DOI:
https://doi.org/10.64268/inspire.v1i2.73Keywords:
Generative AI Search Tools, Educational Research, Early-Career Scholars, Mediation Model, Multi-Method ApproachAbstract
Background: Generative AI search tools has transformed how researcher access, interpret, and synthesize academic literature. For early-career scholars, these technologies offer potential support in addressing limitations related to research experience, particularly in literature comprehension and conceptual framework development. However, empirical studies explaining how and through what internal mechanisms generative AI supports educational research remain limited, especially those that account for psychological and cognitive mediating factors.
Aims: This study aims to examine the role of generative AI search tools in enhancing educational research productivity among early-career scholars by analyzing the mediating roles of academic self-confidence, literature comprehension, and research self-regulation.
Methods: A mediation-based multi-method approach with an explanatory sequential design was employed. Quantitative data were collected through a Likert-scale survey and analyzed using mediation modeling, followed by qualitative data collected through semi-structured interviews and analyzed thematically to elaborate and contextualize the quantitative findings.
Result: The findings indicate that the use of generative AI search tools is positively associated with educational research productivity. This relationship is primarily mediated by literature comprehension, academic self-confidence, and research self-regulation, with literature comprehension emerging as the strongest mediating pathway. Qualitative findings further reveal that generative AI functions as an intellectual companion that supports understanding of complex scholarly literature, strengthens research independence, and facilitates more effective management of the research process.
Conclusion: The study demonstrates that the contribution of generative AI to educational research extends beyond technical assistance, operating through researchers’ internal cognitive and psychological processes. By adopting a mediation-based perspective, this study provides a more nuanced explanation of how generative AI search tools support early-career scholars’ research productivity and contributes to a deeper theoretical understanding of AI-supported educational research practices.
References
Al Shloul, T., Mazhar, T., Abbas, Q., Iqbal, M., Ghadi, Y. Y., Shahzad, T., Mallek, F., & Hamam, H. (2024). Role of activity-based learning and ChatGPT on students’ performance in education. Computers and Education: Artificial Intelligence, 6, 100219.
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
Baskara, F. R., Puri, A. D., & Wardhani, A. R. (2023). ChatGPT and the pedagogical challenge: Unveiling the impact on early-career academics in higher education. Indonesian Journal on Learning and Advanced Education (IJOLAE), 311–322.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Brown, R., Sillence, E., & Branley-Bell, D. (2025). AcademAI: Investigating AI usage, attitudes, and literacy in higher education and research. Journal of Educational Technology Systems, 54(1), 6–33. https://doi.org/10.1177/00472395251347304
Cabrera-Arnau, C. (2024). Understanding student perceptions on the use of generative AI tools in UK higher education. OSF.
Cabuquin, J. C., Acidre, M. A. S., Manabat, M. A. A., Aruta, M. G. H., Sangutan, J., & Yu, R. F. B. (2024). The role of ChatGPT on academic research: Perspectives from Filipino students across diverse educational levels. Salud, Ciencia y Tecnología – Serie de Conferencias, 3, 1205.
Castillo-Segura, P., Alario-Hoyos, C., Kloos, C. D., & Panadero, C. F. (2023). Leveraging the potential of generative AI to accelerate systematic literature reviews: An example in the area of educational technology. In Proceedings of the 2023 World Engineering Education Forum–Global Engineering Deans Council (WEEF-GEDC) (pp. 1–8). IEEE. https://ieeexplore.ieee.org/abstract/document/10344098
Choe, K., Park, S., Jung, S., Kim, H., Yang, J. W., Hong, H., & Seo, J. (2024). Supporting novice researchers to write literature review using language models. In Extended abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–9). https://doi.org/10.1145/3613905.3650787
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.
Dai, Y., Lai, S., Lim, C. P., & Liu, A. (2023). ChatGPT and its impact on research supervision: Insights from Australian postgraduate research students. Australasian Journal of Educational Technology, 39(4), 74–88.
DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed.). SAGE.
Elkhodr, M., & Gide, E. (2025). Generative artificial intelligence empowered learning: A new frontier in educational technology. CRC Press.
Fauzi, C., Rahmani, E. F., & Utimadini, N. J. (2025). Beyond technology acceptance: An interplay of self-efficacy, language proficiency, and ChatGPT adoption from a TAM perspective. Jurnal Pendidikan Progresif, 15(3), 1970–1988.
