Abstract:

As digital technologies are constantly integrated into essential daily-life tasks, Computational thinking (CT) is regarded as a new digital literacy fundamental for coping with the 21st century’s challenges. Most widely, CT is defined as thinking activities that are enabled by applying the basic concepts of computational science, including problem-solving, system design, and the analysis of human behavior. Mainly, CT activates cognitive skills that represent problems and their solutions as computational steps and algorithms. CT aims to understand the mechanisms of digital technologies to formulate and solve problems in various contexts. Therefore, it should not be confused with computer programming, which seeks to analyze a situation and design its solution by implementing a specific programming language through coding. As students engage in CT, they practice abstract, algorithmic, and logical thinking and thus develop cognitive skills that enable them to become more efficient in solving complex and open-ended problems within and across disciplines.

Primarily, CT involves problem-solving processes that activate the skills of abstraction, generalization, decomposition, algorithmic thinking, and debugging. Abstraction removes characteristics or attributes from an object or entity to reduce them to a set of essential factors. Generalization is the skill of formulating a solution in generic terms to be applied to various problems. Decomposition refers to the skill of breaking problems down into small parts to make them easier to solve. Algorithmic thinking is a skill in writing a step-by-step sequence of instructions for a solution or process. Additionally, the algorithmic notions of sequencing (i.e., the skill to put actions in the correct sequence) and algorithmic notions of the flow of control (i.e., the order in which instructions are executed) are considered essential elements of CT. Finally, debugging is the skill to identify, remove, and fix errors.

Although there has been an increased interest during the last years in integrating Computational Thinking (CT) in school curricula, the computational thinking theory is still developing. Educational Robotics (ER) is increasingly used in classrooms to develop students’ CT skills. However, the existing body of research does not provide robust empirical evidence on the effect of specific instructional interventions in ER to enhance CT. This study examined the development of CT skills of primary-school children aged 6, 9, and 12 when doing robotic activities with Dash and Dot robots within the context of two teaching interventions. The findings suggest that the teaching technique affects children’s CT performance. Also, the study reports a statistically significant interaction between the teaching intervention and children’s age regarding their assessment of CT tasks. Study findings contribute quantitative evidence to the literature on how ER can be used to develop CT in primary students. In addition, the study has practical significance for curriculum developers, instructional leaders, and classroom teachers, as they can use the results of this study to design curricula and classroom activities with a focus on the broader set of CT skills.

Keywords:

Computational thinking, robotics, primary education.