International Trends and Influencing Factors in the Integration of Artificial Intelligence in Education with the Application of Qualitative Methods

This study offers a comprehensive examination of the scientific production related to the integration of artificial intelligence (AI) in education using qualitative research methods, an emerging intersection that reflects growing interest in understanding the pedagogical, ethical, and methodological implications of AI in educational contexts. Grounded in a theoretical framework that emphasizes the potential of AI to support personalized learning, augment instructional design, and facilitate data-driven deci-sion-making, the study applies a systematic literature review and bibliometric analysis to 630 publications indexed in Scopus between 2014 and 2024. Results show a significant increase in scholarly output, particularly since 2020, with notable contributions from authors and institutions in the United States, China, and the United Kingdom. High-impact research is found in top-tier journals, and dominant themes include health education, higher education, and the use of AI for feedback and assessment. The findings also highlight the role of semi-structured interviews, thematic analysis, and interdisciplinary approaches in capturing the nuanced impacts of AI integration. The study concludes that qualitative methods remain essential for critically evaluating AI’s role in education, reinforcing the need for ethically sound, human-centered, and context-sensitive applications of AI technologies in diverse learning environments.