新工科软件新生项目课程教学设计与实践  

Teaching Design and Practice of Project Curriculum for New Engineering Software Freshmen

作　　者：杨珊 易黎[1] 张萌洁 朱相印 何中海[1] YANG Shan;YI Li;ZHANG Mengjie;ZHU Xiangyin;HE Zhonghai(School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China)

机构地区：[1]电子科技大学信息与软件工程学院,成都610054

出　　处：《实验科学与技术》2023年第4期49-53,64,共6页Experiment Science and Technology

基　　金：教育部产学合作协同育人项目(201901072028);电子科技大学“开发基于项目的新生课程教改专项”(2019PBLF017)。

摘　　要：该文针对新工科软件专业图像分类任务的新生项目课程存在的3个问题进行分析设计,包括Python语言不熟悉,图像分类入门时间短以及实操环境学生难以搭建,提出了基于百度的AI Studio平台和以PaddleHub预训练模型的应用为中心的课程教学设计,包括融合线性代数的实际应用,预训练模型fine-tune实践以及组队分工线上线下结合学习等,后续可以改进为由学生自主选择设计识别任务内容。该课程设计内容有助于学生奠定工程基础,提高专业技能,培养团队合作能力,最终达到增强专业兴趣和专业信心的课程设计目标。This paper analyzes and designs three problems existing in the new project curriculum of image classification tasks for software majors in the new engineering discipline.These problems include a lack of familiarity with Python language,a short time to learn image classification,and difficulty in setting up practical environments for students.To address these issues,a course teaching design based on Baidu’s AI Studio platform and centered around the application of pre-trained models from PaddleHub is proposed.This design incorporates practical applications of linear algebra,fine-tuning practices with pre-trained models,and online and offline team collaboration and learning.In the future,this design can be improved by allowing students to independently select and design recognition tasks.This curriculum design aims to help students lay a foundation in engineering,improve professional skills,cultivate teamwork abilities,and ultimately achieve the goal of enhancing professional interest and confidence.

关 键 词：新生项目课 图像分类 迁移训练 数据增强 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] G642.0[自动化与计算机技术—计算机科学与技术]