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The aim of this study was to investigate the factors affecting the pre-service computer science teachers' attitudes towards computer programming (ATCP). The sample consists of 119 preservice teachers at a public state university. The influences of students' demographic characteristics (gender, grade level, and high school type), their achievement in computer programming courses, perceived learning, and computer programming self-efficacy on their ATCP were tested using multiple linear regression. Descriptive, correlation and regression analyses revealed three findings: (1) students had moderately high ATCP, (2) their ATCP had significant correlations with their achievement in computer programming courses, computer programming self-efficacy, and perceived learning, and (3) three variables (achievement in computer programming courses, computer programming self-efficacy, and perceived learning) were significant predictors of their ATCP.

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Literature indicated that attitude toward programming, programming self-efficacy, gender, and students’ department has been related to achievement in computer programming. However, there is a need for further studies investigating to what extent these factors explain programming achievement in a model. This study aimed to investigate the effects of programming self-efficacy, attitude towards programming, gender, and students’ department on their perceived learning. A correlational study design was adopted for this study. The sample of the study was 742 students of an engineering faculty at a state university inTurkey. To collect data, 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 was employed. The results indicated that the engineering faculty students’ attitudes towards programming, programming self-efficacy and perceived learning were at high level. In addition, significant correlations between perceived learning and predictive variables were found. Finally, it was concluded that gender, attitude towards programming and programming self-efficacy significantly predicted perceived learning. The results of the study provide a deeper understanding of how students’ learning was affected in programming courses.