Harnessing Artificial Intelligence’s Potential in Rural Education Research: An Application of ChatGPT-4
DOI:
https://doi.org/10.57125/FED.2024.06.25.05Keywords:
AI in Education, Artificial Intelligence, ChatGPT-4, NREA Research Agenda, Research process, doctoral researchAbstract
This exploratory study delved into the capabilities of Artificial Intelligence (AI) to enhance rural education research. Specifically, it sought to operationalise the research agenda outlined by the National Rural Education Association of the United States of America and involve scholar-practitioners in conducting research that could influence policy and practice in rural education. The study explored the opportunities of AI applications, specifically the ChatGPT-4, in generating initial study ideas for the Policy and Funding support theme within the National Rural Education Association Research Agenda – 2022-2027. The focus was on meeting the needs of racially and linguistically diverse students in rural educational settings. The ChatGPT-4 successfully generated five relevant research problems/study topics, nine research questions, and identified three possible theoretical frameworks. Four limitations were identified: (1) inaccuracy of the leading scholars, (2) the lack of contextual understanding, (3) the lack of domain expertise, and (4) a potential over-reliance on automated assistance. The results of this study highlighted the potential of ChatGPT-4 as an effective tool for researchers in the early stages of their projects. It was found that the ChatGPT-4 efficiently provided relevant research topics, questions, and theoretical frameworks. As such, it may provide several advantages in the initial research process including accuracy in generating research problems, saving time, reducing cognitive workload, and enhancing idea generation. Since the tool expedited idea generation, it may free up researchers to concentrate on other aspects of research such as critical thinking and analysis. However, the limitations included inaccuracies in identifying leading scholars, the lack of contextual understanding, insufficient domain expertise, and the risk of excessive dependence on automation. This suggests that caution should be used when utilising AI to support research as human expertise in content, context, and methodology is vital for conducting thorough research.
References
Aithal, P. S., & Aithal, S. (2023). The changing role of higher education in the era of AI-based GPTs. International Journal of Case Studies in Business, IT, and Education (IJCSBE), 7(2), 183–197. https://dx.doi.org/10.2139/ssrn.4609337
Araujo, T. (2020). Conversational agent research toolkit: An alternative for creating and managing chatbots for experimental research. Computational Communication Research, 2(1), 35–51. https://doi.org/10.5117/CCR2020.1.002.ARAU
Baidoo-Anu, D., & Owusu-Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500
Bryk, A. S. (2015). 2014 AERA distinguished lecture: Accelerating how we learn to improve. Educational Researcher, 44(9), 467–477. https://doi.org/10.3102/0013189X15621543
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education. Educational Technology & Society, 25,(1), 28–47. https://www.jstor.org/stable/48647028
Chokshi, A. (2023, April 4). Planning professional development on ChatGPT. ASCD Blog. https://www.ascd.org/blogs/planning-professional-development-on-chatgpt
Coladarci, T. (2007). Improving the yield of rural education research: An editor’s swan song. Journal of Research in Rural Education, 22(3), 1–9. https://jrre.psu.edu/sites/default/files/2019-08/22-3.pdf
Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage Publications.
Crompton, H., & Burke, D. (2024). The Educational Affordances and Challenges of ChatGPT: State of the Field. TechTrends, 68, 380–392. https://doi.org/10.1007/s11528-024-00939-0
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), Article 22. https://doi.org/10.1186/s41239-023-00392-8
Dempere, J., Modugu, K. P., Hesham, A., & Ramasamy, L. (2023). The impact of ChatGPT on higher education. Frontiers in Education, 8, Article 1206936. https://doi.org/10.3389/feduc.2023.1206936
Hartman, S., Roberts, J., Schmitt-Wilson, S., McHenry-Sorber, E., Buffington, P. J., & Biddle, C. (2022). National rural education association research agenda – 2022–2027: A closer look at the research priorities. The Rural Educator, 43(3), 59–66. https://doi.org/10.55533/2643-9662.1349
Hemsley-Brown, J., & Sharp, C. (2003). The use of research to improve professional practice: A systematic review of the literature. Oxford Review of Education, 29(4), 449–471. https://doi.org/10.1080/0305498032000153025
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
Imran, M., & Almusharraf, N. (2023). Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature. Contemporary Educational Technology, 15(4), Article ep464. https://doi.org/10.30935/cedtech/13605
Ivanov, S. (2023). The dark side of artificial intelligence in higher education. The Service Industries Journal, 43(15–16), 1055–1082. https://doi.org/10.1080/02642069.2023.2258799
Jiang, C. (2021). Technical framework and model of artificial intelligence for boosting the revitalization of rural education. In Proceeding of the 2nd International seminar on artificial intelligence, networking and information technology (AINIT) (pp. 107–110). IEEE. https://doi.org/10.1109/AINIT54228.2021.00031
Joyce, K. E., & Cartwright, N. (2020). Bridging the gap between research and practice: Predicting what will work locally. American Educational Research Journal, 57(3), 1045–1082. https://doi.org/10.3102/0002831219866687
Kooli, C. (2023). Chatbots in education and research: A critical examination of ethical implications and solutions. Sustainability, 15(7), Article 5614. https://doi.org/10.3390/su15075614
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), Article 56. https://doi.org/10.1186/s41239-023-00426-1
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology, 74(5), 570–581. https://doi.org/10.1002/asi.24750
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education Sciences, 13(9), Article 856. https://doi.org/10.3390/educsci13090856
Mullen, C. (2003). What is a scholar practitioner? K12 teachers and administrators respond. Scholar Practitioner Quarterly, 1(4), 9–26.
Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022). AI-Based personalized e-learnings systems: Issues, challenges, and solutions. IEEE Access, 10, 81323–81342. https://doi.org/10.1109/ACCESS.2022.3193938
National Academy of Medicine. (n.d.). Toward a code of conduct for artificial intelligence used in health, medical care, and health research. https://nam.edu/programs/value-science-driven-health-care/health-care-artificial-intelligence-code-of-conduct/
Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221–4241. https://doi.org/10.1007/s10639-022-11316-w
Patton, M.Q. (2014). Qualitative research and evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.
Paek, S., & Kim, N. (2021). Analysis of worldwide research trends on the impact of artificial intelligence in education. Sustainability 13(14), Article 7941. https://doi.org/10.3390/su13147941
Perry, J. A., Zambno, D., & Crow, R. (2020). The improvement science dissertation in practice: A guide for faculty, committee members, and their students. Myers Education Press.
Schiff, D. (2022). Education for AI, "not" AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2
Spencer Foundation. (n.d.). Supporting transformative research projects designed to reimagine education systems for equity. https://www.spencer.org/transformative-research-program
Truly, A. (2023, June 16). GPT-4: How to use the AI chatbot that puts ChatGPT to shame. Digitaltrends. https://www.digitaltrends.com/computing/chatgpt-4-everything-we-know-so-far/
U.S. Department of Education. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. Office of Educational Technology. https://tech.ed.gov/files/2023/05/ai-future-of-teaching-and-learning-report.pdf
William T. Grant Foundation. (n.d.). Research grants on improving the use of research evidence. https://wtgrantfoundation.org/grants/research-grants-improving-use-research-evidence
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., ... Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 2021, Article 8812542. https://doi.org/10.1155/2021/8812542
Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, Article 100025. https://doi.org/10.1016/j.caeai.2021.100025
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
