Research on Hybrid Teaching of Computer Composition Principle Based on Engineering Education Certification
- DOI
- 10.2991/978-2-494069-05-3_197How to use a DOI?
- Keywords
- Principles of Computer Composition; Engineering Education Certification; Blended Teaching; Independent Learning
- Abstract
The paper analyzes the current teaching situation of the course “Computer Composition Principles” from the perspective of “student-centered, output-oriented and continuous improvement”, and designs the “1-3-2-1” hybrid teaching organization model based on the engineering education accreditation. The organization mode is based on the digital course resources of Super Star MOOC, interactive communication on the online platform, and problem-oriented teaching activities. This model is conducive to cultivating students’ independent learning ability, enabling them to deepen their understanding and mastery of the computer composition course, adopting diversified assessment and strengthening process control, so as to improve teaching quality and achieve the course teaching objectives.
- Copyright
- © 2023 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 - Sanrong Liu AU - Li Xu AU - Zhihao Cao AU - Yong Wang AU - Yanyan Hou PY - 2022 DA - 2022/11/19 TI - Research on Hybrid Teaching of Computer Composition Principle Based on Engineering Education Certification BT - Proceedings of the 2022 International Conference on Science Education and Art Appreciation (SEAA 2022) PB - Atlantis Press SP - 1618 EP - 1627 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-05-3_197 DO - 10.2991/978-2-494069-05-3_197 ID - Liu2022 ER -