RESEARCHER IN THE SPOTLIGHT
Charlotte Larmuseau
Online learning environments are increasingly being used, both in education and in business contexts. This form of learning offers numerous advantages; the learner can learn where and when he wants and determines his own pace. However, not all learning environments appear to be equally effective and there is often a high dropout rate.
Charlotte Larmuseau’s PhD project focuses on the effectiveness of online learning environments. This focus has to do with our ever more rapidly evolving society. Within the labour market, jobs where routine skills are practiced are increasingly being replaced by technology, with the result that higher demands are made on workers. Online learning environments today need to focus on complex learning content in order to reflect the complexity of today’s society. The findings of these study(s) can therefore provide important guidelines for the design of online learning environments.
For this project, Charlotte crosses national borders. It is a joint PhD, i.e. there is a collaboration between itec and CRiSTAL, a research group at the University of Lille specialising in computer science. Bringing together this expertise is an immediate added value for this research project.
Ideally, learning tasks should match the cognitive, affective and motivational characteristics of the learner and be designed in such a way that they can match the prior knowledge. Subsequently, the learning tasks must also be challenging so that the learner remains motivated.
The first results mainly showed that, regardless of how the learning environment is used, prior knowledge largely determines the learning gain. Pupils without prior knowledge achieve less learning benefit, which may be due to the excessive ‘cognitive overload’ of these learners, as a result of which they drop out more quickly.
Through these findings, Charlotte focuses more on the learning process in a second phase, in order to identify the cognitive (over)load in processing the learning content and also to investigate how the learning process can be adapted to improve the learning outcomes.
Cognitive overload occurs when more information has to be processed than the capacity of the learner’s mental working memory allows. This ensures that the information can no longer be processed and therefore cannot be stored.
The way in which this is researched is explorative in nature; on top of the data experienced by the learner himself, use is made of physiological data. The aim is to investigate how this physiological data relates to cognitive processing. This data is collected on the basis of wearables, which measure skin conductivity and temperature. The changes in heart rate are then also mapped out using ‘chest patches’. These data may possibly indicate when changes take place during the cognitive processing within that learning process. The combination of these data should enable us to detect cognitive (over)load in order to offer tailor-made support.
