Itec is an interdisciplinary research group, we combine methods from a variety disciplines in carrying out projects. More concrete our expertise lies within four main disciplines.
Within instructional design and technology we focus on the design, development, implementation and evaluation of technology-enhanced learning environments. The effectiveness of these technology-enhanced learning environments is assessed in view of cognitive, non-cognitive and efficiency learning outcomes and taking into account individual differences between learners. The effectiveness is determined based on log data, physiological data, self-reports and assessments.
We do not only focus on adapting and personalizing learning content based on collected learning data, we also study how the learning support (feedback, tools, material, ...) can optimally be adapted and personalized.
Based on the statistical modelling and tracking of latent characteristics of learners and predictions made on outcomes, we go one step further by adapting and personalizing the content of learning environments.
We especially focus on the instructional design of learning environments aiming to support complex learning (e.g. the so-called '21st century skills'). The role of technology is essential in realizing these complex objectives.
The increasing possibilities of educational technology offer enormous potential to provide more interaction between students, learning content and teachers, not only on campus but also off campus. With the hybrid virtual classroom we have developed (infrastructure) a learning space that offers flexibility to learners meanwhile sustaining the important interaction of education in a face-to-face setting.
Although the value of collaborative learning is widely recognized, successful teamwork is not guaranteed. We investigate how we can optimize support and assess collaborative learning by means of technology in ambient learning spaces.
Adaptive educational games –adjusting the difficulty level to
children’s performance in the game– can be promising to foster
cognitive, non-cognitive, and efficiency outcomes.
Increase the development of social innovation applications in order to make more efficient and effective local services to address the key societal challenges in the 2 Seas area.
Gepersonaliseerd digitaal leren in het Vlaamse onderwijs. Leren op maat van elk kind wordt internationaal vaak als de toekomst van ons onderwijs naar voor geschoven.
COgnitive Support in Manufacturing Operations. The manufacturing industry is faced with increasing product diversification due to changing customer needs and market demands, which is putting stress on operators.
Strategic Partnership for Higher Education. The European EdTech Network (EETN) is a three-year project funded by the European Commission within the Erasmus+ Strategic Partnership for Higher Education programme.
Smart Education @ Schools is een innovatieprogramma voor leerkrachten in het basis- en secundair onderwijs en in de volwasseneneducatie die de uitdagingen van hun onderwijspraktijk willen aanpakken met slimme educatieve technologie.
Measurement and remediation of overload during assembly work in Industry 4.0
Effective LEarning in remote Classrooms through Technology-enhanced UseR Engagement.
Leadership requires domain-related knowledge, but also transversal skills such as the ability to think critically
A behavioural and neurological study.
Eén van de essentiële aspecten bij het leren is feedback
Empirical data play a key role in the application domains studied by itec. These include a wide variety of quantitative and qualitative data and structured and unstructured data. Within statistical modeling, itec further develops, evaluates and applies complex statistical techniques for collecting, visualizing, and modeling quantitative data. Although the techniques in principle are often widely applicable across domains, this strand of research is feeded by questions and challenges within itec’s application domains, and in turn advances the applied research.
One of the challenges we focus on is the measurement of variables that are not directly observable, by using psychometric techniques and models (e.g., IRT) and combining different types of data.
Based on the statistical modelling and tracking of latent characteristics of learners and predictions made on outcomes, we go one step further by adapting and personalizing the content of learning environments.
We develop algorithms to predict data values for new observations in a dataset and to recommend the most relevant set of items for a given user.
Models and techniques are proposed and evaluated to combine the results of multiple studies in order to increase precision and power, with a focus on the modelling of dependent study results and the results of single-case experimental studies.
Gepersonaliseerd digitaal leren in het Vlaamse onderwijs. Leren op maat van elk kind wordt internationaal vaak als de toekomst van ons onderwijs naar voor geschoven.
COgnitive Support in Manufacturing Operations. The manufacturing industry is faced with increasing product diversification due to changing customer needs and market demands, which is putting stress on operators.
Policy Research Centre for Test Development and National Assessments
Measurement and remediation of overload during assembly work in Industry 4.0
Effective LEarning in remote Classrooms through Technology-enhanced UseR Engagement.
Policy Research Centre for Test Development and National Assessments
Further developments and empirical validation
Handling data and design complexities.
The focus of this postdoctoral research is multilevel modeling of single-case experimental design
An evaluation of the methodological and psychometric quality of language assessments, and training and support in the implementation and automatization of statistical analyses.
We do not only focus on adapting and personalizing learning content based on collected learning data, we also study how the learning support (feedback, tools, material, …) can optimally be adapted and personalized.
Adaptivity of complex learning tasks This PhD project focuses on
COgnitive Support in Manufacturing Operations. The manufacturing industry is faced with increasing product diversification due to changing customer needs and market demands, which is putting stress on operators.
European network for combining language learning with crowdsourcing techniques.
Research and innovation for online learning. Seven partners on both sides of the French-Belgian border, including universities, training and research centres, are working together on a common project.
A behavioural and neurological study.
A blended learning environment for the integrated acquisition of pedagogical content knowledge
Dit project onderzoekt de effectiviteit van verrijkingstechnieken bij audiovisuele input (video) om de diepte of kwaliteit van woordenschatverwerving bij tweedetaalleerders Frans te stimuleren.
Theoretical and empirical validation of lexical competence in French within the Common European Framework of Reference.
Videostreaming as an interactive didactic instrument in computer-assisted language learning.
COmunication and building Bridget thanks to the Acquisition of Languages trough Technologies
Within machine learning and AI, we adapt existing and develop new machine learning algorithms to tackle open questions in the applications domains of itec. We mainly focus on non-standard supervised and semi-supervised learning tasks, such as multi-output prediction, time-to-event prediction and interaction prediction. We typically target three goals in our methods: predictive performance, efficiency and interpretability.
Based on the statistical modelling and tracking of latent characteristics of learners and predictions made on outcomes, we go one step further by adapting and personalizing the content of learning environments.
We develop algorithms to predict data values for new observations in a dataset and to recommend the most relevant set of items for a given user.
Data in various domains is two-dimensional: there are two data types and the values of interest
COgnitive Support in Manufacturing Operations. The manufacturing industry is faced with increasing product diversification due to changing customer needs and market demands, which is putting stress on operators.
Personalized, user-controlled news distribution based on conversational user interfaces to drive user engagement, conversion and retention. An imec-project (2019-2021).
Eén van de essentiële aspecten bij het leren is feedback