Öğrencilerin ödevle ilgili öz-düzenleme becerilerinin ve öğretmenlerin ödev uygulamalarının araştırılması.

This study investigated Grade 7 students’ Science and Technology homework self-regulation in relation to science achievement and teachers’ homework practices. This was a nationwide study; 8318 seventh grade students and 344 Science and Technology teachers in Turkey participated. Participating students completed Student Homework Scale and Science Achievement Test while their Science and Technology teachers responded to the items in Teacher Homework Scale. Hierarchical Linear Modeling (HLM) analyses were conducted due to the nested structure of data. Results revealed that controlling for students’ prior-achievement and gender, students’ perceptions of homework quality and feedback provided on homework predicted students’ homework self-regulation (i.e., goal orientations in homework, homework procrastination, and homework strategy use) and science achievement. Moreover, pursuing high levels of mastery and low levels of work-avoidance goals, having low tendency to procrastinate homework, and using deep learning strategies during homework positively predicted science achievement. Class level analyses revealed that students in classes with higher average perceptions of homework quality were espoused to more mastery and performance goals and less work-avoidance goals; were less likely to delay homework; and used more homework management and deep learning strategies than students in other classes. Besides, students’ shared perceptions of homework feedback positively predicted students’ homework management and deep learning strategy use, and achievement. Additionally, students in classes with higher teacher support for deep learning strategy use performed better on the science achievement test than did students in other classes.Ph.D. - Doctoral Progra