scholarly journals Computational Thinking and Digital Games: Developing Skills With Fun

2020 ◽  
Vol 3 (1) ◽  
pp. 80
Author(s):  
Diego Zabot ◽  
Saulo Ribeiro de Andrade ◽  
Ecivaldo De Souza Matos
Keyword(s):  
Basic Education ◽  
Computational Thinking ◽  
Digital Games ◽  
Thinking Skills ◽  
Systematic Mapping ◽  
Literature Mapping ◽  
Puzzle Games ◽  
Computational Reasoning ◽  
Algorithmic Thinking

INTRODUCTION: Several researchers consider the importance of Computational Thinking being presented and developed from the earliest years of basic education and, furthermore, that digital games can be one of the vehicles to introduce it to children in schools. However, before developing new game solutions for this purpose, it is important to recognize how games can actually contribute to develop Computational Thinking, as well as to identify which skills have been worked on. OBJECTIVE: In this sense, this article presents the synthesis of a systematic mapping, whose objective was to identify how digital games can be used to develop Computational Thinking skills. METHOD: The objective was met by a systematic literature mapping executed by two reviewers and an expert. RESULTS: It was possible to identify some games used to stimulate the development of Computational Thinking skills, as well as the mechanics used by these games. CONCLUSION: It has been found that puzzle games are most commonly used to develop skills in Computational Reasoning. It has also been observed that the abilities of Abstraction and Algorithmic Thinking are the main skills developed in these games.

Assessing Algorithmic Thinking Skills in Early Childhood Education

2020 ◽  
pp. 104-139
Author(s):  
Kalliopi Kanaki ◽  
Michail Kalogiannakis ◽  
Dimitrios Stamovlasis
Keyword(s):  
Latent Class ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Theory And Practice ◽  
Second Grade ◽  
Environmental Study ◽  
Assessment Instruments ◽  
School Students ◽  
Skill Levels ◽  
Algorithmic Thinking

This chapter presents part of a wider project aimed at developing computational thinking assessment instruments for first and second grade primary school students. The applicability of the specific proposed tool, which concerns merely the algorithmic thinking (AT), was tested within the Environmental Study course (ESc). The main pillar of the work is the computational environment PhysGramming. The assessment of AT was based on mental tasks involving puzzles which require AT abilities. The AT test comprised of four puzzles with 4, 6, 9, and 12 pieces respectively, and the puzzle-solving performance was measured at the nominal level (success/failure). Latent class analysis (LCA), a robust multivariate method for categorical data, was implemented, which distinguished two clusters/latent classes corresponding to two distinct levels of AT. Moreover, LCA with covariates, such as gender, grade, achievement in ESc, and the use of plan revealed the association of the above variables with the AT skill-levels. Finally, the results and their implications for theory and practice are discussed.

Computational Thinking and Mathematics

2016 ◽  
pp. 853-865
Author(s):  
Thiago Schumacher Barcelos ◽  
Ismar Frango Silveira
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Basic Education ◽  
National Curriculum ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Educational Systems ◽  
Curriculum Guidelines ◽  
And Mathematics ◽  
The One

On the one hand, ensuring that students archive adequate levels of Mathematical knowledge by the time they finish basic education is a challenge for the educational systems in several countries. On the other hand, the pervasiveness of computer-based devices in everyday situations poses a fundamental question about Computer Science being part of those known as basic sciences. The development of Computer Science (CS) is historically related to Mathematics; however, CS is said to have singular reasoning mechanics for problem solving, whose applications go beyond the frontiers of Computing itself. These problem-solving skills have been defined as Computational Thinking skills. In this chapter, the possible relationships between Math and Computational Thinking skills are discussed in the perspective of national curriculum guidelines for Mathematics of Brazil, Chile, and United States. Three skills that can be jointly developed by both areas are identified in a literature review. Some challenges and implications for educational research and practice are also discussed.

scholarly journals The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction

2019 ◽  
Author(s):  
Nardie L. J. A. Fanchamps ◽  
Lou Slangen ◽  
Paul Hennissen ◽  
Marcus Specht
Keyword(s):  
Self Efficacy ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Preliminary Measurement ◽  
Grid Diagrams ◽  
Mathematical Problems ◽  
Measured Effect ◽  
Primary School Pupils ◽  
Types Of Instruction ◽  
Algorithmic Thinking

