Exploration and Practice of the Talent Cultivation Model for Outstanding Students in Robotics Engineering Major

Abstract

This study presents an innovative talent-training framework for high-achieving undergraduates in robotics engineering that integrates a four-phase developmental scaffold—cognitive ignition, interdisciplinary fusion, research immersion, and entrepreneurial translation—within a trinity ecosystem composed of an elite "robotics honor academy," industry-led living-labs, and an international academic alliance. A three-year quasi-experiment involving 186 outstanding students shows that participants achieved a 42\% increase in flagship competition awards, 2.3-fold rise in first-author IEEE papers, and 96\% job-match relevance versus 71\% in the control group. The model's core mechanisms are: (1) dynamic learning pathways steered by AI-diagnosed competency portraits; (2) cross-disciplinary "chameleon" projects co-supervised by university, corporate and clinical partners; (3) an ethical-by-design thread that embeds robo-ethics, sustainability and societal impact assessment into every project milestone. Structural equation modeling confirms that research immersion exerts the strongest total effect on creative self-efficacy ($\beta=0.54$, $p<0.001$), while entrepreneurial translation is the key predictor of technology-transfer intention ($\beta=0.49$). The findings offer a scalable blueprint for cultivating robotics elites who combine deep technical virtuosity with responsible innovation mindset, and can be adapted to other high-tech engineering disciplines.