A multimodal data-driven framework and system for evaluating the ideological and political education of courses under the Chinese new engineering science

To address the existing challenges in the teaching ideological and political assessment system within Chinese universities, particularly in the context of New Engineering disciplines, this study proposes a new six-dimensional teaching ideological and political evaluation framework. This framework is designed to provide a comprehensive, systematic, and scientifically grounded approach to evaluating the integration of ideological and political education into engineering curricula. By focusing on six key dimensions—socialist core values, Chinese excellent traditional culture, professional ethics and engineering ethics, craftsmanship and creative awareness, teamwork and communication skills, and social responsibility and patriotism—the framework ensures that ideological and political education is not only embedded in the curriculum but also effectively assessed and continuously improved. To operationalize this framework, a teaching ideological and political evaluation system was designed and implemented, leveraging multimodal data-driven algorithms. This system integrates diverse data types, such as text, images, audio, video, and behavioral data, to provide a holistic and objective assessment of teaching effectiveness. The use of advanced data mining and machine learning techniques enables the system to analyze complex datasets, extract meaningful insights, and generate actionable feedback for educators and administrators. The introduction of this pedagogical and political evaluation system provides a scientific and efficient evaluation system for educational administrators to assess potentially valuable ideological and political education in the teaching and learning process and apply it to the management of ideological and political work.