Enhancing Engineering Education through Flipped Learning and Collaborative Coaching: An Empirical Study on AI and Robotics Project Development in Higher Education

This paper examines the impact of a flipped learning approach combined with collaborative coaching as a transformative strategy for skill development in engineering education. Involving 10 undergraduate students divided into an experimental group and a control group, the study focuses on enhancing competencies in AI and robotics. The experimental group, tasked with developing an algorithm for object manipulation and classification using MATLAB and computer vision techniques, participated in the "RoboCup ARM Challenge 2024" with support from collaborative coaching, while the control group received traditional instruction. Comprehensive rubrics were used to evaluate theoretical understanding, technical skills, teamwork, and problem-solving. Statistical analysis revealed that the experimental group achieved significantly higher scores across all competencies, with their first-place success in the international competition further affirming the effectiveness of this approach. The findings underscore the potential of integrating flipped learning and collaborative coaching to prepare students for realworld engineering challenges.