2025 ASEE Annual Conference & Exposition

This study explores the computational thinking skills of young children (2nd-year elementary students) within an embodied learning environment designed to enhance STEM education, utilizing both augmented reality and social robot technology. The research aims to understand how these technologies can support and improve children’s problem-solving abilities in STEM-related tasks. Over a four-day period, students interacted with a custom-developed educational tool, which was designed to engage them in physical activities and social interactions with the robot. These interactions were tracked to observe changes in their bodily movements, responses to problem-solving tasks, and interactions with the social robot.

To comprehensively analyze the children's learning behaviors, researchers conducted manual annotations of video recordings, focusing on key behavioral indicators. Concurrently, objective data were collected using advanced tools such as a motion capture system and facial muscle activity sensors, allowing for precise measurement of physical responses. A detailed statistical analysis will be carried out to determine the correlations and patterns between the motion capture and muscle activity data and the human annotations.

Following the analysis, a machine learning model will be developed to accurately link sensor-based data with human annotations, which will allow for automatic recognition of learning behaviors in future studies. By refining this model, we aim to increase the efficiency of assessing children’s interactions in technology-supported learning environments. Additionally, the study will highlight critical measures that contribute to understanding how students react to and adapt during STEM problem-solving tasks, offering valuable insights into the specific cognitive and physical processes involved in embodied learning. This research has the potential to significantly enhance the methodologies used to evaluate children’s learning behaviors, improving future educational tools and strategies in STEM education.