The effect of data science activities on computational thinking skills of secondary school students

Having computational thinking skills is necessary to adapt to rapidly developing technology. Computational thinking is a skill that should be acquired from an early age. The aim of this study is to examine the effects of data science activities developed for secondary school students on computational thinking skills and to evaluate the applied program according to student opinions. The study was conducted with 19 students studying in the 7th grade. In the study, a needs analysis was first conducted by applying semi-structured interview technique and an experimental study was designed based on qualitative data. After the obtained data were analyzed, data science activities were developed and implemented for middle school students. In this study, a single-group pre-test post-test weak experimental design, which is supported by qualitative data, was used. While obtaining quantitative data before and after the implementation process, the computational thinking skills achievement test and the computational thinking skills self-efficacy perception scale were used. The obtained data were analyzed by using the dependent-independent sample t-test. At the last stage of the study, students' opinions about the activities and the implementation process were taken. Opinions were obtained with a semi-structured interview form. Obtained qualitative data were analyzed by content analysis method. As a result of the implementation of the data science activities developed for middle school students, it was concluded that there was a significant difference between the pre-test and post-test of the academic achievement of computational thinking skills. It was concluded that this difference was not significant in terms of gender variable. Across the test, as a result of the study, it was revealed that there is a significant difference between the students' computational thinking skills self-efficacy perception pre-test scores and their computational thinking skills self-efficacy perception post-test scores. However, when the sub-dimensions of the scale were examined, it was concluded that there was no significant difference between the pre-test and post-test in the problem solving competence sub-dimension. As a result of the interviews, students reported that data science activities improved their problem solving skills and thinking skills. At the same time, it was concluded that the knowledge they learned and the skills they gained contributed positively to their academic success and personal development. Keywords: Computational thinking, data science, data science activities, secondary school students