AbstractThis study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a problem in a way that a computer can process it. Programming robots offers specific affordances as it can be used to develop programs following a Sense-Reason-Act (SRA) cycle. The literature provides evidence that programming robots has the potential to enhance algorithmic thinking as a component of computational thinking. Specifically there are indications that pupils who use SRA-programming learn algorithmic skills better and achieve a higher level of self-efficacy in an open, scaffold learning environment than through direct instruction. In order to determine the influence of the instruction variant used, an experimental research design was made in which pupils solved algorithm-based mathematical problems (grid diagrams) in a preliminary measurement and their self-efficacy determined via a questionnaire. As an intervention, pupils learn to solve programming issues in pairs using “Lego NXT” robots and “Mindstorms” software in two instruction variants. The post-measurement consists of a Lego challenge, solving mathematical problems (grid diagrams), and a repeated self-efficacy questionnaire. This research shows an increase of our measures on algorithmic thinking dependent on the amount of SRA usage (though not significant). Programming using the SRA-cycle can be considered as the cause of the measured effect. The instruction variant used during the robotic intervention seems to play only a marginal role.

Computational Thinking and Mathematics

2014 ◽  
pp. 922-934
Author(s):  
Thiago Schumacher Barcelos ◽  
Ismar Frango Silveira
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Basic Education ◽  
National Curriculum ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Educational Systems ◽  
Curriculum Guidelines ◽  
And Mathematics ◽  
The One

On the one hand, ensuring that students archive adequate levels of Mathematical knowledge by the time they finish basic education is a challenge for the educational systems in several countries. On the other hand, the pervasiveness of computer-based devices in everyday situations poses a fundamental question about Computer Science being part of those known as basic sciences. The development of Computer Science (CS) is historically related to Mathematics; however, CS is said to have singular reasoning mechanics for problem solving, whose applications go beyond the frontiers of Computing itself. These problem-solving skills have been defined as Computational Thinking skills. In this chapter, the possible relationships between Math and Computational Thinking skills are discussed in the perspective of national curriculum guidelines for Mathematics of Brazil, Chile, and United States. Three skills that can be jointly developed by both areas are identified in a literature review. Some challenges and implications for educational research and practice are also discussed.

First-year engineering students' computational reasoning abilities

2022 ◽  
Vol 1 (2) ◽  
Author(s):  
Concepcion Rebollar ◽  
Carolina Varela ◽  
Olatz Eugenio
Keyword(s):  
Critical Thinking ◽  
Problem Solving ◽  
Engineering Students ◽  
Computational Thinking ◽  
First Year ◽  
Reasoning Abilities ◽  
New Students ◽  
Measurement And Evaluation ◽  
Computational Reasoning ◽  
Algorithmic Thinking

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.

scholarly journals Ten Years of Initiatives to Promote Computational Thinking: A Systematic Mapping of Literature

2020 ◽  
Vol 3 (1) ◽  
pp. 95
Author(s):  
Júlia S. B. Ortiz ◽  
Roberto Pereira
Keyword(s):  
Basic Education ◽  
Data Extraction ◽  
Computational Thinking ◽  
Systematic Mapping ◽  
The Public ◽  
The Usa ◽  
Analysis Of Results ◽  
Research Questions ◽  
New Research ◽  
Selection Of

INTRODUCTION: Computational Thinking is a problem solving skill that became well known after Wing's article in 2006. Since then, several researchers have argued this way of thinking can be useful to all people, and much research has been done to promote the development of this skill with different audiences. OBJECTIVE: To discover the state of art of the initiatives carried out in the last decade to promote the development of Computational Thinking, inside and outside Brazil, regardless of the public addressed and the method applied. METHOD: A systematic mapping of the literature was carried out comprising three steps of selection of articles to proceed with data extraction and analysis of results. Three international databases and one national were included to search articles published between 2007 and 2017, in Portuguese and English. From a total of 468 articles, 46 were selected for data extraction and analysis. RESULTS: Mapping allowed us to answer seven research questions, showing, for example, that the USA and Brazil stand out in quantity of research. Additionally, they presented important differences between the duration of the research, target audience(s) and the tools used. We were able to identify that research has grown in number and diversity. Conversely, initiatives in multi and transdisciplinary contexts are still lacking, and little attention is paid to the public in less favored contexts. CONCLUSION: Computational Thinking is a growing topic of research and knowing the initiatives published in these 10 years of research helps in the elaboration of new research, mainly indicating opportunities to be explored. Especially for Brazil, it is necessary to approach students beyond basic education, to explore the transdisciplinary potential of Computational Thinking, and to carry out research of longer duration.

