Academic Text Analysis with Artificial Intelligence in Research Methods Education: Attitudes and Experiences

Today, AI is increasingly used in educational environments, supporting scientific research processes and providing students with personalized learning experiences. In line with this, the study seeks to investigate the influence of AI use in a scientific research methods course on students' attitudes toward the course. An explanatory sequential mixed methods design was employed in the study. The study group consisted of 24 students taking a scientific research methods course at a university in the 2024-2025 academic year. An attitude scale was used for quantitative data collection, while focus group interviews were used for qualitative data. The analysis results indicated that AI use positively impacted students' overall attitudes toward the course. While significant increases were observed in cognitive self-confidence and interest, there was no significant change in the perception of the course's importance or its adaptability to professional life. Furthermore, students stated that AI accelerated research processes, reduced the margin of error, and supported academic writing. However, some students expressed that AI use could negatively impact knowledge retention and reduce course participation. In conclusion, AI-supported learning environments appear to have positive effects on student motivation and cognitive self-confidence. However, additional strategies are needed to strengthen independent learning skills, encourage critical thinking, and further connect the course to the professional context.