Promise and Perils of Artificial Intelligence in Educational Research: An Exploratory Study of Doctoral Scholars’ Perspectives

Authors

  • S. Brindha Devi Department of Education, Alagappa University, Karaikudi. Tamil Nadu, India https://orcid.org/0009-0008-5856-7153
  • R. Ramnath Department of Education, Alagappa University, Karaikudi. Tamil Nadu, India

DOI:

https://doi.org/10.22159/ijoe.2026v14i2.58384

Keywords:

artificial intelligence, educational research, doctoral scholars, interpretative phenomenological analysis, ethical concerns, research practices

Abstract

Artificial intelligence (AI) is playing an important role across academia, especially in research. While some technical aspects of this AI have been studied and discussed in prior research, relatively little is known about its use by doctoral students in the Indian context and how they perceive or utilise it, especially where access to resources and professional training is limited. The present study tries to address this research gap by phenomenologically exploring the real-time experience of doctoral researchers in Tamil Nadu, India. Based on the Technology Acceptance Model (TAM) and its later revisions, TAM2 and TAM3, and the constructs of these models, theoretically and conceptually align with scholars' experiences and perspectives. Interpretive phenomenological analysis was used to systematically collect and analyse data to discover the study's scientific findings. The study identified seven main themes from the perceptions of 11 doctoral participants regarding AI in research. The finding is a mixed response from the participants. Ethical concerns, capacity building, and institutional supports are highlighted.

Downloads

Download data is not yet available.

References

Reference

Ali, I., Warraich, N. F., & Butt, K. (2024). Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction. Information Development, 41(3), 859-874. https://doi.org/10.1177/02666669241257206

Aljarrah, E., Elrehail, H., &Aababneh, B. (2016). E-voting in Jordan: Assessing readiness and developing a system. Computers in Human Behavior, 63, 860–867. https://doi.org/10.1016/j.chb.2016.05.076

Almogren AS &Aljammaz NA (2022). The integrated social cognitive theory with the TAM model: The impact of M-learning in King Saud University art education. Front. Psychol. 13:1050532. doi: 10.3389/fpsyg.2022.1050532

Altwairesh, R., & Aloud, M. (2021). Mobile payments from merchants' perspective: an empirical study using the TAM model in Saudi Arabia. International Journal of Computer Science & Network Security, 21(8), 317-326.

Annamalai, N., Ab Rashid, R., Hashmi, U. M., Mohamed, M., Alqaryouti, M. H., & Sadeq, A. E. (2023). Using chatbots for English language learning in higher education. Computers and Education: Artificial Intelligence, 5, 100153.

Annamalai, S., Ramnath, R., Antony, S., & Devi, S. B. (2025). Doctoral Researchers' Perspectives on Ethical Considerations in Artificial Intelligence in Education Through the Lens of the PAPA Framework. In Ethics and AI Integration Into Modern Classrooms (pp. 493-518). IGI Global Scientific Publishing.

Arora, A., Barrett, M., Lee, E., Oborn, E., & Prince, K. (2023). Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization. Information and Organization, 33(3), 100478. https://doi.org/10.1016/j.infoandorg.2023.100478

Barteit, S., Guzek, D., Jahn, A., Bärnighausen, T., Jorge, M. M., &Neuhann, F. (2020). Evaluation of e-learning for medical education in low- and middle-income countries: A systematic review. Computers & education, 145, 103726. https://doi.org/10.1016/j.compedu.2019.103726

Belda-Medina, J., &Kokošková, V. (2024). ChatGPT for language learning: Assessing teacher candidates’ skills and perceptions using the Technology Acceptance Model (TAM). Innovation in Language Learning and Teaching, 1–16, 1. https://doi.org/10.1080/17501229.2024.2435900

Chakravarti, M. A., Biswas, M. D., Mondal, M. B., & Gupta, D. P. (2025). Towards A Hybrid Epistemology In The Doctoral Ecosystem: A Narrative Review In The Age Of Human-Ai Collaboration. Indian Education In The 21st Century, 33.

Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Chen, Y., Zhang, X., & Wang, J. (2023). AI-powered feedback systems in higher education: Opportunities and challenges. Computers & Education, 196, 104755. https://doi.org/10.1016/j.compedu.2023.104755

Chen, Y., Zhang, X., & Wang, J. (2023). AI-powered feedback systems in higher education: Opportunities and challenges. Computers & Education, 196, 104755. https://doi.org/10.1016/j.compedu.2023.104755

Chiu, T. K. F. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6(November 2023), 100197. https://doi.org/10.1016/j.caeai.2023.100197

Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2172044

Choi, G. W., Kim, S. H., Lee, D., & Moon, J. (2024). Utilizing generative AI for instructional design: Exploring strengths, weaknesses, opportunities, and threats. TechTrends, 1–13, 1. https://doi.org/10.1007/s11528-024-00967-w

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71(March). https://doi.org/10.1016/j.ijinfomgt.2023.102642

Gao, X., & Feng, H. (2023). AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity. Sustainability (Switzerland), 15(11). https://doi.org/10.3390/su15118934

Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12). https://doi.org/10.3390/educsci13121216

Green, T. D., & Donovan, L. C. (2018). Learning Anytime, Anywhere through Technology. The Wiley Handbook of Teaching and Learning, 225–256. https://doi.org/10.1002/9781118955901.ch9

Guidance for generative AI in education and research. (2023). In Guidance for generative AI in education and research. https://doi.org/10.54675/ewzm9535

Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Ilieva, J., Galvin, R., & Dede, C. (2023). The teacher-AI partnership: Designing for co-agency in the classroom. AI and Education Journal, 7(2), 88–102.

Joseph, O. U., Arikpo, I. M., Victor, O. S., Chidirim, N. E., Mbua, A. P., Ify, U. M., & Diwa, O. B. (2024). Artificial Intelligence (AI) in academic research. A multi-group analysis of students’ awareness and perceptions using gender and programme type. Journal of Applied Learning and Teaching, 7(1). https://doi.org/10.37074/jalt.2024.7.1.9

Kasneci, E., Sessler, K., Betschart, M., &Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Instruction, 83, 101812. https://doi.org/10.1016/j.learninstruc.2023.101812

Kong, S. C., Yang, Y., & Hou, C. (2024). Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model. Computers and Education: Artificial Intelligence, 7, 1–12. https://doi.org/10.1016/j.caeai.2024.100328

Krishnamoorthy, R., Srivastava, M. & Khanna, D. (2025). AI in higher education: tapping educators’ perspective. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-024-02657-5

Liu, G., & Ma, C. (2023). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 18(2), 125–138. https://doi.org/10.1080/17501229.2023.2240316

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2021). Intelligence unleashed: An argument for AI in education. Pearson.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2021). Intelligence unleashed: An argument for AI in education. Pearson.

Mahajan, S., Pandey, P. K., Pandey, P. K., & Guleria, N. (2025). Leveraging Artificial Intelligence in Indian Higher Education Institutions to Foster Sustainable Practices: A Comprehensive Analysis. In Adaptive Strategies for Green Economy and Sustainability Policies (pp. 301-320). IGI Global Scientific Publishing.

Maiti, M., Kayal, P., & Vujko, A. (2025). A study on ethical implications of artificial intelligence adoption in business: Challenges and best practices. Future Business Journal, 11, Article 34. https://doi.org/10.1186/s43093-025-00462-5

Malik, A., Khan, M. L., Hussain, K., Qadir, J., & Tarhini, A. (2025). AI in higher education: unveiling academicians’ perspectives on teaching, research, and ethics in the age of ChatGPT. Interactive Learning Environments, 33(3), 2390-2406.

Moharana, S. (2025). Prospects of artificial intelligence (AI) and personalized learning in inclusive education integrated to NEP-2020. Asian Journal of Education and Social Studies, 51(4), 109–116. https://doi.org/10.9734/ajess/2025/v51i41852

Nilashi, M., &Abumalloh, R. A. (2025). i-TAM: A model for immersive technology acceptance. Education and Information Technologies, 30, 7689–7717. https://doi.org/10.1007/s10639-024-13080-5

Nwozor, A. (2025). Artificial intelligence (AI) and academic honesty-dishonesty nexus: Trends and preventive measures. AI and ethics, academic integrity and the future of quality assurance in higher education, 27.

Obaje, T. A. (2025). Advancing Critical Thinking in Higher Education: The Transformative Role of Artificial Intelligence.

Radanliev, P. (2025). AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development. Applied Artificial Intelligence, 39(1). https://doi.org/10.1080/08839514.2025.2463722

Rane, J., Kaya, Ö., Mallick, S. K., & Rane, N. L. (n.d.). Artificial intelligence in education : A SWOT analysis of ChatGPT and its implications for practice and research. 2024, 142–161.

