RESEARCH ON THE INTERACTIVE LEARNING PLATFORM FOR THE "ENGINEERING MECHANICS" COURSE IN THE CONTEXT OF BIG DATA

In the era of big data, the "Engineering Mechanics" course urgently requires innovative reforms in teaching content, methods, experimental components, and evaluation systems. Traditional instruction in “Engineering Mechanics" often inadequately considers individual student learning abilities and feedback, resulting in insufficient mastery of key concepts and a potential decline in students' interest in the subject. To address these challenges, this study proposes the development of an Interactive Learning Platform. By leveraging data-driven strategies, the platform dynamically analyzes and adapts to students' learning needs and knowledge acquisition, significantly enhancing teaching effectiveness. The platform prioritizes accommodating individual differences and providing immediate feedback, effectively assisting students in overcoming challenges in understanding complex theoretical concepts, thereby increasing learning motivation. Through the use of artificial intelligence algorithms, the platform adjusts instructional content and pace to better match students' actual abilities and needs. Furthermore, by integrating practical applications of mechanics with big data-related disciplines, this study introduces a novel teaching approach aimed at developing innovative capabilities in complex mechanics theory. This new educational system aims to cultivate application-oriented talents capable of meeting the demands of the big data era, thus ensuring that students are well-prepared to keep pace with contemporary developments.