Akademik Veri Yönetim Sistemi
Tezin Türü: Doktora
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Eğitim Fakültesi, Eğitim Bilimleri Bölümü, Türkiye
Tezin Onay Tarihi: 2011
Öğrenci: ESMA EMMİOĞLU
Eş Danışman: YEŞİM ÇAPA AYDIN, AHMET OK
Özet:The purpose of the current study was to investigate the structural relationships among self-reported mathematics achievement, attitudes toward statistics, and statistics outcomes by testing a structural model. The current study utilized a survey design. The participants of study consisted of 247 undergraduate and graduate students enrolled in statistics courses in a university in Turkey. The participants were from different disciplines such as engineering, education, and economics. The Turkish version of the Survey of Attitudes toward Statistics-36© (SATS-36©) was used to collect data. The SATS-36© assessed six components of statistics attitudes: cognitive competence, value, difficulty, effort, interest, and affect. Higher scores of the six components referred to the more positive attitudes. In addition, the SATS-36© involved additional items to measure students’ self-reports of mathematics achievement and statistics outcomes. Results of the descriptive statistics analyses revealed that participants of the study had positive attitudes toward statistics except that they had neutral perceptions about the difficulty of statistics and neutral interest in statistics. Statistics outcomes variable was significantly correlated with mathematics achievement, affect, value, interest, and effort variables. Structural equation modeling was used to test the hypothesized structural regression model. Results indicated that affect, value, cognitive competence, and interest variables had large total standardized effects on statistics outcomes variable. Mathematics achievement and the effort variables had small total effects on explaining statistics outcomes. Difficulty had no statistically significant total effect on explaining statistics outcomes. Overall, the hypothesized structural regression model explained 66% of the total variance in statistics outcomes, which was statistically significant.