EXAMINATION OF GRADUATE THESES MADE ON THE SUB-LEARNING FIELD OF PRIMARY SCHOOL MATHEMATICS COURSE DIVISION PROCESS

Abstract

In this study, it was aimed to systematically and holistically analyze postgraduate theses focusing on the teaching of division at the primary school level in Turkey and to determine the academic trends in this field. Descriptive content analysis, one of the types of content analysis, was preferred as the research method. The universe of the study consists of postgraduate theses accessible via the National Thesis Center of the Council of Higher Education, published between 1994 and 2024, and focusing on primary school mathematics and division instruction. The sample of the study includes 42 postgraduate theses selected through criterion sampling. To collect data, the “Postgraduate Thesis Review Form” developed by the researcher was used. The data were analyzed through content analysis and the findings were reported descriptively. According to the findings, the majority of the theses were at the master’s level and focused on themes such as teaching strategies, student difficulties, and mathematical thinking. A significant increase in academic interest in division-related topics has been observed, especially after 2018. This increase is associated with transformations in educational policies, updates in curriculum programs, and the growing importance of student-centered teaching strategies. Additionally, the acceleration of digitalization and distance education during the COVID-19 pandemic contributed to the rise in the number of thesis studies. In particular, the rate of 23.8% reached in 2023 is considered a concrete indicator of the academic interest in restructuring education and digital teaching strategies after the pandemic. Moreover, it was observed that constructivist strategies such as game-based learning, multiple representations, contextual teaching, and the use of concrete materials were frequently employed. However, it was also determined that some theses lacked sufficient reporting regarding the validity and reliability of the data analysis process.