AIGC-Empowered Talent Cultivation Model for the Data Science and Big Data Technology Major under Engineering Education

Abstract

This study examines two main issues in the engineering education of the Data Science and Big Data Technology program: the gap between what students learn and actual industry demands, and the limited application of AIGC technology in daily teaching. To address these problems, we developed a new talent training model based on a four dimensional collaborative framework and three supporting systems; following the approach of not adding separate new courses while integrating AIGC into all teaching links, we added AIGC related content to the existing knowledge-ability-quality training system, revised course content, improved practical training tasks, and promoted cooperation among government, universities and enterprises to ensure AIGC is deeply applied throughout classroom instruction, lab sessions and internship training. We piloted this model with three groups of students at Suqian University, and the results show that students have made clear progress in their ability to complete AIGC assisted tasks and their overall engineering skills, enterprises have given higher recognition to student project outputs, more awards have been obtained in subject competitions and innovation projects, and government-university-enterprise cooperation has been further strengthened. This work provides a practical reference for other emerging engineering majors to keep up with technological development without making major adjustments to their current curriculum systems.