Abstract
Computational thinking (CT) has become a vital approach to problem-solving. This method has been proven successful in various areas, especially science, technology, engineering, mathematics (STEM), and professional development. The integration of CT in education provides a practical approach to solving problems. This concept paper investigated the various uses of instructional techniques and programming tools to enhance CT skills used in previous empirical research. CT consists of four main pillars: decomposition, which refers to breaking down identified problems into smaller parts; pattern recognition, which involves finding occurring patterns that can be seen; abstraction through identification of important details and removing unnecessary information; and algorithm, where a step-by-step procedure is solution is made. By exploring instructional strategies and programming environments, this paper outlines the possible impacts of these instructional strategies, games, and programming environments on improvement in CT skills, thus providing a theoretical basis for future empirical studies. The strength and combination of these approaches provide a comprehensive learning experience. This paper also suggests instructional techniques and programming tools to enhance underexplored CT skills based on research gaps.
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