Interaction Patterns and Embodied Design Processes Using an AI Robotics Kit for K–12 Education
TL;DR
A general structure of the design process from all the interventions is identified, which indicates that designing and building were very central throughout the interventions, with the affordances guiding the design process forward.
Abstract
This multidisciplinary study explores how children interact with a low-cost robotics educational tool designed to teach machine learning (ML) concepts through hands-on making. Artificial intelligence (AI) and ML are increasingly integrated into K-12 education, yet tangible approaches are not extensively studied. We conducted three researcher-led interventions with children aged 10, 11 and 13, each tasked to build an AI-enhanced robot using the robotics kit. Interventions were analyzed both qualitatively and with process mining methods to gain an in-depth view of the interactions. Findings indicate that designing and building were very central throughout the interventions, with the affordances guiding the design process forward. Children exhibited emerging data-driven thinking and ownership of their design process, while still requiring tailored scaffolding throughout the design process. We identify a general structure of the design process from all the interventions and emphasize the importance of building and designing activities. This study provides a new methodological lens to analyzing the interactions between children and embodied AI-educational tools while also contributing to the current body of knowledge on designing and effectively leveraging embodied learning tools.