摘要
为了更直接地掌握学生线上学习情况,及时了解学生学习进度,开展新工科背景下基于深度学习的软件工程专业线上教学系统的研究。通过系统硬件结构的设计与硬件设备参数的选型,软件部分构建资源库,确保输出的资源分类结果与期望分类结果较为接近。引进深度学习理论,推荐个性化教学内容。此外,通过实例应用的方式进行实验验证,结果表明设计的系统在实际应用中可实现对终端在线学生人数的有效识别。
In order to more directly grasp the online learning situation of students and grasp the progress of students’ learning in time, carry out research on the online teaching system of software engineering specialty based on deep learning under the background of new engineering. Carry out the design of the system hardware structure and the selection of hardware equipment parameters, and the software part builds a resource library to ensure that the output resource classification results are closer to the expected classification results. Introduce deep learning theory and recommend personalized teaching content. In addition, by way of example applications, the designed system can be used to effectively identify the number of online students in the terminal through experimental verification.
作者
岳书丹
YUE Shudan(Zhengzhou University of Industrial Technology,Zhengzhou Henan 451100,China)
出处
《信息与电脑》
2021年第15期125-127,共3页
Information & Computer
基金
河南省高校人文社会科学研究一般项目“新工科背景下软件工程专业人才培养模式创新研究”(项目编号:2021-ZDJH-397)。
关键词
新工科背景
深度学习
软件工程专业
new engineering background
deep learning
software engineering major
作者简介
岳书丹(1991-),女,河南郑州人,硕士研究生,讲师。研究方向:软件工程。
