Understanding age and gender differences of computational thinkers : an exploratory study on children's development and learning

Abstract

Over the last decade, computational thinking (CT) has been regarded as an essential skill for the young generation to study, work, and live in the 21st-century. An increasing number of countries have included CT-related content in their curricula starting from primary school.

Despite the growing importance of CT in compulsory education, there is little understanding of whether children are developmentally ready to think computationally and what specific CT concepts and skills can be developed at various ages. Research on examining gender differences in CT across ages is also relatively sparse. Moreover, different instructional approaches have been proposed to support CT acquisition for primary school students, such as game programming and unplugged activities. However, there is still uncertainty whether these approaches are effective for helping children of different ages and genders. Finally, as CT is taught at increasingly early ages, it is necessary to identify the cognitive abilities required for different CT skills. Nevertheless, few studies have investigated the cognitive prerequisites for learning CT.

Therefore, the general aim of this study is to investigate whether significant differences in CT development exist among children of different ages and genders. This study draws on the overarching theory of the growing mind that describes children’s cognitive development in general thought domains to understand the development of three CT dimensions: simple and compound conditionals, pattern recognition, and generalization. The participants are Chinese students aged 9 to 13 (Grades 4–6). This study consists of three sub-studies. Study 1 sought to develop and validate a test measuring primary school students’ skills and age-related differences in CT. Results provide evidence of reliability, validity, and measurement invariance of the developed test. Study 2 investigated the relationship between the three CT dimensions and general cognitive abilities. Further, Study 2 examined grade and gender differences in participants’ natural, preinstruction CT skills. Results indicate that conditional reasoning, analogical reasoning, and the understanding of logical connectives predicted participants’ CT skills as measured by the developed test. Children’s preinstruction CT skills increased substantially as they grew older and did not differ between genders. Study 3 examined whether two instructional approaches—a programming-only approach and a mixed approach combining both unplugged and programming activities—have different effects on CT acquisition for the participants. Results suggest that the mixed approach was more effective for students aged 9 to 11. Conversely, students aged 11 and above learned better through the programming-only approach. Results also show that participants achieved mastery of simple and compound conditionals and pattern recognition after instruction. In summary, this study shows the existence of a CT developmental progression for children aged 9 to 13.

This study suggests the importance of examining the interaction between cognitive development and learning on CT acquisition for primary school students. A framework describing the CT developmental progression for children aged 9 to 13 is proposed to guide the design of age-appropriate instruction. Theoretical, practical, and methodological implications for CT education are discussed. Limitations and future directions are presented.