Promoting pupils’ computational thinking skills and self-efficacy: a problem-solving instructional approach

2021 ◽  
Author(s):  
Hongliang Ma ◽  
Mei Zhao ◽  
Huixin Wang ◽  
Xinqi Wan ◽  
Terence W. Cavanaugh ◽  
...  
Keyword(s):  
Problem Solving ◽  
Self Efficacy ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Instructional Approach

scholarly journals Improving Novice Students’ Computational Thinking Skills by Problem-Solving and Metacognitive Techniques

2021 ◽  
Vol 20 (6) ◽  
pp. 88-108
Author(s):  
Nor Hasbiah Ubaidullah ◽  
Zulkifley Mohamed ◽  
Jamilah Hamid ◽  
Suliana Sulaiman ◽  
Rahmah Lob Yussof
Keyword(s):  
Problem Solving ◽  
Cognitive Skills ◽  
Teaching And Learning ◽  
Intervention Program ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Metacognitive Skills ◽  
Thinking Skill ◽  
Novice Students ◽  
Programming Courses

Admittedly, the teaching and learning of programming courses in the computer science and information technology programs have been extremely challenging. Currently, most instructors depend on either the problem-solving technique or the metacognitive technique to help students develop a range of cognitive skills, including metacognitive skills, which are important in the development of a strong computational thinking skill required for 21st-century learning. Studies focusing on the practices of instructors in using both techniques are scarce, thus motivating the researchers to carry out this study. This study was based on a qualitative approach involving a case-study design in which five (5) male and five (5) female instructors were selected from 10 pre-university centers in Malaysia as the respondents and participants in an intervention program. The research instruments used were an interview checklist and intervention guidelines. As anticipated, the findings showed that the activities of each technique could only help students develop certain sub-skills of the computational thinking skill, thus underscoring the need for instructors to integrate both techniques in their teaching practices. Thus, it could be reasoned that using either the metacognitive technique or the problem-solving technique alone would not be sufficient to help students develop strong computational thinking skills, as each technique has its strengths and weaknesses. Therefore, it becomes imperative for instructors to leverage the strengths of both techniques by integrating both of them in the teaching and learning of programming courses.

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.

Exploring Factors That Influence Computational Thinking Skills in Elementary Students’ Collaborative Robotics

2021 ◽  
pp. 073563312199247
Author(s):  
William H. Stewart ◽  
Youngkyun Baek ◽  
Gina Kwid ◽  
Kellie Taylor
Keyword(s):  
Problem Solving ◽  
Intrinsic Motivation ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Influential Factors ◽  
Educational Setting ◽  
School Students ◽  
Collaborative Robotics ◽  
Significant Relationships ◽  
5Th Grade

Recently educational robotics has expanded into curriculum beyond traditional STEM fields, and which can also be used to foster computational thinking (CT) skills. Prior research has shown numerous interdisciplinary benefits related to CT, however, these influential factors have often been investigated with relatively few variables. This study investigated factors that may lead to 4th and 5th grade elementary school students’ development of computational thinking skills in collaborative robotics activities by hypothesizing a model which proposed that a problem solving inventory, intrinsic motivation, and enjoyment were the main predictors of computational thinking skills. The model was then tested by surveying students with several psychometric inventories where a revised model was then constructed. The study found significant relationships between perceived competence and enjoyment, and learning motivation, and intrinsic motivation. Another important finding was that problem solving was a significant predictor of computational thinking skills. Results were interpreted with reference to implications for possible means of improving learning outcomes when using collaborative robotics in an educational setting.

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