Recherche

Afficher tous les résultats pour

Accueil

Publication

Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (41)

Page 2 sur 3

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon

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 ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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

Giovanni Pizzi, Sara Bonella, Dou Du

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 ...

ELSEVIER2023

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Tanja Christina Käser Jacober, Jibril Albachir Frej, Tatjana Nazaretsky

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

2023

A Conceptual Framework for Integrating Conversational Agents in Digital Education

Juan Carlos Farah

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 ...

EPFL2023

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

Tanja Christina Käser Jacober, Paola Mejia Domenzain, Thiemo Wambsganss, Luca Mouchel

Revision behavior in adaptive writing support systems is an important and relatively new area of research that can improve the design and effectiveness of these tools, and promote students' self-regulated learning (SRL). Understanding how these tools are u ...

Zenodo2023

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

Isabelle Jeanne Lydie Lermigeaux-Sarrade

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 ...

2023

Inclusive engineering classrooms: student teaching assistants' perspectives

Siara Ruth Isaac, Joelyn de Lima, Helena Kovacs

Inclusive teaching is the intentional practice of recognising biases, working to mitigate their impact, and ensuring that students have equitable learning opportunities. In addition to improving students' sense of belonging and self efficacy, inclusive tea ...

TU Dublin2023

Revisiting adversarial training for the worst-performing class

Volkan Cevher, Grigorios Chrysos, Thomas Michaelsen Pethick

Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...

Journal of Machine Learning Research Inc.2023

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

Laila Abdelsalam El-Hamamsy

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 ...

EPFL2023

EEG-Based Online Regulation of Difficulty in Simulated Flying

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ping-Keng Jao

Adaptively increasing the difficulty level in learning was shown to be beneficial than increasing the level after some fixed time intervals. To efficiently adapt the level, we aimed at decoding the subjective difficulty level based on Electroencephalograph ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Work in progress: Imagining / Designing informal spaces for learning

Ingrid Le Duc, Isabelle Jeanne Lydie Lermigeaux-Sarrade

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 ...

Aalborg Universitetsforlag2023

The iReCheck project: using tablets and robots for personalised handwriting practice

Pierre Dillenbourg, Barbara Bruno, Daniel Carnieto Tozadore, Chenyang Wang, David Cohen

Handwriting is an important skill in children development as well as in education that take years to be mastered. While keyboards and similar technological devices increasingly become more popular, new tools and engaging approaches are also required to kee ...

Association for Computing Machinery2023

Evaluation of teachers’ orchestration tools usage in robotic classrooms

Pierre Dillenbourg, Barbara Bruno, Aditi Kothiyal, Sina Shahmoradi

Teachers’ self-efficacy in managing classrooms is an important consideration when it comes to bringing educational robots to classrooms. Orchestration tools support teachers by providing awareness indicators of students’ progress as well as levers to contr ...

2023

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Christian Leinenbach, Sergey Shevchik

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

Elsevier Sci Ltd2023

Simulated Learners in Educational Technology: A Systematic Literature Review and a Turing-like Test

Tanja Christina Käser Jacober

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be use ...

SPRINGER2023

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Leonardo Petrini

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

EPFL2023

How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps

Francesco Mondada, Barbara Bruno, Jessica Elke Dehler Zufferey, Laila Abdelsalam El-Hamamsy, Sunny Jonathan Jean-Jacques Laurent Avry

Background Early exposure to Computer Science (CS) and Computational Thinking (CT) for all is critical to broaden participation and promote equity in the field. But how does the introduction of CS and CT into primary school curricula impact learning, perce ...

2023

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Martin Jaggi, Thijs Vogels, Hadrien Hendrikx

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets

Olga Fink

Finding optimal bidding strategies for generation units in electricity markets would result in higher profit. However, it is a challenging problem due to the system uncertainty which is due to the lack of knowledge of the strategies of other generation uni ...

PERGAMON-ELSEVIER SCIENCE LTD2023

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Willem Anna Mark Wybo, Bernd Albert Illing

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contex-tual sta ...

National Academy of Sciences2023