Fenske, R. F., & Otts, J. A. A. (2024). Incorporating generative AI to promote inquiry-based learning: Comparing Elicit AI research assistant to PubMed and CINAHL Complete. Medical Reference Services Quarterly, 43(4), 292–305. https://doi.org/10.1080/02763869.2024.2403272
Franzoni Velázquez, A. L., Huerta, E., & Jensen, S. (2024). Retracting ChatGPT: Completeness and relevance of academic references. Discover Education, 3(1), 226. https://doi.org/10.1007/s44217-024-00333-1
Gáspár, T. (2023). Literacy for the future: Lessons from foresight case studies. https://publikaciotar.uni-bge.hu/id/eprint/2200/
Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis (2nd ed.). Guilford Press.
Întorsureanu, I., Oprea, S.-V., Bâra, A., & Vespan, D. (2025). Generative AI in education: Perspectives through an academic lens. Electronics, 14(5), 1053.
Kallio, H., Pietilä, A.-M., Johnson, M., & Kangasniemi, M. (2016). Systematic methodological review: Developing a framework for a qualitative semi-structured interview guide. Journal of Advanced Nursing, 72(12), 2954–2965.
Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge University Press.
Kumar, S., & Gunn, A. (2025). Doctoral students’ reflections on generative artificial intelligence (GenAI) use in the literature review process. Innovations in Education and Teaching International, 62(4), 1395–1408. https://doi.org/10.1080/14703297.2024.2427049
Mhlanga, D. (2024). Generative AI for emerging researchers: The promises, ethics, and risks. https://www.researchgate.net/profile/David-Mhlanga-2/publication/379291767
Nguyen-Trung, K., Saeri, A. K., & Kaufman, S. (2024). Applying ChatGPT and AI-powered tools to accelerate evidence reviews. Human Behavior and Emerging Technologies, 2024(1), 8815424. https://doi.org/10.1155/2024/8815424
Оliinyk, I., Bulavina, O., Romanenko, T., Tatarnikova, A., & Smirnov, A. (2024). Artificial intelligence in developing doctoral students’ research competencies. Revista Eduweb, 18(3), 294–305.
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health, 42(5), 533–544.
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). SAGE.
Putri, F. R., & Iswati, H. D. (2025). A qualitative exploration of students’ use of Humata AI to understand thesis literature: A cognitive load perspective. Wiralodra English Journal, 9(2), 166–179.
Shen, X., & Tao, Y. (2025). Metacognitive strategies, AI-based writing self-efficacy, and writing anxiety in AI-assisted writing contexts: A structural equation modeling analysis. International Journal of TESOL Studies, 7(1).
Suárez-Pizzarello, M., Sánchez-Trujillo, M. D. L. A., & Flores, E. A. R. (2024). Exploring ChatGPT-4 as an academic assistant in thesis development: A case study on postgraduate higher education. In Proceedings of the 2024 IEEE 4th International Conference on Advanced Learning Technologies on Education & Research (ICALTER) (pp. 1–4). https://ieeexplore.ieee.org/abstract/document/10819226
Suprobo, W., & Basuki, S. (2024). A systematic literature review: Impact of generative AI as technology to learning in higher education. Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika, 10(2), 135–142.
Tashakkori, A., & Teddlie, C. (2010). Mixed methodology: Combining qualitative and quantitative approaches. SAGE.
Wang, C., Chen, X., Hu, Z., Jin, S., & Gu, X. (2025). Deconstructing university learners’ adoption intention towards AIGC technology: A mixed-methods study using ChatGPT as an example. Journal of Computer Assisted Learning, 41(1), e13117. https://doi.org/10.1111/jcal.13117
Wang, X., Liu, Q., Pang, H., Tan, S. C., Lei, J., Wallace, M. P., & Li, L. (2023). What matters in AI-supported learning: A study of human–AI interactions in language learning using cluster analysis and epistemic network analysis. Computers & Education, 194, 104703.
Yuan, S., & Lipizzi, C. (2025). AI-augmented literature reviews: Efficient clustering and summarization for researchers. IEEE Access. https://ieeexplore.ieee.org/abstract/document/11142702
Zhang, X., Zhang, P., Shen, Y., Liu, M., Wang, Q., Gašević, D., & Fan, Y. (2024). A systematic literature review of empirical research on applying generative artificial intelligence in education. Frontiers of Digital Education, 1(3), 223–245. https://doi.org/10.1007/s44366-024-0028-5
Zhou, X., Teng, D., & Al-Samarraie, H. (2024). The mediating role of generative AI self-regulation on students’ critical thinking and problem-solving. Education Sciences. https://qmro.qmul.ac.uk/xmlui/handle/123456789/101889
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70.
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