Thursday, April 1
4:35-4:55 PM
EDT
Room 2

Patterns of Interactions During the Learning of Computer Science and Computational Thinking Skills in a Teacher Preparation Course

Full Paper (Live Presentation) ID: 58688
  1. aaa
    Gerald Ardito
    Manhattanviille College School of Education

Abstract: This study sought to investigate patterns of interactions between teachers/teacher/ candidates and their instructor in a teacher education course called Computer Science for Teachers. This online course focused on the history of CS in K-12 education, core concepts in computer science (especially coding), and was conducted in a social learning platform designed to optimize student autonomy and independence. Student interactions were analyzed using a variety of methods in order to determine what types of interactions correlated with various aspects of the course. These methods included: interaction coding and visualization using Epistemic Network Analysis (ENA) and Social Network Analysis (SNA). The results of these analyses suggest that teacher control and student autonomy were indicated by differing patterns of interactions between students and their instructor. Additionally, high levels of student autonomy were particularly present during the robotics portion of the course, where students worked on their own to solve a set of open ended challenges. Implications of these results for teacher preparation in CS are discussed, as is future research.

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