scholarly journals Experiences in Learning Problem-Solving through Computational Thinking

2018 ◽  
Vol 18 (02) ◽  
pp. e15 ◽  
Author(s):  
Jacqueline M. Fernández ◽  
Mariela E. Zúñiga ◽  
María V. Rosas ◽  
Roberto A. Guerrero
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Computational Thinking ◽  
First Year ◽  
Learning Problem ◽  
Introductory Course ◽  
San Luis ◽  
National University ◽  
And Mathematics ◽  
Problem Solving Process

Computational Thinking (CT) represents a possible alternative for improving students’ academic performance in higher level degree related to Science, Technology, Engineering and Mathematics (STEM). This work describes two different experimental proposals with the aim of introducing computational thinking to the problem solving issue. The first one was an introductory course in the Faculty of Physical, Mathematical and Natural Sciences (FCFMyN) in 2017, for students enrolled in computer science related careers. The other experience was a first attempt to introduce CT to students and teachers belonging to not computer related faculties at the National University of San Luis (UNSL). Both initiatives use CT as a mean of improving the problem solving process based on the four following elementary concepts: Decomposition, Abstraction, Recognition of patterns and Algorithm. The results of the experiences indicate the relevance of including CT in the learning problem solving issue in different fields. The experiences also conclude that a mandatory CT related course is necessary for those careers having computational problems solving and/or programming related subjects during the first year of their curricula. Part of this work was presented at the XXIII Argentine Congress of Computer Science (CACIC).

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.

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.

scholarly journals Developing an Educational Game to support Cognitive Learning

2014 ◽  
Vol 3 (6) ◽  
Author(s):  
Mary Kiernan ◽  
Cagin Kazimoglu ◽  
Liz Bacon ◽  
Lachlan Mackinnon
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Computational Thinking ◽  
Cognitive Learning ◽  
Educational Game ◽  
First Year ◽  
Logical Thinking ◽  
Introductory Programming ◽  
Programming Students

This paper outlines how an educational game can be used to support the learning of programming within the Computer Science (CS) discipline and reports on the qualitative results of a series of rigorous studies conducted through using this game on first year introductory programming students.  Although this paper applies to the CS discipline computational thinking (CT) is an intrinsic part of the games process applicable to any discipline.  This is because CT is a problem solving approach which combines logical thinking with CS concepts to produce a recipe for solving problems in any discipline regardless of where the problem lies.   

scholarly journals University Students' Attitude and Anxiety Towards Computer Science Education through Computational Thinking

2021 ◽  
Vol 12 (6) ◽  
pp. 755-760
Author(s):  
Youngseok Lee Et.al
Keyword(s):  
Science Education ◽  
Problem Solving ◽  
Computer Science ◽  
Learning Effect ◽  
Computer Science Education ◽  
Computational Thinking ◽  
Average Score ◽  
Problem Solving Skills ◽  
Programming Education ◽  
Learning Technique

Background/Objectives: In the 21st century, communication and collaboration between people is an important element of talent. As artificial intelligence (AI), the cutting edge of computer science, develops, AI and collaboration will become important in the near future. Methods/Statistical analysis: To achieve this, it is necessary to understand how artificial AI based on computer science works, and how problem-based programming education is effective in computer science education. In this study, 177 college students who received programming education focused on problem-solving learning were identified with computational thinking (CT) at the beginning of the semester, and their satisfaction and post-education satisfaction survey showed that their attitudes and interests influenced their education. Findings: To pretest the learners, they were diagnosed using a measurement sheet. The learners’ current knowledge statuses were checked, and the correlation between the evaluation results, based on what was taught according to the problem-solving learning technique, was analyzed according to the proposed method. The analysis of the group average score of the learners showed that the learning effect was significant. The results of the measures of the students’ CT at the beginning of the semester were correlated with problem-solving learning, teaching method, lecture satisfaction, and other environmental factors. The ability to solve a variety of problems using CT will become increasingly important, so if students seek to improve their satisfaction with problem-solving learning techniques for computer science education, it will be possible for universities to develop convergence talent more efficiently. Improvements/Applications: if you pursue a problem-solving learning technique and a way to improve students’ satisfaction, it will help students improve their problem-solving skills. If the method of deriving and improving computational thinking ability in this paper is applied to computer education, it will induce student interest, thereby increasing the learning effect.

scholarly journals Computational Thinking in Mathematics and Computer Science: What Programming Does to Your Head

2021 ◽  
Vol 11 (1) ◽  
pp. 346-363
Author(s):  
Al Cuoco ◽  
Paul Goldenberg
Keyword(s):  
Computer Science ◽  
Classical Result ◽  
Computational Thinking ◽  
Computer Programs ◽  
The Other ◽  
Greatest Common Divisor ◽  
Euclid’S Algorithm ◽  
And Mathematics ◽  
Euclid's Algorithm

How you think about a phenomenon certainly influences how you create a program to model it. The main point of this essay is that the influence goes both ways: creating programs influences how you think. The programs we are talking about are not just the ones we write for a computer. Programs can be implemented on a computer or with physical devices or in your mind. The implementation can bring your ideas to life. Often, though, the implementation and the ideas develop in tandem, each acting as a mirror on the other. We describe an example of how programming and mathematics come together to inform and shape our interpretation of a classical result in mathematics: Euclid's algorithm that finds the greatest common divisor of two integers.

