Open AccessA Novel Learning Engagement Data Model (LEDM) for Online Attendance System
Author(s) -
Abdul Adam Abdullah,
Asar Ak,
Nur Alnisa’ Anis Alanna Binti Ruzelan
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/769/1/012026
Subject(s) - attendance , student engagement , learning analytics , session (web analytics) , blended learning , psychology , analytics , computer science , higher education , face to face , mathematics education , educational technology , medical education , data science , world wide web , medicine , philosophy , epistemology , political science , law , economics , economic growth
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.