Examination of postgraduate theses on autonomous learning and student autonomy

In this study, a total of 170 graduate theses published between 1990 and 2023 on the topics of autonomous learning and student autonomy were examined in the YÖK National Thesis Center database. The search was conducted using the keywords "autonomous learning," "student autonomy," "self-directed learning," "autonomous learning," "learner autonomy," and "autonomous learning." The examination criteria included the year of publication, language of publication, publication type, subject areas, affiliated institutes, research methods, purpose, samples, data collection tools, data analysis methods, findings, conclusions, and recommendations of the theses. The study utilized a qualitative research design through the method of document analysis. The documents were selected using a criterion sampling method. The data were analyzed using descriptive content analysis. According to the results of the research, the theses address various topics such as the fundamental principles of autonomous learning, the role of teachers in promoting student autonomy, the use of technology, and the design of autonomous learning environments. It was observed that the majority of theses were written in English, with only a small number of studies in Turkish. It is believed that new Turkish studies prepared within the field can lead to the development of more suitable and effective autonomy-focused educational approaches for the local student population. The number of master's thesis studies was found to be higher than doctoral thesis studies. The majority of the studies were conducted within the Institute of Educational Sciences and the Institute of Social Sciences. The most commonly used research methods in the theses were purposive and convenience sampling. Quantitative research was the preferred method, and among its designs, the survey design was the most frequently used. Surveys and interviews were the most commonly employed data collection tools. The objectives of the theses mostly aimed to develop applications for enhancing autonomous learning and determining the impact of a variable.