HSE University scholars uncover E-learning preferences of top students

HSE University experts have analysed students’ digital footprints and shown for the first time that final grades depend on one’s personal approach to an online course. Balanced students have proven to be more successful than those who follow a more traditional and practical approach. The findings from this study will help create a more adaptive and personalised educational system. This research has been published in the journal The Internet and Higher Education.

E-learning offers students the flexibility to study at their own pace and choose where to begin. However, it was unknown how a student’s personal choices affect their ability to assimilate knowledge, and how an individual's pattern of switching to a particular type of educational material translates into a specific cognitive load.

Researchers Anna Gorbunova and Ksenia Adamovich from HSE University’s Institute of Education, as well as Alexander Savelyev, Associate Professor at the Faculty of Law, and Jamie Costley from the UAE University, explored how students’ individual approaches to completing online courses are related to their cognitive workload allocation and academic achievement. The study included 90 master’s degree law students enrolled in an online course on the legal protection of personal data. The students had access to three types of materials: video lectures, video case studies, and practical exercises based on legal cases.

To record every action of e-learning students, the researchers used a system for collecting log files (digital footprints) embedded in the educational platform itself. Each click, view, pause, or transition of a student in the interface was automatically recorded as an event in the database, indicating the type of action, timestamp (to the nearest second), as well as user ID and material.

Analysis of these digital footprints revealed three behavioural types. Representatives of the first behavioural type, traditional (27 students), spent a lot of time watching lectures, turned less often to practical tasks, and performed the fewest actions on the platform.

The second type, balanced (30 people), tried to distribute time evenly between lectures, analysis of examples, and study of ready-made solutions. These students were most efficient in terms of time.

The researchers called the third style practice-oriented (33 students). These students immersed themselves in solving cases and working with examples, spending significantly less time on lectures and actively switching between materials.

‘The main discovery was how these styles relate to final test results. Students with a balanced behaviour type received the highest scores. Practice-oriented students turned out to be at an average level. They also reported significantly lower levels of internal cognitive load than traditional ones, meaning the topic seemed less challenging to them. But this did not help them achieve the highest results. The traditional type scored the fewest points,’ said Anna Gorbunova.

To understand the relationship between a particular type of student behaviour and the results obtained, the researchers used structural modelling, a statistical method that allows them to test complex relationships between multiple variables simultaneously. The study showed that higher scores among balanced students were associated with an increased relevant cognitive load, which is the mental effort that leads to a deeper understanding of the subject matter. At the same time, the level of external load caused by choosing what to watch and in what order in an online course was approximately the same for all students, regardless of their learning style.

‘We came to the conclusion that success in online learning with elements of independent choice is determined not only by the quality of the content but also by how the student uses this content. Passively following the path of least resistance (traditional style) or engaging in practice to the detriment of theory (practice-oriented type) may be less effective than conscious, even interaction with different types of educational materials. This knowledge allows us to move from universal course design to personalised support,’ explained Anna Gorbunova.

The researchers hope that in the future, it will be possible to create systems that can monitor a student’s learning style in real time based on their digital footprint and provide personalised recommendations. This would allow online education to become not only flexible but also adaptive, helping each student develop the most effective learning strategy for their individual needs.