Design and Practice of Social Practice Courses Based on Capability Maturity Model: A Case Study of News Edition
- DOI
- 10.2991/978-94-6463-058-9_157How to use a DOI?
- Keywords
- social practice; big data; BOPPPS model; Hierarchical Analysis Process (AHP); Capability Maturity Model (CMM)
- Abstract
As a powerful support for students’ innovation and entrepreneurship in application-oriented colleges and universities, the social practice course completes the leap from academia to the industry during students’ schooling and achieves the breakthrough from learning knowledge to solving social problems. Taking the social practice course News Edition as an example, relying on the BOPPPS teaching model and questionnaire survey method, this paper explores the construction and practice of the practice course with the help of the Analytic Hierarchy Process (AHP). By introducing the Capability Maturity Model (CMM) and using SPSS Software to output the KendallW coordination coefficient, the practical ability of students is evaluated from multiple evaluation systems, thus deriving the problems and improvement directions of the construction of social practice courses.
- 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 - Bei Chen PY - 2022 DA - 2022/12/27 TI - Design and Practice of Social Practice Courses Based on Capability Maturity Model: A Case Study of News Edition BT - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) PB - Atlantis Press SP - 1003 EP - 1008 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-058-9_157 DO - 10.2991/978-94-6463-058-9_157 ID - Chen2022 ER -