Factors predicting engineering faculty students' perceived learning of computer programming
2019
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Danışman: Dr. Öğr. Üyesi Melih Derya Gürer
Özet (EN)
Factors affecting programming achievement are attitude towards programming, programming self-efficacy, gender, students' department and the number of courses taken on computer programming. The related literature indicates that there are different studies examining the effect of these variables on programming achievement. However, there is a need for further studies investigating to what extent these factors explain the success of programming. Hence, the aim of this study was to investigate the factors predicting engineering students' computer programming perceived learning. In this study, the effects of programming self-efficacy, attitude towards programming, gender, department and number of courses regarding computer programming on perceived learning were examined. Correlational study design was adopted for this study. The sample of the study was 880 students of an engineering faculty in North Black Sea Region. To collect data, in addition to demographic variables, Programming Self-Efficacy Scale, Computer Programming Attitude Scale, and Perceived Learning Scale were used. To analyze data, descriptive statistics e.g. mean and standard deviation, and Pearson Correlation tests were administered. In addition, to determine the factors affecting perceived learning, multiple regression analysis were used. As a result, it was concluded that the engineering faculty students' attitudes of towards programming, programming self-efficacy and perceived learning were at a high level. In addition, there were significant correlations between perceived learning and students' gender, department, number of courses on programming, attitude towards programming and programming self-efficacy. Finally, it was concluded that gender, attitude towards programming and programming self-efficacy significantly predicted perceived learning. Based on the results of the study, discussions were made and suggestions for implementation and future research were offered.
Yazar
Dr. Seyfullah Tokumacı
Kurum

Bolu Abant Izzet Baysal University
Bilgisayar ve Öğretim Teknolojileri Eğitimi Bilim Dalı
Bu Yayına Nasıl Atıf Yapılır
Seyfullah Tokumacı (Master Thesis). Factors predicting engineering faculty students' perceived learning of computer programming, 2019, Bolu Abant Izzet Baysal University.
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