Application and Practice of Online Teaching of Computer Image Processing Courses Under the Concept of OBE Education
- DOI
- 10.2991/978-94-6463-044-2_72How to use a DOI?
- Keywords
- OBE education concept; Computer image processing; Online teaching
- Abstract
The computer image processing course is a professional orientation course for computer technology, information technology, artificial intelligence and other majors. During the COVID-19 outbreak this spring, the course teaching team investigated and analyzed the software and hardware environment for students to conduct online teaching, and combined with the characteristics of this course, relying on the online teaching resources established by the continuous promotion of teaching reform in recent years; teaching. Online teaching takes OBE results as the guiding ideology, takes students’ development as the core, pays attention to the autonomy of students and the guidance of teachers, evaluates and feedbacks students’ learning effects through different channels, and promotes teachers and students’ teaching and learning methods. Continuous improvement, so that the quality of online and offline teaching is essentially equal.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Li Wang PY - 2022 DA - 2022/12/27 TI - Application and Practice of Online Teaching of Computer Image Processing Courses Under the Concept of OBE Education BT - Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022) PB - Atlantis Press SP - 566 EP - 570 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-044-2_72 DO - 10.2991/978-94-6463-044-2_72 ID - Wang2022 ER -