Saad, S., Ramli, Z., Sarmila, M. S., Nor, M., & Ali, S. (2025). Exploring the Adoption of AI-Driven Adaptive Learning in Higher Education: A Multidimensional TAM Perspective. International Journal of Academic Research in Business and Social Sciences, 15(5), 1011-1025.

Scherer, R., Siddiq, F., &Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009

Sharma, D., Pareek, A., Noor, S., & Dey, S. K. (2025). Adoption of AI in Education: An Analysis of Acceptance of ChatGPT Among Students Based on the Technology Acceptance Model (TAM). South Asian Journal of Management, 11(1).

Sharma, M., Chahal, S., Sharma, Y., Roy, S. K., & Singh, A. (2024). Educational transformation: A bibliometric and scientometric analysis of AI in higher education. Cahiers Magellanes-NS, 6(2). https://doi.org/10.6084/m9.figshare.263387

Sharma, S., Singh, G., Sharma, C. S., & Kapoor, S. (2024). Artificial intelligence in Indian higher education institutions: a quantitative study on adoption and perceptions. International Journal of System Assurance Engineering and Management, 1-17.

Shen, X., Mo, X., & Xia, T. (2024). Exploring the attitude and use of GenAI-image among art and design college students based on TAM and SDT. Interactive Learning Environments, 33(2), 1198–1215. https://doi.org/10.1080/10494820.2024.2365959

Şimşek, A. S., Cengiz, G. Ş. T., & Bal, M. (2025). Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13591-9

Stolpe, K., & Hallström, J. (2024). Artificial intelligence literacy for technology education. Computers and Education Open, 6(October 2023), 100159. https://doi.org/10.1016/j.caeo.2024.100159

Subaveerapandiyan, A., Kalbande, D., & Ahmad, N. (2025). Perceptions of effectiveness and ethical use of AI tools in academic writing: A study Among PhD scholars in India. Information Development, 0(0). https://doi.org/10.1177/02666669251314840

Taneja, D., Prabagaren, H., & Thomas, M. R. (2025). Al in Academia: Balancing Integrity, Ethics, and. Pitfalls of AI Integration in Education: Skill Obsolescence, Misuse, and Bias: Skill Obsolescence, Misuse, and Bias, 319.

Tzafilkou, K., Perifanou, M., & Economides, A. A. (2021). Negative emotions, cognitive load, acceptance, and self-perceived learning outcome in emergency remote education during COVID-19. Education and information technologies, 26(6), 7497–7521. https://doi.org/10.1007/s10639-021-10604-1

Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252(PA), 124167. https://doi.org/10.1016/j.eswa.2024.124167

Wang, Z., Wang, Y., Zeng, Y., et al. (2025). An investigation into the acceptance of intelligent care systems: An extended technology acceptance model (TAM). Scientific Reports, 15, 17912. https://doi.org/10.1038/s41598-025-02746-w

Wulyani, A. N., Widiati, U., Muniroh, S., Rachmadhany, C. D., Nurlaila, N., Hanifiyah, L., & Sharif, T. I. S. T. (2024). Patterns of utılızıng AI–Assısted tools among EFL students: Need surveys for assessment model development. LLT Journal: A Journal on Language and Language Teaching, 27(1), 157–173. https://doi.org/10.24071/llt.v27i1.7966

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2020). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 17(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2020). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 17(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Zhang, C., Schießl, J., Plößl, L., & others. (2023). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 20(1), 49. https://doi.org/10.1186/s41239-023-00420-7

Zou, R. (2025). Research on Ethical Issues, Data Privacy Protection, Algorithmic Bias, and Regulatory Policy of Artificial Intelligence Technology in Digital Transformation. In: Li, X., Yuan, C., Vartiak, L. (eds) Proceedings of the 8th International Conference on Economic Management and Green Development. ICEMGD 2024. Applied Economics and Policy Studies. Springer, Singapore. https://doi.org/10.1007/978-981-96-3236-7_21

Published

01-03-2026

How to Cite

Devi , S. B., & Ramnath, R. (2026). Promise and Perils of Artificial Intelligence in Educational Research: An Exploratory Study of Doctoral Scholars’ Perspectives. Innovare Journal of Education, 14(2), 31–40. https://doi.org/10.22159/ijoe.2026v14i2.58384

Issue

Section

Research Article(s)

Similar Articles

<< < 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.