Computational thinking has been gaining new impetus in the academic community and in K-12 level education. Scratch is a visual programming environment that can be utilized to teach and learn introductory computing concepts. There are some studies investigating the effectiveness of Scratch for K-12 level education. However, studies that have been conducted at the collegiate level, especially in the context of preservice computing teacher education, are very rare. The present study aimed to investigate the effect of Scratch-based instruction on preservice teachers' understanding of basic programming concepts and their attitudes toward programming. In the present study, a mixed method design was utilized. In the first phase of the study, the data were collected using an achievement test, a practice test, and a computer programming attitude scale. In the second phase of the study, data were collected through a semistructured interview. The results of the study indicated that preservice teachers in Scratch-based instruction had significantly better understanding of basic computing concepts. Qualitative data indicated that Scratch-based instruction was useful in constructing a more meaningful learning environment for preservice teachers. The results of this study have implications for researchers and preservice computing teacher educators when designing an introductory computing course.
Although the determination of university students' attitudes towards computer programming is a significant issue, the issue has been rarely studied. The purpose of this study was to develop an attitude scale assessing university students' attitudes towards computer programming. In the first phase, the scale was administered to 522 university students. Explanatory factor analysis yielded three dimensions: affection, cognition, and behavior. In the second phase, final version of the 18 item-scale was administered to 553 university students. Results of confirmatory factor analysis provided evidence for the factorial structure of the scale. The Cronbach alpha coefficients ranged from 0.80 to 0.90. Psychometric properties of Computer Programming Attitude Scale (CPAS) suggest that it is a valid and reliable instrument for measuring university students' attitudes towards computer programming. ß 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:667-672, 2015; View this article online at wileyonlinelibrary.com/journal/cae;
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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