Digital and Intelligent Empowerment for Precision Teaching: A Process-oriented Evaluation Model for Higher Mathematics Blended Learning

Abstract

Aims: To solve problems like strong subjectivity, unbalanced weights, and lagging evaluation dimensions in blended teaching of Higher Mathematics, and build a process-oriented comprehensive evaluation model empowered by digital intelligence for precision teaching. Study Design:  Constructed an evaluation system and comprehensive evaluation model based on dual-drive logic of Delphi method and Analytic Hierarchy Process (AHP). Place and Duration of Study: Shenyang Normal University, School of Mathematics and Systems Science, between December 2025 and February 2026. Methodology: Established a 15-member interdisciplinary expert consultation pool; screened and optimized indicators through two rounds of Delphi surveys; used AHP to determine indicator weights and conduct consistency tests. Results: The results of AHP weight determination and consistency tests indicate that the "Teaching Support" dimension holds a dominant position, among which "Automated Learning Early Warning and Intervention Response Efficiency" has the highest composite weight (0.112), emerging as a core variable driving precision teaching. Conclusion: The research demonstrates that the focus of evaluation has achieved a paradigm reconstruction from "end-product output" to "process intervention". This model provides decision-making support for the precise implementation of Higher Mathematics teaching reform and offers an operational framework for quality assessment in the digital transformation of higher education.