Projects
Newcomers’ literacy trajectories: mapping and monitoring literacy learning practices, processes and strategies in formal, non-formal and informal spheres. KU Leuven
This doctoral research forms the basis of a broader research project (C2 - Unlocking newcomers’ literacy development: learning for life in formal, non-formal and informal spheres) that focuses on migrant newcomers’ language and literacy development in their new host environment. It explores how they expand their literacy competencies in different situated socialization processes and ecologies, and tries to gain insight into how newcomers’ ...
Implicit Learning and Its Cognitive and Brain Effects on Language Learning With Special Reference to Implicit Music Learning. Vrije Universiteit Brussel
ZoLeerRijk: an interactive learning platform to foster language and learning Ghent University
The research group 'Language, Learning, and Innovation' focuses on assessing and enhancing the reading, writing, and learning performance of primary and secondary school students. Through ZoLeerRijk , we disseminate our evidence-based learning materials aimed at promoting language skills and effective learning. ZoLeerRijk provides educational professionals access to comprehensive lesson packages, informative posters, text ...
Educational platform Language, learning, innovation: Sustainable sharing of evidence-based learning material Ghent University
The research group Language, Learning, Innovation (LLI) has been purposefully focusing on evidence-based intervention research in authentic classroom contexts for many years. Numerous learning materials and professionalization initiatives have already been developed and evaluated. By organizing annual study days and demand-driven individual study courses, we have already focused on disseminating this knowledge and materials to optimize the ...
Deep Learning for Natural Language Processing KU Leuven
As the amount of unstructured text data grows dramatically, the need to intelligently process those text data and extract different types of knowledge from it is also remarkably increasing. One of the goals in natural language processing is to develop general and scalable methods that have the ability to jointly solve tasks like extracting information from big unstructured data, sentiment analysis in social networks and grammatical analysis ...
Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding KU Leuven
Natural language understanding (NLU) by the machine is of large scientific, economic and social value. Humans perform the NLU task in an efficient way by relying on their capability to imagine or anticipate situations. They engage commonsense and world knowledge that is often acquired through perceptual experiences to make explicit what is left implicit in language. Inspired by these characteristics CALCULUS will design, implement and ...
Statistical Relational Learning of Natural Language KU Leuven
computers. The main reasons for this can be found in the structural nature and
the inherent ambiguity of natural language. Correctly interpreting language
therefore requires one to take into account the necessary context. In order
to perform natural language understandingby means of machine learning
techniques, an appropriate representation is ...
Adaptivity in complex language tasks in game-based learning environments KU Leuven
This PhD is carried out within the framework of a Baekeland mandate in collaboration with Linguineo BVBA. Linguineo develops game-based applications for language learning and discovered users’ needs for adaptivity within complex language tasks in the applications. By 'complex language tasks' we mean task-based language activities. Complex language tasks go beyond just exercises and contain different language tasks. The goal is to use language ...
Sign language translation using deep learning Ghent University
To reduce the communication gap between deaf and hearing communities we need a reliable and easytouse sign language translation systems, which is able to convert a video stream into spoken language. In this research we will approach this problem using deep learning techniques.