A novel learning engagement data model (LEDM) for online attendance system

Aziman, Abdullah and Asar, Abdul Karim and Nur Alnisa’ Anis Alanna, Ruzelan (2020) A novel learning engagement data model (LEDM) for online attendance system. In: IOP Conference Series: Materials Science and Engineering, 6th International Conference on Software Engineering and Computer Systems, ICSECS 2019, 25 - 27 September 2019 , Vistana Hotel, Kuantan. pp. 1-9., 769 (012026). ISSN 1757-8981 (Print), 1757-899X (Online)

Pdf (Open access)
A novel learning engagement data model.pdf
Available under License Creative Commons Attribution.

Download (652kB) | Preview


Student engagement is a very interesting subject in higher education. While many studies assess student engagement through survey, this approach claimed in literatures is lack of contextual analysis for decision making. Our motivation in this study is to integrate a simple way to assess student engagement of face-to-face session in blended learning approach within the online attendance system by identifying the data model supporting insightful analytics. This study aims to propose a new learning engagement data model incorporating behaviour, emotional and cognitive engagement for online attendance system. We found an interesting insight which there is a relationship of student engagements with the learning outcomes attainment. Initial findings in this study show potential values how our proposal may benefit higher education in adopting smarter way to measure student engagement while taking student attendance during face-to-face session in blended learning implementation.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Data model; Novel learning engagement data model; Student engagement
Subjects: L Education > LB Theory and practice of education > LB2300 Higher Education
Q Science > QA Mathematics
Faculty/Division: Institute of Postgraduate Studies
Center for Human Sciences
Faculty of Computing
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 13 Dec 2022 04:25
Last Modified: 13 Dec 2022 04:25
URI: http://umpir.ump.edu.my/id/eprint/28805
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item