Assuring the quality of online learning in higher education: Adaptations in design and implementation

Abstract

In higher education, designing online courses aligned with students’ preferences impacts learning effectiveness. Our research aimed to investigate which learning design elements can affect the quality of online learning. To achieve this, we followed a systematic literature review, identified current trends and conducted an online survey outlining university students’ opinions. The results revealed that students’ preferences agree with universal learning design principles, acting as course quality determinants. These elements relate to the structure, appearance, content, interactivity of the course and support in the online setting. We recommend that courses are well organised and include authentic resources, activities and assessments, divided consistently into smaller, topic-based chunks that resemble experiences drawn from real life. The objectives need to be communicated while the expected behaviours are known to students. The respective workload must be equally distributed across the course spectrum in an environment that balances collaborative and self-paced learning. Students must be familiar with the technology, which is also an easy-to-access gate. Lastly, it is suggested that technical and pedagogical support is constantly present so that participants efficiently work in the online context.

Implications for practice or policy:

• In collaboration with educators, instructional designers can use the quality indicators that emerged through the study when designing and evaluating higher education courses.
• Instructional designers and educators may prioritise learners' autonomy, aligning course requirements with students' sense of control.
• Instructional designers and educators can distribute students’ workload equally throughout the course, without strict deadlines, to improve the learning experience.
• Educators may promote collaborative assignments but moderately balance them with an individual-based assessment mode.