A validity and reliability study of the computational thinking scales (CTS)

Korkmaz, Özgen; akir, Recep; zden, M. Yaar

doi:10.1016/j.chb.2017.01.005

Cited by 453 publications

(343 citation statements)

References 19 publications

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“…Bu üst düzey becerilerden bir tanesi de Bilgi İşlemsel Düşünmedir (Computational Thinking) (Philips, 2009;Wing 2010). Bilgi İşlemsel Düşünme, sadece bilgisayar bilimcilerinin değil tüm insanların sahip olmaları gereken bir beceri olarak görülmektedir (Korkmaz, Çakir, & Özden, 2017;Wing, 2006;Wing, 2008;Wing, 2010). …”

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Computer Programming Self-Efficacy Scale (Cpses) for Secondary School Students: Development, Validation and Reliability

Kukul¹,

Gökçearslan²,

Günbatar³

2017

Eğitim Teknolojisi Kuram Ve Uygulama

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Computer programming has been included in the curriculum of K12 education around the world and this has necessitated a tool for the assessment of the computer programming selfefficacy. Thus, this study aims to suggest the necessary scale for the field. In the scale development, the steps of classical measurement theory were applied. Following the expert review, the item pool was conducted with 233 students in a public secondary school which provides education to the age group of 12-14 in the school year 2014-2015. As a result of the study, a unidimensional 5-point Likert scale of 31 items was obtained. The factor loads varied between 0.47 and 0.71 and the explained variance rate was 41.15%. In the analysis of the internal consistency, sufficient values were found; the Cronbach alpha as 0.95 and the equivalent halves method result as 0.96. For the construct validity, exploratory and confirmatory factor analysis were applied and the result showed that the scale is valid and reliable. Günümüzde, bilişim teknolojilerindeki gelişmelerle insanların problemlere çözüm arayışları farklılaşmıştır. Uzun sürede bitirilebilecek bir iş ya da görev teknolojiyi kullanarak kısa sürede bitirebilmektedir. Dijital teknolojinin içerisinde büyüyen çocukların, sadece o teknolojiyi kullanmaları değil, gerekirse yeni teknolojiler üreterek üst düzey düşünme becerilerinin gelişmesi beklenmektedir (Kalelioğlu, 2015). Bu üst düzey becerilerden bir tanesi de Bilgi İşlemsel Düşünmedir (Computational Thinking) (Philips, 2009;Wing 2010). Bilgi İşlemsel Düşünme, sadece bilgisayar bilimcilerinin değil tüm insanların sahip olmaları gereken bir beceri olarak görülmektedir (Korkmaz, Çakir, & Özden, 2017;Wing, 2006;Wing, 2008;Wing, 2010). KeywordsBilgi İşlemsel Düşünme becerisinin öğrencilere kazandırılmasında sık kullanılan yöntemlerden bir tanesi, "Başlangıç Öğrenme Ortamları" olarak değerlendirilen görsel programlama araçlarıyla bilgisayar programlama öğretimidir (Weinberg, 2013). Programlama becerisi yaratıcı düşünme, problem çözme, mantıksal çıkarım gibi üst düzey düşünme becerilerinin geliştirilmesine olanak tanımaktadır (Fesakis & Serafeim, 2009;Fessakis, Gouli, & Mavroudi, 2013;Kay & Knaack, 2005). Bilgisayar programlama becerisinin öğrencilere sağladığı katkı, eğitimcilerin ve araştırmacıların ilgisini çekmiş (Gökçearslan & Alper, 2015), bu doğrultuda Avrupa ve Amerika'da erken yaşlar için bilgisayar programlama öğretimine yönelik ders ve etkinlikler üzerine yapılan çalışmalar artmıştır (Grover & Pea, 2013;Kafai & Burke, 2013). Birçok ülke erken yaşlar için bilgisayar programlamayı ulusal programlarına entegre etmeye başlamışlardır (Kalelioğlu, 2015).Geçmişte öğrencilere bilgisayar programlamanın öğretilmeye çalışılıp, sadece az sayıdaki öğrencinin başarılı olması (Resnick et al., 2009), "bu sefer de aynı sorunla karşı karşıya kalınır mı?" sorusunu akla getirmektedir. Bunun için öğrencilerin bilgisayar programlamaya yönelik düşünceleri ve bilgisayar programlamadaki başarılarının değerlendirilmesi gerekmektedir. Öğrencilerin öz-yeterl...

