Exploring Instructional Strategies for Computational Thinking Concepts and Practices in Higher Education
Abstract: Computational thinking is a problem-solving skill that involves students’ systematic design to solve complex problems, which is a crucial skill in the digital society. Researchers and practitioners have attempted to improve computational thinking skills in higher education. However, studies on interventions facilitated to teach computational thinking in higher education are still scarce. This study discusses instructional strategies utilized in a college-level computational thinking course. The course was designed to use Scratch as a computational tool to improve students’ digital literacy, problem-solving, and critical thinking. Using qualitative content analysis, we analyzed a total of 67 students’ coding journals to explore effective instructional strategies. The findings show that the choice of instructional strategy was a dynamic process. There were specific strategies that students preferred when learning certain CT concepts and practices at different stages. As the study is limited to undergraduates without any prior knowledge and their coding journals only, we suggest future studies could involve a wider range of learners and include other data resources such as interviews and their performances in the course.