Research on Cluster Analysis of Process Evaluation Integrated into Teaching
Authors
Yongjian Wang1, Nie Zhou2, *, Pengfei Hu3, *
1Teaching and Research Support Center, Army Logistics Academy, Chongqing, 401331, China
2Teaching and Research Support Center, Army Logistics Academy, Chongqing, 401331, China
3International Training Department, Army Logistics Academy, Chongqing, 401331, China
*Corresponding author.
Email: 22653526@qq.com
*Corresponding author.
Email: 857682490@qq.com
Corresponding Authors
Nie Zhou, Pengfei Hu
Available Online 28 September 2023.
- DOI
- 10.2991/978-94-6463-264-4_61How to use a DOI?
- Keywords
- process evaluation; learning characteristics; cluster analysis; teaching quality; practical exploration
- Abstract
The process evaluation integrated into teaching is aimed at promoting learners’ development. It takes “efficient learning” as the basic starting point and follows the course learning method of “evaluation methods being various, but not fixed”, to accurately grasp the immediate evaluation in the teaching process. This paper aims to analyze the characteristics of process evaluation integrated into teaching, expounds on the comparative advantages with traditional learning evaluation, and proposes the implementation strategy of process evaluation by adapting big data cluster analysis to improve learners’ thinking ability.
- Copyright
- © 2024 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 - Yongjian Wang AU - Nie Zhou AU - Pengfei Hu PY - 2023 DA - 2023/09/28 TI - Research on Cluster Analysis of Process Evaluation Integrated into Teaching BT - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023) PB - Atlantis Press SP - 534 EP - 541 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-264-4_61 DO - 10.2991/978-94-6463-264-4_61 ID - Wang2023 ER -