<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">EIR</journal-id><journal-title-group><journal-title>Educational Innovation and Research</journal-title></journal-title-group><issn>3066-8298</issn><eissn>3066-828X</eissn><publisher><publisher-name>Art and Design</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/EIR.2025070026</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>人工智能背景下“数字视频原理及应用”课程教学体系创新和智能教学实践</title><url>https://artdesignp.com/journal/EIR/1/7/10.61369/EIR.2025070026</url><author>张宝菊,杨雨晴,张翠萍,张博,张亚蒙</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>1</volume><issue>7</issue><history><date date-type="pub"><published-time>2025-09-20</published-time></date></history><abstract>在人工智能快速发展的背景下，高校信息技术类课程正面临着教学改革的迫切需求。本文以&amp;ldquo;数字视频原理及应用&amp;rdquo;课程为例，借助人工智能技术，围绕课程教学内容更新、思政元素融入、实验体系建设、教学模式创新和智能教学实践等方面展开系统改革与探索，结合项目驱动、科研反哺教学等创新模式，以及智能教学平台的建设与应用，实现了从传统模式教学到智能化教学的转变，旨在培养适应时代需求的高素质复合型人才。研究结果表明，这些改革措施有效提升了学生的专业能力、创新意识与综合素养，为高等教育课程改革提供了有益的参考。</abstract><keywords>课程教学改革,项目驱动,课程思政,教学模式创新,智能教学平台</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]马艳平,张风彦.基于DeepSeek+下信息技术课程教学改革研究初探[J].电脑知识与技术,2025,21(15):24-27.DOI:10.14004/j.cnki.ckt.2025.0734.[2]张宝菊,孙友辰,张翠萍,等.数字视频原理及应用在课程实验教学的改革与探索[J].卫星电视与宽带多媒体,2021(19):181-182.DOI:10.12246/j.issn.1673-0348.2021.19.088.[3] Chen Z, Liang Q. 5G Channel Forecasting and Power Allocation Based on LSTM Network and Cooperative Communication[C]// International Wireless Internet Conference. Cham: Springer Nature Switzerland, 2023: 119-133.[4] Chen Z, Liang Q, Zhang B. Analysis of EEG signal evoked by passive movement and motor imagery[C]// International Conference on Communications, Signal Processing, and Systems. Singapore: Springer Singapore, 2017: 827-835.[5]蔡利梅.数字图像处理课程思政教学探索[J].大学教育,2023,(08):86-88+95.[6]杜辉.新工科背景下数字图像与视频处理课程混合式教学的探索与实践[J].现代信息科技,2024,8(12):188-192+198.DOI:10.19850/j.cnki.2096-4706.2024.12.040.[7]侯冠宇.DeepSeek赋能高校思政课创新的理论与实践[J].广西财经学院学报,2025,38(02):113-124.[8] Chen Z, Liang Q. Efficient energy power allocation for forecasted channel based on transfer entropy[C]// International Conference on Communications, Signal Processing, and Systems. Singapore: Springer Singapore, 2020: 1758-1765.[9] Wang W, Chen Z, Mu J, et al. Throat polyp detection based on compressed big data of voice with support vector machine algorithm[J]. EURASIP Journal on Advances in Signal Processing, 2014, 2014(1): 1-11[10]吴陈陈,王金凯,杜振东,等.基于DeepSeek的高职工业机器人现场编程课程教学改革研究[J].装备制造技术,2025,(02):93-96+103.[11] Chen Z. Power allocation and massive mimo channel modeling for 5g wireless communications[D]. The University of Texas at Arlington, 2022.[12]艾欣,徐文君,肖天宇,等.人工智能背景下OBE模式推动超声医学课程思政改革探索[J/OL].医学教育研究与实践,1-6[2025-06-26].</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
