A Systematic Analysis on Graduate Theses Published in The Field of Computer Programming in K-12 Education Between 2018 and 2022

Abstract

This study is designed to reveal the research trends of graduate theses published in the field of computer programming in K-12 between 2018 and 2022. Document analysis was used for data collection in this study. The data was divided into 9 categories, and the results demonstrated that the scholars in the Departments of Computer Educational and Instructional Technologies (CEIT) at Atatürk University and Ondokuz Mayıs University of Türkiye mainly published master’s theses in this field in 2019. Another result was that though CEIT is also the main department for doctoral theses, no difference exists in terms of years or universities. “Teaching, learning, and training programming” and "computational thinking" are the most frequently used keywords in graduate programs, respectively. While quantitative and mixed method (parallel, convergent), convenience sampling, and psychometric scales are preferred in master's theses, mixed method (explanatory, mixed), purposive sampling, interviews/focus group interviews, and psychometric scales are preferred in doctoral theses, respectively. Observation and semi-structured interview forms are used as data collection tools in the theses. Although quantitative methods are mainly utilized in data analysis, parametric and non-parametric statistical tests are also used, and content analysis is resorted to as part of qualitative methods. Whilst validity and reliability studies have been carried out measurement tools are employed in master's theses, scales have been developed in doctoral theses. The present study also offers some suggestions for future research on teaching computer programming