A Knowledge-Graph-Based Digital Teaching Model: Taking the Course "Principles of Automatic Control" as an Example

Abstract

As digital transformation in education deepens, traditional teaching models often struggle with conceptually abstract and knowledge-intensive courses like "Principles of Automatic Control," resulting in high cognitive load, weak knowledge connectivity, and limited personalized learning. Taking this course as a case, we explore the construction and practice of a knowledge-graph-based digital teaching model. By building a knowledge graph with granular knowledge points and attaching rich, systematic learning resources, we integrate digital teaching resources, content, processes, and assessment into a personalized, intelligent approach that boosts student efficiency and teaching quality. Practice shows the model structures knowledge visually, helps students build systematic frameworks, markedly improves learning focus and instructional efficiency, and offers a reference and case for digital reform in core STEM courses.