Do We Really Need Block-Based Programming to Enhance Computational Thinking in Science Classes?

As a result of technological developments, digital technologies are increasing their impact in all areas of life. This impact complicates the problems that need to be solved while diversifying the ways to solve them. This research addresses the use of computational thinking, one of the diversified problem-solving approaches, in science education. In this context, the research aims to determine the effect of a block-based coding tool on the enhancement of computational thinking skills. To this objective, the study, designed with a quasi-experimental design, aims to determine the effect of block-based coding and the algorithmic explanation approach on academic achievement and computational thinking skills. In the study conducted with sixth-grade middle school students, five different computational thinking activities were carried out over sixteen class hours. The results of the study showed no significant difference in science achievement between the experimental and control groups. However, significant differences in favor of the control group were found in the overall computational thinking scale and in the cooperativity and problem solving sub-dimensions. Based on this result, it can be argued that block-based coding contributes more positively to the development of computational thinking than the algorithmic explanation approach. However, the science achievement, creativity, algorithmic thinking, and critical thinking sub-dimensions, which did not show significant differences, indicate the potential positive effect of the algorithmic explanation approach. Therefore, it can be considered an important alternative, especially in situations where a digital divide can be observed.