A systematic mapping study on teaching and learning Computational Thinking through programming in higher education

Abstract

Computational Thinking (CT) through programming in higher education is considered an important skill for students to become problem solvers and thrive in the new digital workplace. Despite the wide interest, a systematic map of CT through programming in higher education is still missing. The aim of this study is twofold. First, we aim to provide a systematic map of the relevant research by identifying the areas and sub-areas of CT through programming teaching and learning in higher education. Second, we aim to investigate these areas based on two dimensions: their evolution over the years and the branches to which CT is applied. For this purpose, we apply a systematic mapping methodology. Main results include the identification of the CT areas of Knowledge Base, Assessment, Learning Strategies, Tools, Factors and Capacity Building. Of these, Knowledge Base, Assessment and Tools have significantly evolved throughout the years, while Capacity Building has only recently emerged. In addition, the introduction of CT to undergraduate students and preservice teachers differs mainly in the tools used and the CT elements that are assessed. The study contributes to the field by providing a structured type of research conducted and identifying gaps and opportunities for future research.