Bridging Asynchronicity and Engagement: Data-Driven Insights Into Flipped Learning

Abstract

Advocates of flipped and blended learning have reported on how these models encourage students to actively engage and become agents in their own learning. There is, however, limited evidence on the extent to which asynchronous online learning materials developed for flipped learning programmes support students to actively engage in their learning. Using back-end data analytics, this study aims to demonstrate the behaviour patterns exhibited by students in a programme where 30% of the flipped learning curriculum design is delivered asynchronously online. A cross-sectional case study research design within a quantitative framework was used. Online content used to teach foundational year students (n=3957) English for Academic Purposes at a British-Asian university in China was analysed. This included teacher-generated videos, comprehension quizzes, and activities linked to subsequent in-person sessions. A prominent finding of this study is that students do in fact take advantage of the unrestricted access to online materials, although overall asynchronous student engagement still needs in-class teacher action to be supported. In summary, data-led investigations into students’ online behaviour can advance the pedagogical design and underpinnings of flipped learning along with enhancing educators' adeptness in navigating blended learning environments.



Author Information
Ivana Vulic, Xi'an Jiaotong Liverpool University, China
Alan Meek, Xi'an Jiatong Liverpool University, China

Paper Information
Conference: ACE2023
Stream: Design

This paper is part of the ACE2023 Conference Proceedings (View)
Full Paper
View / Download the full paper in a new tab/window


To cite this article:
Vulic I., & Meek A. (2024) Bridging Asynchronicity and Engagement: Data-Driven Insights Into Flipped Learning ISSN: 2186-5892 The Asian Conference on Education 2023: Official Conference Proceedings https://doi.org/10.22492/issn.2186-5892.2024.161
To link to this article: https://doi.org/10.22492/issn.2186-5892.2024.161


Comments & Feedback

Place a comment using your LinkedIn profile

Comments

Share on activity feed

Powered by WP LinkPress

Share this Research

Posted by James Alexander Gordon