computational thinking
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2022 ◽  
Vol 11 (2) ◽  
pp. 639-652
Saralah Sovey ◽  
Kamisah Osman ◽  
Mohd Effendi

<p style="text-align: justify;">Computational thinking (CT) is a method for solving complex problems, but also gives people an inventive inspiration to adapt to our smart and changing society. Globally it has been considered as vital abilities for solving genuine issues successfully and efficiently in the 21st century. Recent studies have revealed that the nurture of CT mainly centered on measuring the technical skill. There is a lack of conceptualization and instruments that cogitate on CT disposition and attitudes. This study attends to these limitations by developing an instrument to measure CT concerning dispositions and attitudes. The instruments' validity and reliability testing were performed with the participation from secondary school students in Malaysia. The internal consistency reliability, standardized residual variance, construct validity and composite reliability were examined. The result revealed that the instrument validity was confirmed after removing items. The reliability and validity of the instrument have been verified. The findings established that all constructs are useful for assessing the disposition of computer science students. The implications for psychometric assessment were evident in terms of giving empirical evidence to corroborate theory-based constructs and also validating items' quality to appropriately represent the measurement.</p>

2022 ◽  
Vol 22 (2) ◽  
pp. 1-27
Rina P. Y. Lai

Computational Thinking (CT ), entailing both domain-general and domain-specific skills, is a competency fundamental to computing education and beyond. However, as a cross-domain competency, appropriate assessment design and method remain equivocal. Indeed, the majority of the existing assessments have a predominant focus on measuring programming proficiency and neglecting other contexts in which CT can also be manifested. To broaden the promotion and practice of CT, it is necessary to integrate diverse problem types and item formats using a competency-based assessment method to measure CT. Taking a psychometric approach, this article evaluates a novel computer-based assessment of CT competency, Computational Thinking Challenge. The assessment was administered to 119 British upper secondary school students ( M = 16.11; SD = 1.19) with a range of prior programming experiences. Results from several reliability analyses, a convergent validity analysis, and a Rasch analysis, provided evidence to support the quality of the assessment. Taken together, the study demonstrated the feasibility to expand from traditional assessment methods to integrating multiple contexts, problem types, and item formats in measuring CT competency in a comprehensive manner.

Ceylan Zhao ◽  
Timothy Burgess

In this research, we looked at the cognitive and behavioral effects of playing Penguin Go, a video game that was created to help middle school kids improve their computational thinking (CT) abilities. Apart from the general efficacy of the game, we looked at the effects of a single game feature—constraints on the amount of blocks that may be used in a solution. Students' CT abilities increased dramatically after playing Penguin Go for fewer than two hours, according to the findings, but the extra limits had no meaningful effect on learning. Furthermore, although the game as a whole had no effect on students' views toward computer science, the limitations condition of the game had a detrimental effect on students' attitudes toward computer science. The outcomes of this study, as well as suggested possibilities for future research in the area of employing these sorts of games to build computational thinking abilities, are reviewed.

Concepcion Rebollar ◽  
Carolina Varela ◽  
Olatz Eugenio

Computational thinking is an essential skill set for today's students, given the digital age in which we live and work (CT). Without a precise definition, it is generally understood to be a collection of abilities and attitudes required to deal with difficulties in any aspect of life, whether or not a computer is involved. Measurement and evaluation of students' progress in CT abilities are critical, and this can only be done using instruments that have been tested and shown to work before. New students at the Basque Country's University of the Basque Country's Engineering Degrees are tested for critical thinking, algorithmic thinking, problem solving, cooperation and creativity using a previously proven tool.

2022 ◽  
pp. 073563312110604
Jian-Wen Fang ◽  
Dan Shao ◽  
Gwo-Jen Hwang ◽  
Shao-Chen Chang

Scholars believe that computational thinking is one of the essential competencies of the 21st century and computer programming courses have been recognized as a potential means of fostering students’ computational thinking. In tradition instruction, PFCT (problem identification, flow definition, coding, and testing) is a commonly adopted procedure to guide students to learn and practice computer programming. However, without further guidance, students might focus on learning the syntax of computer programming language rather than the concept of solving problems. This study proposes a peer-assessment-supported PFCT (PA-PFCT) approach for boosting students’ computer programming knowledge and computational thinking awareness. A quasi-experiment was conducted on a computer programming course in a high school to evaluate its influence on students’ learning achievement, computational thinking awareness, learning motivation, and self-efficacy. An experimental group of 51 students learned with the proposed approach, while a control group of 49 students learned with the traditional PFCT (T-PFCT) approach. The experimental results show that the proposed approach significantly enhanced the students’ computational thinking awareness, learning motivation, and self-efficacy, while not having significant impacts on their computer programming knowledge test scores.

Nina Bonderup Dohn ◽  
Yasmin Kafai ◽  
Anders Mørch ◽  
Marco Ragni

2022 ◽  
Vol 12 (1) ◽  
pp. 39
Jesús Acevedo-Borrega ◽  
Jesús Valverde-Berrocoso ◽  
María del Carmen Garrido-Arroyo

Interest in computational thinking (CT) in the scientific community has increased significantly in the last 4 years, as evidenced by the numerous systematic reviews carried out. However, there is a lack of reviews that update the emerging conceptualization of CT and which also examine the roles of the school curriculum and teachers in the face of CT. A systematic literature review (SLR) consists of a collection of research conducted according to previous criteria with the aim of answering research questions with validity and quality. For this reason, the PRISMA-ScR statement was followed. Articles published in scientific journals, from Scopus and WoS, between January 2018 and August 2021 were included, in the English or Spanish language. The initial search resulted in 492 articles, to which the inclusion-exclusion criteria were applied. The final sample of texts for the present systematic review was n = 145. The texts were analyzed from three perspectives: conceptual, documentary and pedagogical. Thus, a renewal of previous literature reviews was carried out, updating the situation with research from recent years and new data, obtained to contribute to the collective intelligence on methodological strategies (80% of the sample was divided into “plugged” and “unplugged”); educational (more than 50% studied CT evaluation); and resources, including a collection of more than 119 educational resources.

2022 ◽  
Vol 8 (1) ◽  
pp. 114-118
Rif'ati Dina Handayani ◽  
Sri Handono Budi Prastowo ◽  
Trapsilo Prihandono ◽  
Lailatul Nuraini ◽  
Bambang Supriadi ◽  

Abstraction is the primary key in computational thinking. This study aims to analyze students’ computational thinking skills of abstraction on the concept of kinematics. The data were collected through students’ project documents and interviews. The data is examined using a content analysis approach that emphasizes writing, verbal, or visual communication. The results revealed that students’ abstraction skills were evident in collecting data and analyzing, and recognizing patterns but were less visible in building models or simulations. Abstraction skills can be used as a foundation and framework for viewing a concept in physics not only in mathematics or formulas views but as a data iterative relationship. This research is expected to provide an overview for physics instructors to integrate computational thinking in their learning classroom

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