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“…One of these high-level skills is Computational Thinking (Philips, 2009;Wing 2010). Computational Thinking is considered as a skill that should be possessed not only by computer scientists, but everyone (Korkmaz, Çakir, & Özden, 2017;Wing, 2006;Wing, 2008;Wing, 2010).…”

Section: Introductionmentioning

confidence: 99%

Computer Programming Self-Efficacy Scale (Cpses) for Secondary School Students: Development, Validation and Reliability

Kukul¹,

Gökçearslan²,

Günbatar³

2017

Eğitim Teknolojisi Kuram Ve Uygulama

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“…• CT perceptions-attitudes scales: They are aimed at assessing the perceptions (e.g., self-efficacy perceptions) and attitudes of the subjects not only about CT, but also about related issues such as computers, computer science, computer programming, or even digital literacy. Among scales targeted to students, we can name the Computational Thinking Scales (CTS) (Korkmaz, Çakir, & Özden, 2017), the Computational Thinking Skills Scale (CTSS) (Durak & Saritepeci, 2018), or the Computer Programming Self -Efficacy Scale (CPSES) (Kukul, Gökçearslan, & Günbatar, 2017). When we are interested in assessing the perceptions and attitudes of teachers, the research work of Yadav, Mayfield, Zhou, Hambrusch, and Korb (2014) can be highlighted.…”

Section: Computational Thinking Assessment Toolsmentioning

confidence: 99%

Combining Assessment Tools for a Comprehensive Evaluation of Computational Thinking Interventions

González

Moreno-León²,

Robles

2019

Computational Thinking Education

123

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Given that computational thinking (CT) is still a blurry psychological construct, its assessment remains as a thorny, unresolved issue. Hence, in recent years, several assessment tools have been developed from different approaches and operational definitions of CT. However, very little research has been conducted to study whether these instruments provide convergent measurements, and how to combine them properly in educational settings. In response, we first review a myriad of CT assessment tools and classify them according to their evaluative approach. Second, we report the results of two convergent validity studies that involve three of these CT assessment tools, which come from different perspectives: the Computational Thinking Test, the Bebras Tasks, and Dr. Scratch. Finally, we propose a comprehensive model to evaluate the development of CT within educational scenarios and interventions, which includes the aforementioned and other reviewed assessment tools. Our comprehensive model intends to assess CT along every cognitive level of Bloom's taxonomy and throughout the various stages of typical educational interventions. Furthermore, the model explicitly indicates how to harmoniously combine the different types of CT assessment tools in order to give answer to the most common research questions in the field of CT Education. Thus, this contribution may lead scholars and policy-makers to perform accurate evaluation designs of CT according to their inquiry goals.

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“…Moreover, measurement of CT competence is most commonly based on summative assessment, such as questionnaires (Korkmaz, Çakir, & Özden, 2017) or test scores (Román-González, Pérez-González, & Jiménez-Fernández, 2017;Zhong, Wang, Chen, & Li, 2016), with little emphasis on formative assessment of programming processes to foster CT competence development. Besides, such assessments typically focus on individual outcomes.…”

Section: Ct and Programmingmentioning

confidence: 99%

Analysing computational thinking in collaborative programming: A quantitative ethnography approach

Ruis

et al. 2019

Computer Assisted Learning

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Computational thinking (CT), the ability to devise computational solutions for real‐life problems, has received growing attention from both educators and researchers. To better improve university students' CT competence, collaborative programming is regarded as an effective learning approach. However, how novice programmers develop CT competence through collaborative problem solving remains unclear. This study adopted an innovative approach, quantitative ethnography, to analyze the collaborative programming activities of a high‐performing and a low‐performing team. Both the discourse analysis and epistemic network models revealed that across concepts, practices, and identity, the high‐performing team exhibited CT that was systematic, whereas the CT of the low‐performing team was characterized by tinkering or guess‐and‐check approaches. However, the low‐performing group's CT development trajectory ultimately converged towards the high‐performing group's. This study thus improves understanding of how novices learn CT, and it illustrates a useful method for modeling CT based in authentic problem‐solving contexts.

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A validity and reliability study of the computational thinking scales (CTS)

Cited by 453 publications

References 19 publications

Computer Programming Self-Efficacy Scale (Cpses) for Secondary School Students: Development, Validation and Reliability

Computer Programming Self-Efficacy Scale (Cpses) for Secondary School Students: Development, Validation and Reliability

Combining Assessment Tools for a Comprehensive Evaluation of Computational Thinking Interventions

Analysing computational thinking in collaborative programming: A quantitative ethnography approach

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