Generative artificial intelligence tools in education research: Applications, and methodological enhancements
Abstract:This opinion paper discusses the rapid development of generative artificial intelligence (GenAI) tools, which have significantly impacted educational research. This study examines the diverse applications of GenAI in educational settings, highlighting how it can enhance data analysis, automate literature reviews using generative AI tools, and facilitate personalized learning. By incorporating GenAI techniques such as automated content generation, researchers may expedite the data collecting process, generate insights from large-scale datasets, and develop adaptive learning materials that respond to student needs individually. This study also demonstrates methodological improvements made possible by GenAI, such as enhanced research design and the promotion of collaboration across disciplines. The researchers highlight best practices and potential pitfalls related to using GenAI tools in education research through a review of recent literature and case studies. As generative AI continues to impact the educational system, researchers and educators must exercise caution to maximize its potential. This paper's ultimate goal is to give researchers and educators a framework for efficiently utilizing GenAI technology, stressing the value of data integrity and ethical issues in promoting creative research approaches.