THE IMPACT OF ARTIFICIAL INTELLIGENCE ON STUDENTS’ LEARNING PROCESSES: A MIXED-METHOD STUDY
Keywords:
artificial intelligence, higher education, academic performance, adaptive learning, intelligent tutoring systems, educational technologyAbstract
This study examines the impact of artificial intelligence (AI) on students’ learning processes using a mixed-method research design. The study was conducted among 10 secondary school students aged 15–17, with data collected through surveys, semi-structured interviews, and observation. The findings show that AI is widely integrated into students’ academic activities, particularly for completing assignments, translating texts, and generating ideas. While AI improves efficiency and access to information, it also contributes to over-reliance and reduced independent thinking. The study concludes that AI plays a dual role in education, functioning both as a valuable learning support tool and a potential source of dependency, emphasizing the need for its balanced and guided use.
References
Russell, S., Norvig, P. Artificial Intelligence: A Modern Approach. 4th ed. Pearson, 2021. – 1152 p.
Luckin, R. Machine Learning and Human Intelligence: The Future of Education. London: UCL IOE Press, 2018. – 210 p.
Holmes, W., Bialik, M., Fadel, C. Artificial Intelligence in Education. Boston: CCR, 2019. – 124 p.
VanLehn, K. The Relative Effectiveness of Human Tutoring and ITS. Educational Psychologist, 2011, 46(4), pp. 197–221.
Graesser, A., D’Mello, S. Emotions in Intelligent Tutoring Systems. Journal of Educational Psychology, 2015, 107(4), pp. 1230–1242.
UNESCO. Artificial Intelligence in Education: Challenges and Opportunities. Paris: UNESCO, 2021. – 86 p.
Selwyn, N. Should Robots Replace Teachers? Cambridge: Polity Press, 2019. – 256 p.
Bryman, A. Social Research Methods. Oxford: OUP, 2016. – 747 p.
Creswell, J. W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage, 2018. – 304 p.
Seidman, I. Interviewing as Qualitative Research. Teachers College Press, 2019. – 200 p.
Hammersley, M., Atkinson, P. Ethnography: Principles in Practice. Routledge, 2019. – 288 p.
Luckin, R. et al. AI and Future of Learning. Learning Sciences Review, 2020, 12(2), pp. 45–70.
D’Mello, S. Affective Computing in Education. Learning and Instruction, 2017, 50, pp. 1–15.
Downloads
Published
Issue
Section
How to Cite
