Knowledge Level and Self-Confidence on The Computational Thinking Skills Among Science Teacher Candidates

Abstract

The trending topic in today's education is computational thinking skills which are used to help to solve complicated problems easier. This study aims to identify the level of knowledge and self-confidence of science teacher candidates (physics and biology) on computational thinking skills. The survey research design was used through a mixed-method approach by combining quantitative and qualitative approaches. The quantitative study involved 1016 randomly selected groups of science teachers while in the qualitative study, eight science teachers were chosen based on the scores obtained from the quantitative study. The questionnaire was used as a quantitative data collecting technique to analyze descriptive statistics. Then, an interview was used as the qualitative data collecting technique and was analyzed through theme creation. The findings show that science teacher candidates have a high level of knowledge and self-confidence. The implication of this study is very important for teacher candidates because computational thinking can help to facilitate problems solving in everyday life. Teacher candidates need to be given knowledge and understanding of computational thinking skills, to have readiness and self-confidence in facing the challenges of the learning in the 21st-century