Measurement Indicators of Student Engagement and Investigation on Student Engagement in Blended Learning
- DOI
- 10.2991/978-94-6463-040-4_125How to use a DOI?
- Keywords
- blended learning; digital technology; student engagement; measurement indicator; Superstar platform; quantitative research
- Abstract
With the influx of technology, Blended Learning (BL) has become a new and important teaching method in colleges and universities. Digital technology in BL environment inherently affecting all aspects of the student experience. Superstar platform can increase students’ behavioural, affective(emotional) and cognitive (intellectual) engagement in various ways. The identification of influencing factors and measurement indicators of student engagement in blended learning environment are indistinct in current literature. This paper identifies influencing factors and measurement indicators of student engagement in blended learning through analysis, then clarify indicators regarding what should be focused on to improve student engagement and indicate the measurement indicators with Superstar platform. In addition, this paper uses quantitative research to provide analyses and countermeasures of the student engagement in blended learning.
- 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 - Xiaoyan Zhao AU - Izaham Shah Ismail AU - Suthagar Narasuman PY - 2022 DA - 2022/12/27 TI - Measurement Indicators of Student Engagement and Investigation on Student Engagement in Blended Learning BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 823 EP - 829 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_125 DO - 10.2991/978-94-6463-040-4_125 ID - Zhao2022 ER -