Computational Thinking, 21st Century Skills, and Robotics

Introduction

Computational thinking is an essential skill for the 21st century learner, but is seemingly underdeveloped within the standards of the education system. “Computational thinking (CT) is a transversal and complex competence that goes beyond the use of computers and writing code. It is considered an ideal medium for the development of 21st-century skills” (Acevedo-Borrega et al., 2022, p. 1). Critical thinking, collaboration, communication, and creativity linked with problem-solving creates an extensive toolkit for engagement for all in the classroom. Computational thinking skills are molded in many different and diverse forms and can be applied to all areas of computer literacy. The computer literacy environment unfolds the understanding and application attributed to computational thinking. Nicoletti and Suemasu (2021) stated,

Using analytic and algorithmic concepts and strategies, computational thinking is related to computer literacy with strengths in formulating, analyzing, and solving problems. The aim is to establish a channel for students to enhance their ability to formulate questions, articulate answers, and solve problems. According to Witherspoon et al. (2017), computational thinking brings to the classroom exciting and innovative activities, including robotics, through hands-on application platforms not only in the science and mathematics curriculum, but also in language arts, visual arts, social studies, foreign language and more. Within the past few years, the momentum of computational thinking integration within the K-12 education system is slowly extending and infiltrating across the STEM fields, in which the computational thinking skillset gap is quite evident at the intermediate school level (Computer Science Teachers Association [CSTA], 2017; Grover & Pea, 2013).

The educational field places the essence of the computer combined with abstract innovation to drive understanding and engagement in the power of thinking. Hence, big ideas emerge and explode through innovative disruptive paradigms to turnkey the status quo in future-drive classrooms. According to Papert (1993), “You can’t think seriously about thinking without thinking about thinking about something” (p. 10). In society, a natural human method of understanding is thinking something through, from start to finish. Kordaki and Kakavas (2017) explained that a specific way of thinking reverts to the relationship between abstraction and the orderly process of algorithmic problem-solving, which contribute either directly or indirectly to the learner mastering skills involved with computational thinking. It is all about making computing cool and abstractions coming alive.

Computational Thinking

Jeanette Wing, a forerunner in the field of computer science, promoted computational thinking in 2006 as a fundamental and operational stepping stone in human analytical skill and thought process as it relates to computer science and all professional fields. Fields such as engineering, medicine, manufacturing, education, finance, health science, and cybersecurity, utilize some form of computational thinking every day. With that ideology, Wing (2006) described computational thinking in terms of (a) abstraction, (b) decomposition, (c) system analysis, and (d) modularity to include more abstract ideology specifications. Within her research studies, Wing (2006) realized that focusing just on the mathematical aspects of solving problems was not sufficient, whereas within the computational thinking structure there was an intersection between logical thinking and systems thinking, allowing for the mixing of many other thought processes such as “compositional reasoning, pattern matching procedural thinking, and recursive thinking” (p. 1). Computational thinking was instrumental in formulating the framework evident by reconstructing, rethinking, and addressing the mental process of inquiry into solving all types of real-world problems (Lee et al., 2014).