2025 ASEE Annual Conference & Exposition

With the fast pace of technological developments and the growing need for qualified professionals in Science, Technology, Engineering, and Mathematics (STEM), promoting Computer Science (CS) education in primary school has become imperative. However, the persistent gender gap in STEM and the still limited number of individuals entering these fields, despite the high industry demand, remain significant challenges. Consequently, Computational Thinking (CT) has become a critical component that young students must develop. However, there is still little understanding of how children develop CT skills and engage with CT-related tasks.
Hence, this study responds to these 21st-century needs and aims to offer valuable insights into how first-grade students demonstrate their understanding and application of CT principles. Through programming lessons accommodating their unique developmental stage, the research focuses on their ability to develop and debug algorithms in coding challenges using plugged activities involving Educational Robots (ER) and a block-based programming language platform. It also examines engagement patterns across cognitive, behavioral, emotional, and social dimensions, investigating potential biological sex differences while considering the broader implications for the gender gap.
The study utilized a naturalistic inquiry approach, incorporating qualitative analysis of students’ work, classroom observations, and video data to gain meaningful insights into students’ conceptual understanding of CT principles and whether differences in engagement are influenced by biological sex or other factors inherent in the learning process, such as individual learning styles. The findings show that while there were slight differences in how students engaged with and approached CT tasks, they were more related to learning styles, individual traits, and how they respond to interpersonal interactions with peers rather than biological sex. Both boys and girls were highly cognitively engaged — e.g., problem-solving and algorithmic thinking — with social dynamics significantly influencing collaboration and overall engagement. Emotional responses, such as excitement and frustration, were present in all groups. Additionally, boys and girls exhibited similar behavioral engagement through active participation, persistence in debugging, and eagerness to solve coding tasks.
The findings highlight that even at an early age, students can grasp and apply foundational CT concepts present in algorithm development and debugging. However, curricula should be strategically designed considering students’ developmental stages. The study suggests the young age of the students might explain the lack of significant sex-based differences. At this age, students are less influenced by social gender norms, which could explain the minimal differences in engagement patterns. While this study focuses on biological sex differences, it is essential to consider how societal gender norms might influence these engagement patterns as students age and begin to internalize such norms. The early exposure to computational thinking is an opportunity to foster environments that challenge traditional gender stereotypes before they become established.