高教学刊2025，Vol.11Issue(31)：104-107,4.DOI:10.19980/j.CN23-1593/G4.2025.31.024
数字图像处理实验课混合式智能教学设计研究
摘要
Abstract
The in-depth development of artificial intelligence technology is reconstructing the education ecosystem and promoting the fundamental reform of teaching with intelligent interaction that breaks through the limitations of time and space.As a basic course of electronic information majors,Digital Image Processing urgently needs to build a teaching paradigm of"theory-practice-innovation"deep integration in the context of digital and intelligent transformation.The purpose of this paper is to study the problems of lack of personalized guidance and students'lack of motivation for innovation in Digital Image Processing Experimental Course.Based on the cognitive load theory and formative evaluation mechanism,a three-stage progressive teaching model of"knowledge graph guidance-project practice driven-dynamic ranking incentive"was constructed.In this study,we constructed a knowledge graph,sorted out the logical relationship of knowledge points through a graphical structure,and established a real-time ranking incentive system for experimental results to stimulate students'enthusiasm for practice,providing a replicable blended teaching solution for engineering experimental courses.关键词
数字图像处理/混合式教学/实验课程改革/人工智能/知识图谱Key words
Digital Image Processing/blended teaching/experimental curriculum reform/artificial intelligence/knowledge graph分类
教育学引用本文复制引用
高晶,吕宁,金国栋,谭力宁..数字图像处理实验课混合式智能教学设计研究[J].高教学刊,2025,11(31):104-107,4.基金项目
2023年重点项目陕西省高等教育教学改革研究项目"岗位引领、智信赋能,无人机侦察课程建设研究与实践"(23BZ095) （23BZ095）
