Exploring the Evaluation of College Students’ Learning Effect Under SPOC Teaching Mode Based on Cluster Analysis
- DOI
- 10.2991/978-94-6463-024-4_52How to use a DOI?
- Keywords
- SPOC; Blended Teaching; Evaluation of Learning Effect; Cluster Analysis; K-means Algorithm
- Abstract
SPOC (Small Private Online Course) is an online and offline blended teaching mode. Many colleges and universities have adopted this teaching mode to improve teaching quality. However, due to the particularity of teaching mode, the way of evaluating students’ learning effect under this mode needs to be further explored. In this study, a course with SPOC teaching mode was selected as an example and K-means algorithm was applied to conduct cluster analysis on students’ learning behaviours and grades, so as to form an evaluation of students’ learning effects by classification. The study also predicted the importance of various factors that might influence learning outcomes. The research results verify the effectiveness of K-means clustering method in evaluating students’ learning effect. The application of this evaluation method can enable students to improve themselves in a targeted way, and also help teachers find potential problems in SPOC teaching mode, so as to further improve the teaching quality.
- 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 - Yuhan Shi PY - 2022 DA - 2022/12/12 TI - Exploring the Evaluation of College Students’ Learning Effect Under SPOC Teaching Mode Based on Cluster Analysis BT - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022) PB - Atlantis Press SP - 495 EP - 503 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-024-4_52 DO - 10.2991/978-94-6463-024-4_52 ID - Shi2022 ER -