Descriptive Content Analysis of Postgraduate Studies on Probability in Mathematics Education in Turkey

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Ali ŞAHİN

Abstract

This study aims to determine the results of descriptive content analysis of postgraduate studies
on probability in mathematics education. The study is a qualitative study and utilizes the
document analysis technique. The sample of this study consists of 21 postgraduate theses on the
subject of probability conducted at the Council of Higher Education (YÖK) National Thesis
Center. The "Thesis Studies on Probability Review Form" prepared by the researcher was used as
the data collection tool. Descriptive content analysis method was used in the analysis of the
obtained data. As a result of the analysis conducted according to the thematic characteristics of
postgraduate studies, it was seen that the highest number of master's studies was 20 studies
(95.2%), while in terms of years, it was seen that the most studies were in 2024 (23.8%). It was
observed that more studies were conducted at Boğaziçi University, Balıkesir University, and
Karadeniz Technical University compared to other universities, with 3 studies (14.2%) each, while
in terms of institutes, it was found that studies were published at the Institute of Science and
Technology with a maximum of 10 studies (47.6%). According to the methodological structure,
experimental research method was preferred in 5 studies (23.8%), while in terms of sample size,
studies were conducted with 120 or more participants in 8 studies (38.1%). In terms of sample
type, 16 studies (76.1%) conducted studies with students, and in terms of data collection tool, it
was seen that achievement test was used the most, with 14 studies (33.3%). As a result of the
examinations carried out, it was found that t-tests were used for dependent and independent
samples in 9 studies (20.0%).

Article Details

How to Cite
ŞAHİN, A. (2026). Descriptive Content Analysis of Postgraduate Studies on Probability in Mathematics Education in Turkey. Social, Human and Administrative SciencesSEARCH, 9(1), 1–19. https://doi.org/10.26677/TR1010.2026.1617
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