Coding activities for children: Coupling eye-tracking with qualitative data to investigate gender differences. (April 2020)

• Record Type: Journal Article
• Authors: Papavlasopoulou, Sofia; Sharma, Kshitij; Giannakos, Michail N.
• Is Part Of: Computers in human behavior. Volume 105(2020)
• Publication Date: 2020-04
• Subjects: Coding -- Computational thinking -- Eye-tracking -- Gender differences -- Learning strategies; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2019.03.003
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: Computational thinking and coding are becoming an integral part of K-12 education, with female students being underrepresented in such subjects. The proliferation of technological tools and programming environments offers the opportunity for creative coding activities for children and increases the need for appropriate instructional practices. In this study, we design and evaluate a coding workshop for children. Our goal is to examine differences between boys and girls using eye-tracking as an objective measure and triangulating the findings with qualitative data coming from children's interviews. The results show no statistically significant difference between female and male gaze and learning gain during the coding activity; interestingly, the qualitative data show differences in the strategies and implemented practices during coding, and in perceptions about those coding activities. Our results highlight that further studies need to utilize objective measures and unveil necessary differences in the design and implementation of coding activities. Furthermore, our results provide objective evidence that female students do not lack in competences compared to boys, but simply that they have a different approach during coding activities and different perspectives about coding, an approach that needs to be cultivated and nurtured. Highlights: We designed and evaluated a coding workshop for children. We examined gender differences using eye-tracking and interviews. We found no-statistically significant gender difference in gaze and learning gain during coding. We found gender differences in the strategies and implemented practices during coding. Females do not lack in competences but simply have a different approach during coding.