UP‐GEARED: UNLOCKING THE POTENTIAL OF GENERATIVE AI FOR EQUITY AND ACCESS IN ROBOTICS EDUCATION
UP-GEARED explores the potential of generative AI to bridge prior knowledge gaps and enable equitable learning experiences. By leveraging AI's ability to assist users regardless of their prior experience, this research investigates how generative AI can foster high-level conceptual engagement and improve motivation in educational contexts.
UP-GEARED focuses on engineering design education through the lens of educational robotics, developing and testing a task-oriented generative AI tool to support creative productivity. A prototype AI robot design assistant, integrated into a virtual robot-building game, is designed to enhance learning outcomes for lower-performing students. The study examines how generative AI can close equity gaps and evaluates its impact on task performance, motivation, and subsequent independent learning.
Using a design-based research approach, the project will uncover technical challenges and define future research directions. A crossover-design classroom study will assess the tool's effects, particularly its ability to benefit learners with limited prior robotics experience. Potential peripheral effects, such as reliance on the tool and reduced performance without it, will also be examined.
Findings will inform efforts to develop ethical and effective generative AI tools that support equitable, age-appropriate learning and inspire interest in AI. This research aims to integrate AI into education responsibly, advancing both technical and pedagogical innovation in the field.
This material is based upon work supported by the National Science Foundation under Grant Number 2341190.