Exploration and Practice of the Blended Teaching Mode of Industrial Robot Courses Based on the Background of Artificial Intelligence

With the advancement of the “Made in China 2025” strategy, the contradiction in talent supply in the field of industrial robots is prominent. The traditional training model has problems such as a lagging curriculum system, insufficient practical training equipment, and a single evaluation system. The development of artificial intelligence technology has brought new opportunities to the teaching of industrial robot courses and constructed a blended teaching model. This model encompasses the construction of the core parameter system for industrial robots and the architecture of an intelligent teaching platform. Teaching practices are carried out through methods such as “online theoretical foundation - virtual simulation pre-training - offline practical operation deepening”. Practice shows that the blended teaching mode is significantly superior to the traditional teaching mode in multiple dimensions such as the compliance rate of industrial applicability, practical operation efficiency, and recognition accuracy. However, this teaching mode is confronted with challenges such as difficulties in updating teaching resources, insufficient interdisciplinary ability of teachers, significant differences in students' learning autonomy, and insufficient depth of school-enterprise cooperation. To this end, countermeasures need to be taken in aspects such as resource construction, improvement of teachers' capabilities, student management and deepening of school-enterprise cooperation to promote high-quality development of teaching.