Developing the Computer Programming Self-Efficacy Scale for Computer Literacy Education

Abstract

Computer programming has been gradually emphasized in recent computer literacy education and regarded as a requirement for all middle school students in some countries. To understand young students' perceptions about their own learning in computer programming, this study aimed to develop an instrument, Computer Programming Self-Efficacy Scale (CPSES), for all students above middle school levels. Based on Berland and Lee's computational thinking framework, this study developed the CPSES items at a literacy level and finally the instrument included the five subscales: Logical Thinking, Algorithm, Debug, Control, and Cooperation. An exploratory factor analysis and reliability tests were conducted in this study. The reliability alpha was .96 for the overall scale, and ranged from .84 to .96 for the subscales. This study also confirmed the positive correlation between computer programming experience and computer programming self-efficacy. In addition, for low-and middle-experienced learners, significant gender differences were found in two subscales: Algorithm and Debug. The CPSES can be applied as an evaluation tool in computer education, robotics education, as well as integrated STEM or STEAM education in which computer programming was regarded as a part of computer literacy.

Examination of Undergraduate and Associate Degree Students’ Computer Programming Attitude and Self-Efficacy According to Thinking Style, Gender and Experience

“…However, some studies suggest that female students present similar characteristics with male students in relation to programming (Byrne & Lyons, 2001;Malik & Coldwell-Neilson, 2018;Sharma & Shen, 2018;Ventura, 2005), gender does not contribute to prediction of programming performance significantly (Mazman, 2013), and programming attitude does not vary depending on gender (Erol & Kurt, 2017;Yagci, 2016). There are conflicting results in terms of gender variable in the literature (Adamopoulos, 2017;Tsai, Wang & Hsu, 2018). Thus, findings obtained in this study conflict with studies in the literature which suggests that gender affects programming attitude and self-efficacy.…”

“…Therefore, it can be said that programming self-efficacy perception is related with previous experiences and preliminary knowledge (Mazman & Altun, 2013). The programming self-efficacy of those who have more programming experience is also significantly higher (Tsai, Wang & Hsu, 2018). It is quite reasonable that there was a difference between the students with a high level of experience in programming (i.e., 7 years) and the students who had met with programming only a short time ago (less than 1 year and 2 years) in this study.…”

Digital story design activities used for teaching programming effect on learning of programming concepts, programming self‐efficacy, and participation and analysis of student experiences

“…For this reason, it is important to determine and develop the levels of programming skills of students. The most important variables that need to be addressed in order to examine the levels of programming skill of students are programming achievement and programming self‐efficacy, and these variables provide important clues to the development of programming skills (Davidsson, Larzon, & Ljunggren, ; Tsai, Wang, & Hsu, ). Self‐efficacy affects the choice of activities, the level of effort spent, resistance, and performance in coping with difficulties in order to solve a problem and to accomplish a task (Bandura, ).…”

The Validity and Reliability Study of The Turkish Version of Computer Programming Self-Efficacy Scale

“…In this regard, in many countries, including Turkey, the need for rearranging national ICT education curriculums in such a way to include computational skills has emerged (Bocconi, Chioccariello, Dettori, Ferrari, & Engelhardt, 2016;Jun, Han, Kim, & Lee, 2014;Yadav, Good, Voogt, & Fisser, 2017). Computer programming education is considered as an essential way of developing computational skills (Tsai, Wang & Hsu, 2019). Research showed that there is a strong relationship between self-efficacy and student achievement in computational thinking (CT) activities, including programming (Gurer, Cetin & Top, 2019;Haslaman & Aşkar, 2007;Hawlitschek, Koppen, Dietrich, & Zug, 2019;Korkmaz, Kılıç, Çakır & Erdoğmuş;Mazman Akar & Altun, 2017).…”

“…Considering the developments in the field of ICT and computer science, as well as the changes in the current understanding of CT over the past 20 years, the need to revisit selfefficacy measurement tools becomes more evident. Hence, this study aims to adapt the Computer Programming Self-efficacy Scale developed by Tsai, Wang, and Hsu (2019) to the Turkish language and to examine its psychometric properties.…”