Experiences in Learning Problem-Solving through Computational Thinking

Abstract

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).