Mathieu d’Aquin

Mathieu d’Aquin


Current position: Professor of Informatics, Data Analytics and Semantic Web

Research field: Informatics, Semantic Web, Learning Analytics

Research focus within AFEL: Data collection, processing and analytics

What is your main research interest?

I essentially work on data, information and knowledge management, which involves sharing, curating, integrating and analysing information assets through the web.

What are you currently working on? (in the context within AFEL)

Besides coordinating the project, my focus in AFEL is on the data processing part, and especially on data collection and delivery. That includes working on the data platform that will be the central hub for data in the project, as well as looking into the different channels through which we will be collecting data. For what concerns processing the data, I have a particular interest in the tasks of detecting learning activities from data, and assessing their effectiveness.

What is “Analytics of Every Day Learning” for you?

First, it is “Analytics for Everyday Learning” as I believe it should be analytics for the purpose of improving everyday learning, and not only that has for subject every day learning. Therefore, to me, it means a way to give learners an understanding of their own learning behaviour from across all the web platforms that they use, so that they can better control and improve the way they learn.

What are present challenges that the AFEL project can support?

Key challenges are first technical: How to integrate and analyse data coming from so many different platforms? However, the real issue is conceptual: We need to understand learning without being limited by where it takes place. More and more of the learning activities of an everyday learner, whether they are students enrolled in formal studies or not, take place in online platform, social media and collaboration systems. This redefines the way we see learning, and therefore the way learning analytics can help.

What have you learnt from your engagement with Learning Analytics?

I have learnt that it is far from ready for the real life learning as it happens today. Many initiatives exist that demonstrate the potential of the technologies associated with learning analytics, but too few really look at learning behaviours in a complete way with the needed clarity and robustness.

Why should learners use AFEL tools? (What can they expect, which personal requirements are necessary, what benefit do they generate?)

The main reason to use AFEL tools is to understand how we learn, and through that, how we could learn better. The tools collect data about our learning activities and show us the way we are using resources online, collaborating and progressing along our learning paths. This should ideally be available to everybody, so that anybody can discover resources that can be useful, find different ways to achieve specific learning goals, and identify points of view and people who can enrich their learning experience.

What is your vision for “Analytics of Every Day Learning”? (Explain in 2 sentences. What should be achieved after 3 years? Through AFEL, what will have changed for the online social learner?)

Ideally, AFEL will have come up with a set of connected tools that will be able to provide learners with a full picture of their learning activities online, without ever being a burden to them. It should be easy, and obvious to learners that, by engaging with these tools, you can reach a more satisfying and more efficient learning experience. Because of this, providers of online learning platforms, and even platforms not directly dedicated to learning, could also integrate these tools, so to support their users in being more effective learners.