Trajectories of Developing Computational Thinking Competencies: Case Portraits of Korean Gifted Girls

Abstract

From a learning ecology perspective, this paper aims to better understand how girls become gifted in CT competencies and how CT competencies were manifested through the co-influence of multiple factors in the developmental trajectory. A life-narrative approach using interviews was taken to unpack the significant factors that facilitate or limit the development of CT competencies. Three portraits of Korean gifted girls in information science are presented to illustrate how they developed interest and fluency in CT. Data were analyzed by a framework of Gagne's DMGT (Differentiating Model of Giftedness and Talent) 2.0. Major themes identified across the case portraits are (a) the linkage between mathematical, science, and computational thinking; (b) parents and teachers as the main catalysts; (c) self-directedness; (d) limited learning resources and knowledge-building strategies; (e) formal gifted education program as a turning point; and (f) the weak linkage between CT competencies and the future self. Implications on the pedagogical approaches concerning the gender equity issue in CT are also discussed.