Integration of Ideological and Political Elements in Natural Fiber Teaching and Evaluation of Online Learning Effects
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Abstract
Natural-fiber courses in textile education often integrate ideological and political elements in fragmented ways, with limited structured organization for themes such as sustainable manufacturing ethics and insufficient quantitative evaluation in online environments. This study presents a system for integrating ideological and political elements into natural-fiber courses within an online learning environment. The knowledge-graph-driven instructional design embeds four core themes: craftsmanship, green development, national culture, and social responsibility. The same knowledgeorganization and learning-analytics framework can also support engineering education in smart textiles, electromagnetic-compatible materials, and antenna-integrated wearable systems, where professional knowledge and value-oriented design constraints must be taught together. The platform collects posts, assignments, and test data, and applies a multidimensional learning-analytics model based on clustering and association-rule mining. The evaluation system covers knowledge mastery, interactive activity, and ideological and political identification, defined as an observable behavior-oriented indicator of value-related semantic expression in online learning outcomes. Experimental results show that ideological and political identification in the silk-fiber course reaches 89.7 in the craftsmanship dimension, while the cotton-fiber course scores 87.2 in the green-development dimension. Typical error rates remain below 20%, and correct response rates exceed 80% across instructional tasks. The study validates structured integration and quantitative feedback for natural-fiber education and provides a transferable model for engineering-oriented materials curricula.
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