Temporal analysis of multimodal data to predict collaborative learning outcomes

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With recent innovations in artificial intelligence (AI), machines can now recognize architectural patterns and generate new forms in ways that far exceed human capacity. The integration of machines in the design process has ushered in a substantial shift i ...

PolyGloT, a novel framework for educators and students, is designed to create, curate, and engage in personalized learning paths in digital education. This open, adaptable, and versatile framework facilitates the design and consumption of adaptive learning ...

Learning manipulation from demonstration is a key way for humans to teach complex tasks. However, this domain mainly focuses on kinetic teaching, and does not consider imitation of interaction forces which is essential for more contact rich tasks. We propo ...

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

Research on Computer-Supported Collaborative Learning (CSCL) has provided significant insights into why collaborative learning is effective and how we can effectively provide support for it. Building on this knowledge, we can investigate when collaboration ...

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, ...

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

Twitter is a popular micro-blogging service on theWeb, where people can enter short messages, which then become visible to some other users of the service. While the topics of these messages varies, there are a lot of messages where the users express their ...

This paper discusses the potential role of social software in supporting teamwork and collaborative project management in higher education. Based on the fact that social software has been widely spread among young students nowadays, using it for collaborat ...

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

Information is the resolution of uncertainty and manifests itself as patterns. Although complex, most observable phenomena are not random and instead are associated with deterministic, chaotic systems. The underlying patterns and symmetries expressed from ...

This paper focuses on Engineering Education Research on Technology Enhanced Learning carried out at the Swiss Federal Institute of Technology in Lausanne (EPFL), and on its current focus on personal and collaborative learning. After some thoughts on the di ...

We live in a rapidly changing digital world marked by technological advances, and fraught with online information constantly growing thanks to the Internet revolution and the online social applications in particular. Formal learning acquired in traditional ...

Faces play a vital role in people's daily lives, as they are able to convey many different information and above all their behaviour and emotions. Therefore, for decades the face has been investigated by researchers in several fields such as computer scien ...

In crowding, the perception of a target is impeded by surrounding clutter. While traditional models are feedforward and local, there is increasing behavioral and neural evidence for a critical role of recurrent processing across the visual hierarchy in cro ...

Decentralized training of deep learning models is a key element for enabling data privacy and on-device learning over networks. In realistic learning scenarios, the presence of heterogeneity across different clients' local datasets poses an optimization ch ...

Temporal analysis of multimodal data to predict collaborative learning outcomes

Chattez avec Graph Search

Deep Architectural Form

Scalable Personalized Education in the Age of GenAI: The Potential and Challenges of the PolyGloT Framework

Learning Motion Reconstruction from Demonstration via Multi-Modal Soft Tactile Sensing

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Multimodal person recognition in audio-visual streams

It is not either or: An initial investigation into combining collaborative and individual learning using an ITS

Perspective Aware Road Obstacle Detection

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

A benchmark dataset for machine learning in ecotoxicology

Interpretable Representation Learning and Evaluation for Abstractive Summarization

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Entity-based Classification of Twitter Messages

Using Social Software for Teamwork and Collaborative Project Management in Higher Education

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Measurement in the Age of Information

Tackling Engineering Education Research Challenges: Web 2.0 Social Software for Personal Learning

The 3A Interaction Model and Relation-Based Recommender System : Adopting Social Media Paradigms in Designing Personal Learning Environments

Automatic face analysis in static and dynamic environments

The role of population receptive field size and recurrent processing in learning to “de-crowd”

Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data