Teachers’ Knowledge in Informatics—Exploring Educational Robotics Resources Through the Lens of Textual Data Analysis

Abstract

In this research, we are interested in the knowledge of primary and secondary teachers to teach informatics. Using pedagogical resources produced by them as a trace of their enacted Pedagogical Content Knowledge (ePCK), we perform Textual Data Analysis and Clustering to discover the topics they write about. Focusing on resources in educational robotics, we show that lexicon used by teachers is different depending on the robot they use. Reinert's clustering associates each robot with a separate cluster and a specific vocabulary. Multiple Correspondence Analysis (MCA) shows an opposition between lexicon found in resources using event-driven robots (Thymio and Ozobot) and in resources using sequential robots (Beebot and Bluebot). Event-driven robots tend to be more related with events and behavior notions, as sequential robots tend to be more related with first manipulations of an object and programming notions.