scholarly journals The Effect of Algorithm Education on Students’ Computer Programming Self-Efficacy Perceptions and Computational Thinking Skills

2020 ◽  
Vol 3 (3) ◽  
pp. 19-32
Author(s):  
PINAR MIHCI Türker ◽  
Ferhat Kadir Pala
Keyword(s):  
Self Efficacy ◽  
Teacher Candidates ◽  
Computer Programming ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Rank Test ◽  
Signed Rank ◽  
Algorithmic Problems ◽  
Signed Rank Test ◽  
Algorithmic Thinking

In this study, the effect of algorithm education on teacher candidates’ computational thinking skills and computer programming self-efficacy perceptions were examined. In the study, one group pretest posttest experimental design was employed. The participants consisted of 24 (14 males and 10 females) teacher candidates, majoring in Computer Education and Instructional Technology (CEIT). In order to determine the teacher candidates’ computer programming self-efficacy perceptions, the Computer Programming Self-Efficacy Scale was used, whereas Computational Thinking Skills Scale was used to determine their computational thinking skills. The Wilcoxon Signed-Rank Test was used to analyze the differences between pretest and posttest scores of students' computer programming self-efficacy perceptions and computational thinking skills. Throughout the practices, 10 different algorithmic problems were presented to the students each week, and they were asked to solve these problems using flow chart. For 13 weeks, 130 different algorithmic problems were solved. Algorithm education positively and significantly increased students' simple programming tasks, complex programming tasks and programming self-efficacy perceptions. On the other hand, algorithm education had a positive and significant effect only on students’ algorithmic thinking sub-dimension but did not have any effect on other sub-dimensions and computational thinking skills in general.  

scholarly journals An Analysis of Students’ Computational Thinking Skills on The Number Patterns Lesson during The Covid-19 Pandemic

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Dwi Fitriani Rosali ◽  
Didi Suryadi
Keyword(s):  
Computational Thinking ◽  
Thinking Skills ◽  
Problem Decomposition ◽  
Education Curriculum ◽  
Descriptive Research ◽  
Educational Framework ◽  
Type Test ◽  
8Th Grade ◽  
Qualitative Descriptive ◽  
Algorithmic Thinking

The development of the education curriculum in Indonesia makes students must have skills so that they can compete globally, especially in the 21st century. The development is closely related to technology and information. One of skills that support the development of technology and information is the <em>computational thinking</em> skills. This study aims to analyze students’ <em>computational thinking</em> skills on the number patterns lesson during the Covid-19 pandemic. This study was qualitative-descriptive research with the subjects of 4 students from 8th grade in Makassar. The instruments used in this study were a test of the <em>computational thinking</em> skills in the form of essay type test on the number patterns lesson and interview guidance. The results of this study indicated that all subjects met the first indicator of problem decomposition and one subject met the second indicator of problem decomposition, all subjects met the indicator of pattern recognition, three subjects met the indicator of abstraction and generalization, all subjects met the first indicator of algorithmic thinking and two subjects met the second indicator of algorithmic thinking on <em>computational thinking</em> skills. Thus, students’ <em>computational thinking</em> skills during the Covid-19 pandemic were still low, so an educational framework is needed to improve students’ <em>computational thinking</em> skills.

Assessing Algorithmic Thinking Skills in Early Childhood Education

2022 ◽  
pp. 488-523
Author(s):  
Kalliopi Kanaki ◽  
Michail Kalogiannakis ◽  
Dimitrios Stamovlasis
Keyword(s):  
Latent Class ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Theory And Practice ◽  
Second Grade ◽  
Environmental Study ◽  
Assessment Instruments ◽  
School Students ◽  
Skill Levels ◽  
Algorithmic Thinking

This chapter presents part of a wider project aimed at developing computational thinking assessment instruments for first and second grade primary school students. The applicability of the specific proposed tool, which concerns merely the algorithmic thinking (AT), was tested within the Environmental Study course (ESc). The main pillar of the work is the computational environment PhysGramming. The assessment of AT was based on mental tasks involving puzzles which require AT abilities. The AT test comprised of four puzzles with 4, 6, 9, and 12 pieces respectively, and the puzzle-solving performance was measured at the nominal level (success/failure). Latent class analysis (LCA), a robust multivariate method for categorical data, was implemented, which distinguished two clusters/latent classes corresponding to two distinct levels of AT. Moreover, LCA with covariates, such as gender, grade, achievement in ESc, and the use of plan revealed the association of the above variables with the AT skill-levels. Finally, the results and their implications for theory and practice are discussed.

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