Posted by @natasabrouwer on April 16, 2022, 2:19 p.m. Contact: @natasabrouwer


Motivation for this project

VITAL - Visualisation Tools and Analytics to Monitor Online Language Learning & Teaching (2015-2017)

Students involved in e-learning often have a limited knowledge of their own learning habits and which rate of studying with the online material is required. To succeed in (semi-)autonomous learning, however, a higher level of self-regulation is needed.
Find here an nteractive animation about Learning Analytics, xAPI and the VITAL project and test your knowledge!

Aims of the project

This Erasmus+ project aims to establish a clear image of how higher education students in different European countries learn online through the use of learning analytics. The project aims at the development of a generic model for implementing learning analytics in interactive e-learning tools, which can be reused in different educational settings, countries, courses.

The goal is to map existing learning patterns in 4 different types of online language learning and teaching and maths courses and to feed back this new knowledge to the most important educational actors themselves, being the students and their lecturers. The focus is on the courses used and the students’ learning trails through these courses, and process mining techniques will be used for the analysis of the data. The University of Amsterdam, Faculty of Science focus on math courses.

Special care is given to ease of use of the dashboards for non-specialist users. These applications allow both the teachers and the students to understand how they learn online but also to compare their profile to user patterns of their peers. Educators get dynamic and real-time overviews of how their students are progressing, which students might be at risk of dropping out or of failing for the course and which parts of the courses cause difficulties/require more feedback

The project outputs aim to be used by or presented to the student and instructor target groups but more generally also to all stakeholders in the field of educational innovation and research on a European level. All technologies, models, algorithms, reports, guidelines, recommendations get their disposal under open licenses.


A complimentary and cross-disciplinary consortium of teams from three universities and a private open source company was set up:

  • Universiteit Hasselt (Centrum voor Toegepaste Linguïstiek) (BE) (coordinator)
  • University of Central Lancashire (School of Language, Literature and International Studies) (UK)
  • Universiteit van Amsterdam (Faculty of Science) (NL)
  • HT2 (UK)

Project leader VITAL: Anouk Gelan (Universiteit Hasselt)
Project partner leader University of Amsterdam: André Heck
Project partner leader University of Central Lancashire: Michael Thomas
Project partner leader HT2: Ben Betts

Start project: October 2015

End project: October 2017

Funding: Erasmus+, Strategic partnerships, KA2 Higher Education (2015-1-BE02-KA203-012317)


The VITAL project: some research findings

  • The data analysis based on detailed xAPI course activity tracking allowed us to acquire various insights into the online learning behaviour of students, such as the regularity of online learning, time spent learning online, planning of activities (when, which contents), most difficult/used/repeated activities, use of functionalities such as discussion forum, dictionary, etc., activity between types of resources and navigation patterns.
  • The comparison of educational cases indicated that course design strongly determines the online learning engagement of students, e.g. the class schedule in a flipped learning design, the organisation of assessments at fixed intervals in a mastery learning design or posting feedback on online assignments in a task-based course design.
  • Online engagement correlated with study success for most cases.
  • Based on cluster analysis, several student profiles could be identified according to their online learning behaviour, and certain learning patterns appeared to be more performed by successful students.
  • Specific functionalities in the online courses appeared to be under-used and are open to revision or to be brought more clearly to the attention of students.
  • Correlations between specific learning activities and study success were used as input for the student and instructor dashboards developed by the project. These were implemented to advise students on their progress and recommended uses of the courses and to adapt their learning behaviour in a timely manner. Instructors are enabled to monitor the progress of their students in the course of the semester and to know which students are at risk of for which course contents more feedback is needed.
Original author: Natasa Brouwer
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