Blended courses, which combine online and face-to-face delivery, are rapidly gaining traction in educational institutions in recent years because of the many benefits they offer. Higher success rate and lower withdrawal rate are just two of the key benefits observed in blended courses in comparison to face-to-face courses (LÃ³pez-PÃ©rez et al., 2011). Many early studies on blended courses focused on the definitions and models (Halverson et al., 2012). Only a few research studies examine the determinants that impact the performance of learners in blended courses. This study aims to bridge this gap in the literature.In particular, this study examines course determinants such as the course discipline (e.g., accountancy, finance, sociology), nature (i.e., qualitative, quantitative or mixed), assessment method (e.g., written or project) and level (i.e., beginner, intermediate or advanced). Analysis is performed at a course level for both blended and face-to-face courses offered from 2014 to 2016. The variable of interest is the average final score of the learners. The effect of time (i.e., whether the determinants change over time) is also investigated. Data mining techniques such as decision trees and logistics regression are used to perform the analysis. This study can provide additional insights to the current literature as it focuses on determinants that affect learners' performance for blended vis-Ã -vis face-to-face delivery mode across time. With a better understanding of the determinants, universities can better structure their courses to exploit the benefits of both blended and face-to-face courses.
Wei Chin, Jess Tan, Singapore University of Social Sciences, Singapore
Hian Chye Koh, Singapore University of Social Sciences, Singapore
Stream: Curriculum Design & Development
This paper is part of the ACE2017 Conference Proceedings (View)
View / Download the full paper in a new tab/window
Powered by WP LinkPress