scholarly journals A game proposal to develop Computational Thinking and environmental awareness

2020 ◽  
Vol 3 (1) ◽  
pp. 111
Author(s):  
Fernanda Pires ◽  
Fabrizio F. Honda ◽  
Guibson Silva ◽  
Rafaela Melo ◽  
Rosiane De Freitas ◽  
...  
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Undergraduate Students ◽  
Development Process ◽  
School Context ◽  
Cognitive Structure ◽  
Computational Thinking ◽  
Educational Game ◽  
Agile Methodologies ◽  
Directed Learning

INTRODUCTION: Discussions around the development of Computational Thinking have demanded efforts to propose methods, techniques and tools that can assist in this process, especially in the school context. This paper deals with the development of an educational game with the theme "Environment and Sustainability" involving the pillars of Computational Thinking. OBJECTIVE: The game aims to assist the development of Computational Thinking by solving the problems to be solved in the missions of the heroine Sofia. The proposal for creating the game points out ways to create tools that work across curriculum themes. Tactics usually incorporated into the algorithmic language that permeate the problem solving processes in Computer Science be used. METHOD: The creation of the game followed a development process based on agile methodologies. The human cognitive structure was considered together with the intertwining between the games and the four pillars of Computational Thinking for the composition of an architecture applied to the game map. RESULTS: The evaluation of the game map regarding the "algorithmization" of the phases fulfilled the requirements regarding the location of the pillars (Decomposition, Pattern, Abstraction and Algorithm). The game, as an entertainment product, was evaluated using the E-Game Flow which pointed to acceptance by the evaluators (undergraduate students in the Computing area) and some suggestions for improvement were recorded. CONCLUSION: Games are presented as an important tool regarding the development process of Computational Thinking considering the engagement they can cause in their users and the possibilities of using their mechanics for directed learning.

A New Approach for Assessing Learners in an Online Problem Based Learning Environment

2020 ◽  
pp. 307-324
Author(s):  
Houda Tadjer ◽  
Yacine Lafifi ◽  
Hassina Seridi-Bouchelaghem
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Small Groups ◽  
Learning Process ◽  
Problem Based Learning ◽  
Point Of View ◽  
New Method ◽  
Science Department ◽  
New Approach ◽  
Problem Solving Process

Problem-based learning (PBL) is an approach that improves students' skills in problem solving. The application of PBL as an approach of teaching in a class requires students' presence; such constraint cannot be fulfilled by all students. Therefore, it is important to avoid this problem by implementing an online PBL environment where students are grouped remotely and work together to solve a problem proposed by the teacher. This will guide the learning process of the learners and can evaluate their solution. In reality, we can find members who do not really contribute to solve a problem. From this point of view, the teacher's evaluation will not be adequate to estimate the contribution of the learner in the solution of a given problem. Therefore, it is important to think of another way for assessing learners' solution. So, the challenge is to implement an online PBL environment and to propose a new method for assessing students. In this paper, the authors present their system called Problearn. The developed system allows students to solve problems remotely in small groups. Furthermore, the system evaluates each student based on his behavioral profiles during the problem-solving process. To do so, the system must keep track of different actions carried out by the students. This system has been tested by students of a computer science department where they achieved very good results.

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.

Examining the Current Definitions of Computational Thinking

2022 ◽  
pp. 224-252
Author(s):  
Kadir Demir ◽  
Cansu Çaka ◽  
Nihal Dulkadir Yaman ◽  
Hakan İslamoğlu ◽  
Abdullah Kuzu
Keyword(s):  
Problem Solving ◽  
Computer Science ◽  
Human Behavior ◽  
Daily Life ◽  
Computational Thinking ◽  
Current Situation ◽  
Early Age ◽  
Algorithmic Problem ◽  
The World ◽  
Basic Concepts

Computational thinking involves understanding human behavior, designing systems and solving problems by applying the mental tools that reflect the computer science and basic concepts. Development of frameworks of computational thinking helps integrate computational thinking into education and daily life. It is important for students to start using the computational methods and tools as well as algorithmic problem solving in their educations from kindergarten level to university level. Importance of training on programming at early age was explained. In addition, the current situation of programming in education in the world was reviewed. Then curricula and projects in different countries were summarized. It is necessary to start studies at an early age to help individuals acquire these skills.

Educational Robotics and Computational Thinking Development

2020 ◽  
pp. 310-338
Author(s):  
Timoleon Theofanellis ◽  
Evagelia Voulgari ◽  
Savvas Tsolakis
Keyword(s):  
Pattern Recognition ◽  
Problem Solving ◽  
Computational Thinking ◽  
Robotic Systems ◽  
Educational Robotics ◽  
Two Systems ◽  
Do It Yourself ◽  
Problem Solving Process ◽  
The Way

Computational thinking (CT) is a problem-solving process that refers to characteristics such as de-composition, abstraction, pattern recognition, and algorithms. This chapter focuses on educational robotics and their use in developing CT. Firstly, the importance of CT is analyzed along with the way it is applied in the classroom. It goes on discussing the way the introduction of educational robotic systems in education affect CT and the importance of the do-it-yourself philosophy. It presents two widely used educational robotic systems follows, Arduino and Lego EV3, along with examples of their relationship with CT development. The chapter finishes with a comparison of the two systems regarding the easiness and difficulties of using them.

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