Attitudes of IT teacher candidates towards computer programming and their self-efficacy and opinions regarding to block-based programming

Çoban, Emre; Korkmaz, Özgen; Çakır, Recep; Erdoğmuş, Feray Uğur

doi:10.1007/s10639-020-10164-w

Cited by 13 publications

(5 citation statements)

References 31 publications

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“…In the literature, there are studies on non-cognitive factors that support the results of this study. It was found that there is a moderate significant relationship between CPA and CPSE (Çoban, Korkmaz, Çakır & Erdoğmuş, 2020); and a moderate significant relationship between CT and CPSE (Durak, Yılmaz, & Yılmaz, 2019) and CPSE predicted CT significantly (Avcu & Ayverdi, 2020). The importance of the data obtained within the scope of this study is that the CPSE and CPA variables, which come to mind as the non-cognitive factor when it comes to CT, are considered together for the middle school students, and this study reveals the order of their importance.…”

Section: Discussion Of Findingsmentioning

confidence: 68%

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Günbatar

2020

IJCSES

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The purpose of this research is to examine Computer Programming Attitude (CPA), Computer Programming Self-Efficacy (CPSE) and Computational Thinking (CT) skills of middle school students who took the Information Technologies & Software (IT&S) courses and those who did not, and make various analyses according to the relationships between these variables. As a result of the analysis, it was found that CPA and CPSE variables are significant predictors for CT skills, both students who took IT&S course and those who did not take have moderate CPSE, but students who took IT&S course have a statistically significantly higher CPSE. In addition, it was observed that both those who took IT&S course and those who did not have moderate CPA and did not differ statistically, and students who took IT&S course had a high level of CT, while those who did not take the course were moderate and statistically different. It was also found that students who took IT&S courses made cumulative progress in terms of CPSE, CPA and CT variables compared to those who did not. The obtained results are discussed within the framework of middle school IT & S course curriculum held in Turkey in 2018.

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Section: Discussion Of Findingsmentioning

confidence: 68%

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Günbatar

2020

IJCSES

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“…Scholars have pointed out that programming beginners have difficulties with learning (Law et al, 2010; Ramalingam & Wiedenbeck, 2004), which may stem from their self-efficacy factor (Çoban et al, 2020; Kong et al, 2018; Tsai, 2019; Yukselturk & Altiok, 2017). Thus, the self-efficacy factor was examined in previous studies on general programming (Kong et al, 2018; Kovari & Katona, 2023) or block-based programming (Belland et al, 2022; Durak, 2018; Ma et al, 2021; Wei et al, 2021; Yukselturk & Altiok, 2017; Çoban et al, 2020). For example, in Durak’s (2018) study, students used Scratch to carry out digital story design activities in programming learning.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Programming learning requires that learners experience the execution of program applications (apps) and increase their confidence in programming learning by completing an actual program (Kong et al, 2018; Wei et al, 2021; Yukselturk & Altiok, 2017). In response to the learning threshold of the traditional textual program, block-based programming instruction has recently emerged as a beginner’s tool for programming learning (Çoban et al, 2020; Weintrop & Wilensky, 2019; Weng et al, 2023; Vasconcelos & Kim, 2022). Using a visual programming language interface reduces the learning barrier of memorizing syntax.…”

Section: Introductionmentioning

confidence: 99%

Effects of a Programming Course Using the GAME Model on Undergraduates’ Self-Efficacy and Basic Programming Concepts

Tsai,

Chen,

Hsieh

et al. 2023

Journal of Educational Computing Research

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In higher education, it is challenging to cultivate non-computer science majors’ programming concepts. This study used the GAME model (gamification, assessment, modeling, and enquiry) in a programming education course to enhance undergraduates’ self-efficacy and performance of basic programming concepts. There were 83 undergraduates taking part in this study, which adopted a quasi-experimental research design. Students in the experimental group ( n = 43) experienced a course in which the GAME model was used to design the block-based programming course. The control group ( n = 40) was given a general information education course covering similar learning concepts without the game-based learning strategy. The analysis of covariance (ANCOVA) was adopted to investigate the effect of the GAME model on students’ learning outcomes for the quantitative data. In the qualitative analysis, students’ responses to the course perception questionnaire were coded and analyzed. The results showed that students in the experimental group outperformed their counterparts regarding self-efficacy and basic programming concepts. The experimental treatment resulted in a small to medium effect size difference between the two groups. The results showed that incorporating the GAME model into block-based programming teaching helped improve undergraduates’ self-efficacy and performance of basic programming concepts. In addition, these experimental group undergraduates also perceived the pedagogic GAME model positively. Several research suggestions are proposed based on the findings of the present study.

