Erasmus+, Strategic partnerships, KA2 Higher Education (2015-1-BE02-KA203-012317)
Although most HE institutions have embraced the potential of e-learning methods and have invested in technology-enhanced learning environments and tools, we do not have a clear picture of students’ online learning habits. The understanding of concrete learning behaviour and uses of electronic courseware and online resources is an important prerequisite to assess the quality of autonomous, lifelong learning.
Moreover, 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.
This project proposal addresses the Erasmus + challenge of raising the quality of education through the use of learning analytics. Learning analytics is a new and promising research field which can be defined as “the measurement, collection, analysis and reporting of data about learners in their context, for purposes of understanding and optimizing learning and the environment in which it occurs” (Siemens et. Al). The recent evolution of web-based learning and the possibility of tracking students’ online behaviour offers promising new ways of measuring actual self-study activities.
This project aims to establish a clear image of how higher education students in different European countries learn online. 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. A bottom-up learning analytics approach will be used taking the perspective of the learning process. The focus will be 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. Therefore, a complimentary and cross-disciplinary consortium of teams from three universities and a private open source company was set up.
- implement tracking of learning data based on the new Experience API standard for interoperability with other learning environments (e.g. mobile apps, games) and Blackboard learning data
- pilot the implemented tracking technology, test data and process lining algorithms
- collection of data: the learning behavior of several student groups enrolled in distance learning or university programmes with an important self-study component will be tracked during one semester. The data will be collected in a central repository (Learning Record store) or in Blackboard LMS. An important point of concern in the project will be the privacy of the students who will be monitored and data protection.
- analyse the processes of autonomous learning comparing them to the intended pedagogic objectives of the tools. Detection of patterns of learning behaviour, exploration of user profiles to be identified and feedback about used learning resources.
- development & implementation of data visualisation tools in order to create a learning dashboard application for students and for teachers.
Special care will be given to ease of use of the dashboards for non-specialist users. These applications will 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 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 project outputs will 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 will be put at their disposal under open licenses.
- 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)
01.10.2015 - 31.12.2017
Prof. M. Verjans
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