Abstract
In order to realize the data-driven teaching quality evaluation activities and the construction of its system, we must deeply study the relevant models used to guide its algorithm selection, evaluation implementation and system integration. This paper focuses on the analysis model, process model and system model of data-driven teaching quality evaluation. The analysis model is used to form the reference model of how to deal with relevant data and provide reference for data processing. In this part, the cluster analysis, association analysis and prediction analysis are discussed in detail; the process model is used to form the teaching quality evaluation cycle of evaluation to promote learning, which provides reference for organizing evaluation activities, this part analyzes the teaching activities, evaluation activities, intervention activities and their interrelations in the process model. The system model is used to form a reference mode for guiding the design, construction and transformation of teaching quality evaluation big data system, which provides reference for system implementation, this part analyzes the functions of data acquisition layer, data management layer, data interface layer, data processing layer, business application layer and service interface layer.
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