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“…He advocated for the perspective of ‘programming empowerment’ and encouraged children to develop high‐order thinking through programming (Papert, 1980). Afterwards, K‐12 programming education rapidly developed, and various programming platforms were continuously launched, including visual programming (Scratch, Code.org, AppInventor, LightBot, and Blockly) (Çoban et al, 2020), educational robotics (Lego, Arduino, mBot, BeeBot, Botley, and TangibleK robots) (Fessakis & Prantsoudi, 2019), and unplugged (CS unplugged, PAP, Codemonkey, and Kodable) (Aranda et al, 2019; Deng et al, 2020; Resnick & Robinson, 2017; Scherer et al, 2019). Incorporating programming into the K‐12 curriculum has become a global consensus.…”

Section: Introductionmentioning

confidence: 99%

“…A great deal of research of K‐12 programming education pays more attention to teachers' teaching behaviour (Fessakis & Prantsoudi, 2019; Pérez‐Calderón et al, 2021), but less attention paid to their attitudes. However, compared with the teachers' proficiency in programming knowledge and skills, their previous attitude towards programming and teaching intention may be the key to determine the effect of K‐12 programming education (Çoban et al, 2020). Therefore, measuring K‐12 teachers' attitudes towards programming is a prerequisite.…”

Section: Introductionmentioning

confidence: 99%

K‐12 teachers' programming attitudes among different disciplines: Analysis of influential factors

Sun,

Zhou

2023

Computer Assisted Learning

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BackgroundIntegrating programming in K‐12 curriculum has become a global consensus. Teachers are central figures in programming instruction. But the majority of current research focuses on teachers' external teaching behaviours and less on teachers' attitudes towards programming.ObjectivesThe purpose of this study is to validate the K‐12 in‐service Teacher Programming Attitudes Scale (TPAS), to analyse teachers' programming attitudes and their differences in personal, teaching, and environmental factors, and further explore the predictive relationship.MethodsThe sample is 888 K‐12 teachers from China. First, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were adopted to validate the availability and reliability of TPAS; Second, independent sample t‐test and one‐way Analysis of Variance (ANOVA) were adopted to explain the differences. Finally, correlation analysis and linear regression analysis were adopted to verify the correlation and prediction relationship.Results and ConclusionTPAS possess good reliability and validity (χ2/df = 2.488, RMSEA = 0.055, CFI = 0.943, TLI = 0.935, and IFI = 0.943). Further analysis found that, first of all, male teachers possess more positive programming attitudes than female teachers; second, young teachers who are under 30 and the length of teaching under 5 years possess more positive programming attitudes; thirdly, in addition to Information and Communication Technology teachers, primary science teachers also possess high programming attitudes, followed by teachers of Humanities and Arts, reflecting the potential of teaching programming in integrated subjects and the humanities. Finally, primary school teachers possess the best programming attitudes. With the growth of grade, teachers' enthusiasm for programming has gradually decreased. Additionally, discipline, grade and gender factors were considered to predict K‐12 teachers' programming attitudes.ImplicationsThe results of this study contribute to integrating programming teaching of teachers and promoting programming education in K‐12 classrooms.

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Attitudes of IT teacher candidates towards computer programming and their self-efficacy and opinions regarding to block-based programming

Cited by 13 publications

References 31 publications

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Computational Thinking Skills, Programming Self-Efficacies and Programming Attitudes of the Students

Effects of a Programming Course Using the GAME Model on Undergraduates’ Self-Efficacy and Basic Programming Concepts

K‐12 teachers' programming attitudes among different disciplines: Analysis of influential factors

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