A Valid and Reliable Scale for Developing Programming-Oriented Computational Thinking

Abstract

In this research, a scale was developed to determine the programming-oriented computational thinking skills of university students. The participants were 360 students studying in various departments at different universities in Turkey for computer programming. The scale consists of 33 items under conceptual knowledge, algorithmic thinking, and evaluation subscale. While there was no significant difference between the students’ conceptual knowledge and algorithmic thinking skills, the evaluation skills of male students differed significantly compared to females. Programming experience has a significant effect on conceptual knowledge, algorithmic thinking, and evaluation. The algorithmic thinking skills of the students who have low, middle, and high-level programming experience differed significantly. In terms of the development of conceptual knowledge and evaluation skills, it was observed that students should have at least one year of programming experience, but this experience will not make a significant difference if it is four years or more. It is thought that this scale, which is structured for different applications (e.g., web, game, robot) and learning environments (e.g., text, block) within the framework of its programming capabilities (conceptual, semantic, strategic knowledge), will contribute significantly to the evaluation of computational thinking as programming oriented.

Tendencies towards Computational Thinking: A Content Analysis Study

“…In her research, Yeni (2018) stated that students benefited from writing code, tests, observation, code block interpretation, ordering code blocks and open-ended questions to determine their level of understanding of programming terms depending on CT. While tests consisting of multiple choice and open-ended questions were used frequently in previous research (Atmatzidou & Demetriadis, 2016;Chen et al, 2017;Grover et al, 2014), scales for different student levels were also developed by researchers (Korkmaz et al, 2017;Kukul & Karataş, 2019;Yağcı, 2019;Kılıç et al, 2021). Especially in block-based programming environments such as Scratch, software such as Dr Scratch and Scrape are also used to evaluate the code sets quickly created by the students and to provide quick feedback to the students (Moreno-León et al, 2015;Wolz, 2011).…”

“…These tools changed as process and result oriented (Yeni, 2018). Scales (Kılıç, Gökoğlu, & Öztürk, 2021;Korkmaz, Çakir, & Özden, 2017;Kukul & Karataş, 2019;Yağcı, 2019) and tests (Atmatzidou & Demetriadis, 2016;Chen, Shen, Barth-Cohen, Jiang, Huang, & Eltoukhy, 2017) were generally used in outcome-based assessments. In process-oriented evaluations, different evaluation models were preferred (Basawapatna, Koh, Repenning, Webb, & Marshall, 2011;Brennan & Resnick, 2012;Koh, Basawapatna, Bennett, & Repenning, 2010;Seiter & Foreman, 2013).…”

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

“…It includes 29 items, which are distributed into five subscales. This widely‐used scale is a general CT evaluation method (Kilic et al, 2021; Lin et al, 2021). We performed a back‐to‐back translation whereby experts in both Chinese and English helped check the language's accuracy and coherence.…”

“…evaluation method (Kilic et al, 2021;Lin et al, 2021). We performed a back-to-back translation whereby experts in both Chinese and English helped check the language's accuracy and coherence.…”

Exploring relationships among students' computational thinking skills, emotions, and cognitive load using simulation games in primary education

“…A valid and reliable tool for examining CT skills was developed by Kılıç et al (2021). The CT scale uses a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).…”