Effectiveness of Computational Thinking in Problem Based Learning

Abstract

National Education Policy 2020 demands the education system to acclimate problem based and discovery oriented learning. A problem used as a tool for teaching and learning can help to achieve the learning outcomes and also enhance cognitive and critical thinking skills. Self-directed learning is one of the essential skills needed for the today’s working professionals. Problem based learning and computational Thinking methodologies have been used in varying contexts to achieve the desired course outcomes. This paper proposes a model to solve and analyze case studies using both the approaches. The model was tested using open book exams as assessment method for system design problems and computational thinking was found to be effective when combined with the problem based learning methodology. The instruments were validated using cronbach’s alpha co-efficient and even the student feedback has been positive for the process. The model was analyzed using the case study research method. The results appear to be promising and can be used for most computer science courses which are algorithmic or problem solving in nature. Combining computational thinking with problem solving can be an effective way of course delivery and open book exams can be an effective assessment method.