Development and analysis of the Elementary Student Coding Attitudes Survey

Mason, Stacie L.; Rich, Peter J.

doi:10.1016/j.compedu.2020.103898

Cited by 49 publications

(32 citation statements)

References 47 publications

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“…An example item for cognition dimension can be “Programming is a distinguishing skill.” Behavior dimension is related to behavioral intentions and “I do research in order to be a good programmer” is an example item for this subdimension. Attitude scales from different subject domains had been considered to construct the first item pool for the scale [3–5,9,23,26,31,36]. The first item pool included 29 items, including affection, cognition, and behavior dimensions.…”

Section: Methodsmentioning

confidence: 99%

“…Awareness, perceived ability, value, and commitment were determined to be the dimensions of the scale. Mason and Rich [23] developed coding attitudes survey for elementary school students. Social value, coding confidence, coding interest, perception of coders, and coding utility were taken as the dimensions of attitude.…”

Section: Introductionmentioning

confidence: 99%

“…He determined confidence and motivation, usefulness, achievement, social perception, and gender as the dimensions of attitude toward programming. Mason and Rich [23] developed a coding attitude scale for students of grades 4–6, including coding confidence, interest, utility, perceptions of coders, and social value as subdimensions of attitude. Cetin and Ozden [5] developed a computer programming attitude scale for university students.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A scale for measuring middle school students' attitudes toward programming

Gul

Çetin

Özden

2021

Comput Appl Eng Educ

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Engineering education has been gaining a place in today's schools within the STEAM framework. Computing is an integral part of the STEAM framework. Affective variables related to computer programming might have an effect on the quality of STEAM education. The aim of this study is to develop a valid and reliable scale to measure middle school students' attitudes toward programming. In the first phase of the study, exploratory factor analysis was conducted with data collected from a total of 508 middle school students. Exploratory factor analysis yielded a one‐dimensional attitude scale. In the second phase of the study, confirmatory factor analysis was used on data obtained from 414 middle school students to examine factor structure. Analyses provided evidence for the factorial structure of the scale. The Cronbach α coefficient of the scale was found to be .93. Then scale was administered to 65 middle school students who attended after‐school coding clubs and who did not attend after‐school coding clubs. It can be concluded that the scale is a reliable and valid scale for measuring middle school students' attitudes toward programming. Moreover, the scale was used to compare the students' scores according to their grades and gender. The findings were discussed.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A scale for measuring middle school students' attitudes toward programming

Gul

Çetin

Özden

2021

Comput Appl Eng Educ

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“…interventions and programmes, it is necessary to develop appropriate tools to assess students' CT development (Mason & Rich, 2021;Román-González et al, 2019). Contemporary learning theories with a socio-cultural and participatory view of learning have proposed 'identity' as a lens to understand students' development (Gee, 2001;Kim et al, 2018;Sfard & Prusak, 2005).…”

Section: Practitioner Notesmentioning

confidence: 99%

“…The development of block‐based programming environments such as Scratch allows even young students to develop CT through programming activities (Lye & Koh, 2014; Shute et al., 2017). To understand student learning in different CT interventions and programmes, it is necessary to develop appropriate tools to assess students' CT development (Mason & Rich, 2021; Román‐González et al., 2019). Contemporary learning theories with a socio‐cultural and participatory view of learning have proposed ‘identity’ as a lens to understand students' development (Gee, 2001; Kim et al., 2018; Sfard & Prusak, 2005).…”

Section: Introductionmentioning

confidence: 99%

Computational identity and programming empowerment of students in computational thinking development

Kong

Lai

2021

Brit J Educational Tech

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The participatory view of learning emphasises students' identity construction. However, identity research in the context of programming education to cultivate students' computational thinking is scarce.In this study, an instrument of computational identity with components of engagement, imagination and affiliation, was developed and validated. Convenience sampling was used to select 1066 senior primary school students studying programming to respond to the instrument, and to a programming empowerment instrument developed previously with components of meaningfulness, self-efficacy and impact.The two instruments' factor structure was confirmed to have acceptable discriminant validity and support gender invariance. There was a positive relationship between programming empowerment and computational identity. Specifically, students' perceived meaningfulness and self-efficacy of programming related to all aspects of computational identity. The perceived impact of programming is related only to the imaginative aspect of computational identity. The establishment of the instrument enables researchers to investigate further factors related to students' computational identity development. The results also indicate that the programming curriculum should be

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How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

Jiang,

Islam,

et al. 2023

J Res Sci Teach

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Computational thinking (CT) is vital for success in numerous domains. However, the nature, definition, and scope of CT are ill‐defined, and research on how best to develop CT is very limited. This study focused on how thinking styles and STEM attitudes have effects on computational thinking. Using a proportionate stratified random sampling procedure, 1195 students from two universities were surveyed. A structural equation modeling analysis showed that students' thinking styles and STEM attitudes directly predicted their computational thinking skills and that thinking styles mediated the relationship between STEM attitudes and computational thinking skills. Thinking styles and STEM attitudes are strong predictors of CT skills. Based on the results, we recommended that the conceptualization of CT be broadened to reflect its trans‐disciplinary nature within the context of STEM education. This study adds to the limited theoretical understanding of CT and CT‐predictors in higher education, which has been studied much less than in K‐12 education.

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Development and analysis of the Elementary Student Coding Attitudes Survey

Cited by 49 publications

References 47 publications

A scale for measuring middle school students' attitudes toward programming

A scale for measuring middle school students' attitudes toward programming

Computational identity and programming empowerment of students in computational thinking development

How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

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