Abstract:

In education, few would argue against the importance for academic institutions, teachers and instructional designers to capture, develop, maximise and maintain the level, intensity and persistence of the students’ engagement in their learning experience. This is hardly surprising as researchers have found student engagement to be positively associated with academic performance and persistence, as well as other positive academic, social and emotional outcomes such as attendance, social awareness and emotional self-regulation.

More recently, researchers have turned their attention to the factors that promote learner engagement in an online context, thanks largely to the widespread adoption of massive open online courses (MOOC), the democratisation of online and blended learning in traditional academic institutions, and the more recent legitimisation of online learning as a viable alternative to the face-to-face mode of delivery in times of crises such as the COVID-19 pandemic.

This paper proposes an antecedent-consequent framework for employing online engagement as a decision criterion in digital course design. Its application is illustrated via a marketing course with two different course designs (the antecedents). Using data from Canvas, a learning management system (LMS), and an online engagement framework developed by Tan & Koh (2018), nine online access metrics are computed to measure different aspects of online learning engagement for each of the two course designs. Subsequently, based on the online engagement behaviour desired (the decision criterion), the appropriate digital course design is identified and can then be implemented to enhance learning outcomes (the consequents).

The rationale underlying the antecedent-consequent framework focused on online engagement to aid digital course design is that online engagement is important as it is associated with positive outcomes. Also, online engagement is itself affected by course design, among other factors. Hence, by mapping the associations between various course designs and the resulting online engagement metrics computed with LMS data and learning analytics, an appropriate course design can be identified leading to the desired online engagement behaviour, which will in turn, lead to positive outcomes.

The proposed framework assumes the availability of alternative course designs and their resultant online engagement behaviours as measured with LMS data. Despite this limitation, it is hoped that this study can help instructors and course designers develop courses that can better enhance learning outcomes and learner experience.

Keywords:

Learner engagement, online learning behaviour, operationalization of online engagement, framework for online engagement, course design.