Exploration of Online and Offline Hybrid Enhanced Deep Teaching Guided by Project and Knowledge Graph
- DOI
- 10.2991/978-94-6463-803-5_21How to use a DOI?
- Keywords
- Online and Offline Hybrid Enhancement Deep teaching; Project Guidance; Knowledge Graph; Database System
- Abstract
Cultivating the college students’ ability of high-level thinking and solving complex problems are inseparable from in-depth teaching, and the online and offline integrated teaching method based on online teaching platforms can help achieve in-depth teaching. This paper takes the teaching of the database system course as an example. In view of the characteristics of this course, which has the characteristics of abstract concepts, many knowledge points, and strong practicality, in order to help students form a chain knowledge structure and build the overall knowledge system of the course, this paper relies on engineering project oriented teaching to construct a database system knowledge graph, and proposes an online and offline hybrid enhanced deep teaching model guided by projects and knowledge graphs. The teaching model is elaborated from three dimensions: pre class teaching planning, in class teaching implementation, and post class teaching consolidation.
- Copyright
- © 2025 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 - Min Hu AU - Shuli Zheng AU - Zhengqiong Liu PY - 2025 DA - 2025/07/31 TI - Exploration of Online and Offline Hybrid Enhanced Deep Teaching Guided by Project and Knowledge Graph BT - Proceedings of the 5th International Conference on Internet, Education and Information Technology (IEIT 2025) PB - Atlantis Press SP - 200 EP - 207 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-803-5_21 DO - 10.2991/978-94-6463-803-5_21 ID - Hu2025 ER -