The effect of artificial intelligence-supported online classroom management on students' attitudes towards English course and artificial intelligence, their self-directed online learning, and academic achievement

The This thesis aims to investigate the effects of AI-supported online classroom management (AISOCM) on students' attitudes toward English courses and artificial intelligence, their self-directed online learning skills and academic achievement. Additionally, it evaluates the impact of AI-supported applications on students' attitudes toward artificial intelligence. The study was conducted using a quasi-experimental design. The experimental and control Grups consisted of 7th-grade students from a middle school in Diyarbakır. The experimental Grup included 32 students, while the control Grup comprised 33 students. Over eight weeks, the experimental Grup was taught using AI- enhanced online classroom management, while the control Grup was taught using only traditional online classroom management. Data were collected using the Attitude Toward English Courses Scale, Self-Directed Online Learning Scale, Academic Achievement Test, and Attitude Toward Artificial Intelligence Scale. The collected quantitative data were analyzed using dependent and independent t-tests. The findings of the study reveal that AISOCM positively impacted students' attitudes toward English courses. Students in the experimental Grup showed significant improvements in both affective (interest and motivation) and behavioral (participation and active learning) dimensions. Specifically, AI-supported tools, with their personalized learning pathways and real-time feedback mechanisms, increased students' motivation and fostered greater engagement in the learning process. In contrast, similar positive effects were not observed in the control Grup. Students in the experimental Grup exhibited significant improvements in both autonomous learning and asynchronous learning dimensions of self-directed online learning. The flexible learning pathways provided by AISOCM enabled students to manage their learning processes more effectively. However, no significant changes were observed in self-directed learning levels in the control Grup. These findings demonstrate the effectiveness of AISOCM in supporting self-directed online learning skills. In terms of academic achievement, students in the experimental Grup showed significant improvements compared to the control Grup. In the assessments of Units 1 and 2, the scores of the experimental Grup were found to be significantly higher. This demonstrates that AI-enhanced online classroom management is an effective tool for improving students' academic performance. In particular, the use of personalized feedback and tailored learning pathways helped students better understand the learning materials and strengthened their long-term learning skills. Regarding attitudes toward artificial intelligence, no significant changes were observed in the experimental Grup's attitudes; however, their existing positive attitudes were maintained. It is recommended that such applications be implemented over a longer duration and with greater intensity to further enhance positive attitudes toward AI. The literature suggests that such applications could yield stronger effects in the long term