Young children’s conceptions of robot programming learning: A draw-a-picture and epistemic network analysis

Abstract

As technology-enhanced children’s learning has gained wide attention, programmable robots have been gradually introduced in early childhood education. Hence, it would be valuable to understand how young children perceive robot programming learning. Draw-a-picture technique is an ideal method to elicit ideas, thoughts, and feelings for children with limited literacy, and epistemic network analysis (ENA) is a novel analytical method to analyze children’s conceptions through the visualized network model. Therefore, this study employed a draw-a-picture technique and ENA to explore 189 5-6-year-old young children’s conceptions of robot programming learning and probe whether their conceptions differ by gender and learning achievements. Results revealed that most children believed that with robot programming kits, they could engage in programming activities with peers in any location and held positive emotions and attitudes. In addition, young children’s conceptions of robot programming learning differ notably by gender and learning achievements. Based on the current findings, several suggestions were proposed, which could set a reference for future robot programming teaching in early childhood education.

Keywords

• robot programming learning
• young children
• draw-a-picture technique
• epistemic network analysis