Smart Environments and Analytics on Video-Based Learning

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Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...

Addressing the complex challenges of sustainability demands for good teamwork abilities for future technicians and engineers. In our three institutions we adopted project-based learning to facilitate the development of these skills – but is this enough? Si ...

In this paper we present the Open Software Services for Classrooms and Research (OSSCAR) platform. OSSCAR provides an open collaborative environment to develop and access educational resources in the form of web applications, for which various deployment m ...

The presence of conversational agents (or chatbots) in educational contexts has been steadily increasing over the past few years. Recent surveys have shown widespread interest in the use of chatbots in education, both for research and practice. Although th ...

The paper presents ICAP (interactive, constructive, active and passive) as the theoretical framework to understand the role of informal learning spaces as an active learning tool when students have informal meetings to work on projects. Students in our En ...

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-supervised learning models fail to leverage information across multiple data t ...

Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support the pr ...

Smart Environments and Analytics on Video-Based Learning

Chat with Graph Search

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Co-constructing an Effective, Sustainable and Scalable Primary School Computer Science Curricular Reform

FROM GROUP WORK TO TEAM WORK: COMPARATIVE ANALYSIS IN THREE EUROPEAN INSTITUTIONS

OSSCAR, an open platform for collaborative development of computational tools for education in science

A Conceptual Framework for Integrating Conversational Agents in Digital Education

Work in progress: Imagining / Designing informal spaces for learning

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

XTab: Cross-table Pretraining for Tabular Transformers

Active Learning for Imbalanced Civil Infrastructure Data