The COVID-19 pandemic has simply added to the ever more rapid growth in online learning since 2005. Online education generates massive income, with the global e-learning market estimated at US$144 billion in 2019 and predicted to reach US$374 billion by 2026. However, universities have struggled to reduce high online student dropout rates – online students are 2.5 times more likely than on-campus students to withdraw without a qualification.
Advances in online educational technology have helped universities tap new and lucrative markets. Students with complex lives who are unable to attend on-campus classes prefer online learning. Yet introductory online modules frequently have a dropout rate of more than one in five students.
This high dropout rate costs universities millions in lost revenue every year. It also creates a poor perception of online education. Yet universities are still neglecting the main causes of dropout identified in our research.
The scale of online dropouts means small improvements can be worth a lot to universities. As COVID-19 forced many programs online and reduced revenue from international students, universities have increased efforts to improve online retention. Current interventions include massive investment in learning technology.
However, these efforts are having little if any impact on the persistently high dropout rate.
There has been substantial research on this issue. Shallow understanding and universities not responding to the root dropout causes have been identified as the underlying problem.
Past online retention studies have often failed to provide insights into all drivers of dropout or ways to overcome them. The small samples often used in qualitative studies have been identified as a shortcoming that explains this deficiency.
Our research on open online education dropout can help.
The study included 200 in-depth interviews with online dropout students. This sample is much larger than past qualitative retention studies. It enabled us to explore the full range of dropout reasons down to those that explain 5% of dropouts.
What did the study reveal about causes?
The CDU-led study identified more than 40 dropout causes within ten broad themes. Personal circumstances were the major drivers. Over 65% of the main dropout reasons fell into this category.
Personal circumstances include broad dropout themes relating to students’ employment, family and relationships, health, personal situation and location. We identified many subthemes that provide more detailed insights into each of these aspects.
Learner context aspects accounted for almost one-quarter of the main dropout reasons. These include the students’ enrolment approach and motivation, study time management and learning resources and experience.
Only 10% of main dropout reasons related to administrative issues and module design and delivery. Yet universities’ retention efforts often focus primarily on these aspects.
What did the study reveal about reducing dropout?
To be effective, retention initiatives must respond to the major dropout causes. However, personal circumstance are often seen as being an “uncontrollable” dropout dimension and beyond universities’ ability to accommodate.
Our study sought students’ suggestions about how the university could have helped to prevent their dropout. We identified 19 dimensions within five dropout intervention themes. Many of these relate to the students’ personal struggles and study-life challenges, which retention initiatives often ignore.
A common suggestion was to develop students’ study skills and build their resilience before they start their courses. This would help students set realistic study goals and develop strategies for coping with study-life challenges and personal commitments.
The students often mentioned that university policies and processes did not allow for their personal challenges. At the end of the day, even the best learning technologies can’t help a parent looking after a sick child, or an employee covering for a sick colleague. Universities need to pay much more attention to such issues.
Students with sudden temporary increases in personal demands need simpler processes for requesting extensions and adjusting hand-in dates.
For longer-term disruptions, offering flexible semesters and micro-credentialling modules – breaking courses into smaller credit-bearing components – can help. This will allow students to drop out part-way in one semester and later resume study where they left off.
Students wanted such interventions to be made available without financial or academic penalty. They could then easily resume study once a personal challenge has subsided.
They also frequently mentioned assessment design and policies in relation to module completion. For example, providing alternative assessment options and more flexible submission dates would allow for students’ unpredictable changing personal circumstances.
Unis need to rethink their approach
Universities can do more to reduce the persistently high dropout rates that plague online education. First, however, they must recognise the shortcomings of their intervention strategies. Currently, their focus is mainly on “controllable” dropout dimensions and learning technology and design.
To reduce online dropout universities must respond to the main dropout causes, which relate to students’ personal circumstances. Universities need to appreciate dropout from the students’ perspective. They can then give priority to interventions that respond effectively to students’ complex life circumstances.