Publications associées à Service-learning

Generative adversarial training of product of policies for robust and adaptive movement primitives

Sylvain Calinon, Emmanuel Pignat, Hakan Girgin

In learning from demonstrations, many generative models of trajectories make simplifying assumptions of independence. Correctness is sacrificed in the name of tractability and speed of the learning phase. The ignored dependencies, which are often the kinem ...

2020

Transferring interactive activities in large lectures from face-to-face to online settings

Pierre Dillenbourg, Jennifer Kaitlyn Olsen, Louis Pierre Faucon

Purpose Within higher education, there was an abrupt shift from face-to-face to online lecturing with the introduction of social distancing measures in light of a global pandemic. The purpose of this study is to enrich the connection between students and i ...

EMERALD GROUP PUBLISHING LTD2020

CoWriting Kazakh: Learning a New Script with a Robot

Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal

In the Republic of Kazakhstan, the transition from Cyrillic to Latin alphabet raises challenges to training an entire population in writing the new script. This paper presents a CoWriting Kazakh system, an extension of the existing CoWriter system, aiming ...

Association for Computing Machinery2020

Combining the Knowledge Appropriation Model and epistemic networks to understand co-creation and adoption of learning designs using log data

Denis Gillet, Maria Jesus Rodriguez Triana

Social practices are well-known mediators in the adoption of educational innovations during professional learning, as postulated by the Knowledge Appropriation Model (KAM). However, understanding how teachers adopt new pedagogical approaches at scale is of ...

2020

Training Channel Selection for Learning-based 1-bit Precoding in Massive MU-MIMO

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Sitian Li

Learning-based algorithms have gained great popularity in communications since they often outperform even carefully engineered solutions by learning from training samples. In this paper, we show that the selection of appropriate training examples can be im ...

IEEE2020

Is There ‘ONE way’ of Learning? A Data-driven Approach

Pierre Dillenbourg, Barbara Bruno, Jauwairia Nasir

Intelligent Tutoring Systems (ITS) are required to intervene in a learning activity while it is unfolding, to support the learner. To do so, they often rely on performance of a learner, as an approximation for engagement in the learning process. However, i ...

2020

Social Learning With Partial Information Sharing

Ali H. Sayed, Virginia Bordignon

This work studies the learning abilities of agents sharing partial beliefs over social networks. The agents observe data that could have risen from one of several hypotheses and interact locally to decide whether the observations they are receiving have ri ...

IEEE2020

Temporal analysis of multimodal data to predict collaborative learning outcomes

Kshitij Sharma, Jennifer Kaitlyn Olsen

The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated ...

WILEY2020

MMKG: Multi-modal Knowledge Graphs

Alberto Garcia Duran, Hongyu Li, Ye Liu

We present Mmkg, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs. Therefore, multi-relational link prediction and entity matching communiti ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

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Service-learning

Generative adversarial training of product of policies for robust and adaptive movement primitives

Transferring interactive activities in large lectures from face-to-face to online settings

CoWriting Kazakh: Learning a New Script with a Robot

Combining the Knowledge Appropriation Model and epistemic networks to understand co-creation and adoption of learning designs using log data

Emotions in engineering education: Towards a research agenda

Training Channel Selection for Learning-based 1-bit Precoding in Massive MU-MIMO

Is There ‘ONE way’ of Learning? A Data-driven Approach

Social Learning With Partial Information Sharing

Temporal analysis of multimodal data to predict collaborative learning outcomes

MMKG: Multi-modal Knowledge Graphs

Graph Chatbot

Chattez avec Graph Search

Social Learning With Partial Information Sharing

Combining the Knowledge Appropriation Model and epistemic networks to understand co-creation and adoption of learning designs using log data

Generative adversarial training of product of policies for robust and adaptive movement primitives

Transferring interactive activities in large lectures from face-to-face to online settings

MMKG: Multi-modal Knowledge Graphs

Training Channel Selection for Learning-based 1-bit Precoding in Massive MU-MIMO

Is There ‘ONE way’ of Learning? A Data-driven Approach

Emotions in engineering education: Towards a research agenda

Temporal analysis of multimodal data to predict collaborative learning outcomes

CoWriting Kazakh: Learning a New Script with a Robot