This study details a researcher’s self-study journey in advancing from a computational thinking (CT) novice to an expert. The researcher went through a four-stage process, with a preliminary literature review preceding the four stages. From the literature review, the computational thinking analysis (CT_AT) tool was developed for use in stage one to analyze science, technology, engineering, art, and mathematic (STEAM) modules. Although no discernable patterns were found in analyzing the five science and five engineering-based modules, the analysis revealed which CT practices were missing or weakly exposed. In stage two activities were suggested to promote these missing or weakly exposed practices. Stage three required the researcher to develop his own STEAM module from the viewpoint of exposing students to CT. The fourth stage was to validate the CT_AT through interviews with pre-service and in-service teachers. These interviews led to changes in the CT_AT tool and, as a result, the researcher produced a guidebook that could be used by teachers in their own CT studies. This guidebook can be used by teachers to develop and become competent in CT skills.

The purpose of this study was to explore if, what kinds of, how much computational thinking (CT after this) practices could be included in STEAM programs, and what kinds of CT practices could be improved to make STEAM revitalized. The CT analyzing tool with operational definitions and its examples in science education was modified and employed for 5 science-focused and 5 engineering-focused STEAM programs. There was no discerning pattern of CT practices uses between science and engineering STEAM programs but CT practices were displayed depending on their topics. The patterns of CT practices uses from each STEAM program could be used to describe what CT practices were more explored, weakly exposed, or missing. On the basis of these prescription of CT practices from each STEAM program, the researchers could develop the weakly exposed or missing CT practices to be improved for the rich experience in CT practices during STEAM programs.

The purpose of science education is scientific literacy, which is extended in its meaning in the 21st century. Students must be equipped with the skills necessary to solve problems from the community beyond obtaining the knowledge from curiosity, which is called ‘computational thinking’. In this paper, the authors tried to define computational thinking in science education from the view of scientific literacy in the 21st century; (1) computational thinking is an explicit skill shown in the two steps of abstracting the problems and automating solutions, (2) computational thinking consists of concrete components and practices which are observable and measurable, (3) computational thinking is a catalyst for STEAM (Science, Technology, Engineering, Arts, and Mathematics) education, and (4) computational thinking is a cognitive process to be learned. More implication about the necessity of including computational thinking and its emphasis in implementing in science teaching and learning for the envisioned scientific literacy is added.