A systemic review of Problem-Based Learning (PBL) and Computational Thinking (CT) in teaching and learning

Abstract

Because of its educational benefits for both learners and teachers, Problem-Based Learning (PBL) and Computational Thinking (CT), teaching paradigms, and problem-solving methodologies have become widely used in teaching and learning. However, research on its integration into the teaching and learning process is still sparse, leaving educators with few guidelines for using constructive learning theory techniques. This study aims to thoroughly review and determine the country of application, learner level, PBL and CT dimensions, and learning methodologies that can lead to the successful implementation of PBL-CT. From 2017 to 2022, this study tracks relevant and published articles to identify gaps in the implementation of PBL-CT and maps their history into a taxonomy that can be used to guide future research. Limited study has yet been published that specifically describes the suitable PBL-CT framework or paradigm. Most articles deal with computing, followed by STEM (Science, Technology, Engineering, and Math) and non-STEM subjects. Some key implications can assist educators in developing effective PBL-CT lesson designs and provide some research directions for future studies. Effective PBL-CT integration improves learners' computational thinking skills while boosting teaching and learning. One of the 21st-century amplifications required for student success in CT