Publications related to Experiential learning

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Ekaterina Krymova, Mike Seidel, Davide Di Croce, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Iop Publishing Ltd2024

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

Maria del Carmen Sandi Perez, Elias Georges Gebara, Ana del Rocio Conde Moro

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

Springer2024

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Tanja Christina Käser Jacober, Thiemo Wambsganss

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

2024

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Seyedbehzad Bozorgtabar

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Elsevier2024

How to Support Students to Cultivate Psychological Safety in their Teams

Francesco Mondada, Jessica Elke Dehler Zufferey, Yousef Jalali

The importance of psychological safety in teams has been demonstrated in different settings. Team performance improves when team climate allows team members to be their authentic selves, to ask questions and raise concerns comfortably. However, it is less ...

EPFL2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking

Denis Gillet, Juan Carlos Farah, Adrian Christian Holzer, Abdessalam Ouaazki

As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...

2024

How to support students to develop coaching and peer teaching skills

Siara Ruth Isaac, Joelyn de Lima

Students learn more when they are actively engaged in the learning process. While hands-on activities, labs and projects are moments when students are active, the learning benefits can be amplified with coaching strategies. This activity will enable studen ...

EPFL2024

Social Opinion Formation and Decision Making Under Communication Trends

Ali H. Sayed, Virginia Bordignon, Mert Kayaalp

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Unveiling the complexity of learning and decision-making

Wei-Hsiang Lin

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Matthias Grossglauser, Aswin Suresh, Chi Hsuan Wu

We propose an interpretable model to score the subjective bias present in documents, based only on their textual content. Our model is trained on pairs of revisions of the same Wikipedia article, where one version is more biased than the other. Although pr ...

2024

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

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

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

Stéphane Perrin

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

Are engineering teachers ready to leverage the power of play to teach transversal skills?

Roland John Tormey, Siara Ruth Isaac, Jessica Elke Dehler Zufferey, Yousef Jalali, Natascia Petringa

What conceptions do teachers hold about learning activities to develop students’ transversal skills? This qualitative exploration at a research-intensive engineering school draws on interviews and focus groups to explore teachers’ ideas about developing in ...

2023

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Ali H. Sayed, Virginia Bordignon, Stefan Vlaski

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

Inclusive engineering classrooms: student teaching assistants' perspectives

Siara Ruth Isaac, Helena Kovacs, Joelyn de Lima

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

Networked Signal and Information Processing: Learning by multiagent systems

Ali H. Sayed, Stefan Vlaski

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Nirupam Gupta, Shuo Liu

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

Assoc Computing Machinery2023

Action Levers towards Sustainable Wellbeing: Re-Thinking Negative Emissions, Sufficiency, Deliberative Democracy

Sascha Nick

Systems theory defines leverage points as places to intervene in order to change a system. Points with high impact on system behavior are notoriously hard to act upon, and indeed most policy intervention is based at the lowest level (#12 in Donella Meadows ...

EPFL2023