Research on Case Teaching Reform Enabled by CNN Model
- DOI
- 10.2991/978-94-6463-058-9_114How to use a DOI?
- Keywords
- Big Date; CNN; STEAM Education; Case Teaching
- ABSTRACT
With the continuous breakthrough of the key technologies of artificial intelligence and big data analysis of education, and their innovative applications in various industries, a diversified trend of digitalization, networking and intelligent development is created from the traditional education model. In order to meet the demand of intelligent curriculum reform in universities and solve the problem of multi-disciplinary teaching design, empowered by CNN model, a practical model of case teaching reform is proposed, centring on the suitability of C-STEAM education concept and case teaching method. Under the circumstance of insufficient sample size, the case classification ability of CNN model is improved by use of data enhancement and K-fold validation method. Through model decomposition, the key “four-step method” of teaching implementation is sorted out, and through model construction, the feasibility of deep learning workstation is verified. From the perspective of theory and technology, the construction of curriculum information is carried out by practice and exploration, which is expected to give some enlightenment for the teaching reform in the era of intelligence.
- 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 - Peng Xiao AU - Yu Chen AU - Chengcheng Lu PY - 2022 DA - 2022/12/27 TI - Research on Case Teaching Reform Enabled by CNN Model BT - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) PB - Atlantis Press SP - 729 EP - 737 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-058-9_114 DO - 10.2991/978-94-6463-058-9_114 ID - Xiao2022 ER -