Factors and Recommendations to Support Students’ Enjoyment of Online Learning With Fun: A Mixed Method Study During COVID-19

Okada, Alexandra and Sheehy, Kieron (2020). Factors and Recommendations to Support Students’ Enjoyment of Online Learning With Fun: A Mixed Method Study During COVID-19. Frontiers in Education, 5(1), article no. 584351.

DOI: https://doi.org/10.3389/feduc.2020.584351

Abstract

Understanding components that influence students’ enjoyment of distance higher education is increasingly important to enhance academic performance and retention. Although there is a growing body of research about students’ engagement with online learning, a research gap exists concerning whether fun affect students’ enjoyment. A contributing factor to this situation is that the meaning of fun in learning is unclear, and its possible role is controversial. This research is original in examining students’ views about fun and online learning, and influential components and connections. This study investigated the beliefs and attitudes of a sample of 551 distance education students including pre-services and in-service teachers, consultants and education professionals using a mixed-method approach. Quantitative and Qualitative data were generated through a self-reflective instrument during the COVID-19 pandemic. The findings revealed that 88.77% of participants valued fun in online learning; linked to well-being, motivation and performance. However, 16.66% mentioned that fun within online learning could take the focus off their studies and result in distraction or loss of time. Principal component analysis revealed three groups of students who found (1) fun relevant in socio-constructivist learning (2) no fun in traditional transmissive learning and (3) disturbing fun in constructivist learning. This study also provides key recommendations extracted from participants’ views supported by consensual review for course teams, teaching staff and students to enhance online learning experiences with enjoyment and fun.

Viewing alternatives

Download history

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About