Pierre Dillenbourg

Related publications (368)

Evaluation of teachers’ orchestration tools usage in robotic classrooms

Barbara Bruno, Pierre Dillenbourg, 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 control the flow of the lesson. We designed and evaluated the impact of an orchestration tool for a series of robot-based learning activities to teach a basic concept in mathematics to children, aged 7-10. Six teachers in primary schools across Switzerland used the orchestration tool to manage the activities in six sessions involving a total of ninety-one students. We observed teachers’ usage of the orchestration tool during the sessions and interviewed them after the sessions about the usefulness of these functionalities. Our findings show that even though teachers used the tool in different ways from each other, in general, it supported them in their classroom orchestration practices, mainly to manage the activity sequence and get aware of the robot technical failures and, to a lesser degree, get aware of students’ progress for the purpose of activity transitions and enriching class discussions. We discuss the theoretical implications of these results, relating our findings to the literature on classroom orchestration tool design, especially highlighting the importance of educational level and the type of learning technology as contextual factors affecting teachers’ usage of orchestration tools. We also provide implications for designing orchestration tools, focusing on the necessity of providing different types of awareness indicators and multiple options for activity management to fulfil the variety of teachers’ orchestration needs.

2023

Fashioning the Future: Unlocking the Creative Potential of Deep Generative Models for Design Space Exploration

Richard Lee Davis, Pierre Dillenbourg, Wei Jiang, Kevin Gonyop Kim

This paper investigates the potential impact of deep generative models on the work of creative professionals, specifically focusing on fashion design. We argue that current generative modeling tools lack critical features that would make them useful creativity support tools, and introduce our own tool, generative.fashion, which was designed with theoretical principles of design space exploration in mind. Through qualitative studies with fashion design apprentices, we demonstrate how generative.fashion supported both divergent and convergent thinking, and compare it with a state-of-the-art diffusion model, Stable Diffusion. In general, the apprentices preferred generative.fashion over Stable Diffusion, citing the features explicitly designed to support ideation. We conclude that the exploration and development of novel interfaces and interaction modalities that are theoretically aligned with principles of design space exploration is crucial for unlocking the creative potential of generative AI and advancing a new era of creativity.

Association for Computing Machinery2023

A game-based approach for evaluating and customizing handwriting training using an autonomous social robot

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

Handwriting learning is a long and complex process that takes about ten years to be fully mastered. Nearly one-third of all children aged 4-12 experiences handwriting difficulties and, sadly, most of them are left to fight them on their own, due to the scarcity of tools for the detection and remediation of such difficulties. Building on state-of-the-art digital solutions for automated handwriting assessment and the training of specific handwriting-related skills, in this article we discuss requirements, rationale, and architecture of a system for handwriting training, which relies on a social robot as a mediator agent, offering personalized training and suggestions. The system is envisioned to operate autonomously and to support long-term interactions via personalization. Preliminary validation of the system in an experiment with 31 children showed its potential not only for autonomously guiding handwriting training sessions but also for its inclusion in the teachers' practice.

2022

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One of the major challenges in educational contexts is to correctly interpret the student's learning process in real-time, which is a necessary pre-requisite for timely and appropriate interventions. In educational HRI, multiple solutions have been proposed to endow robots with this key ability, typically relying on observable proxies such as in-task performance, affective behavior, engagement with the robot, etc. In this methodology paper, we propose and validate a metric for the real-time analysis of the behaviour of learners, allowing to assess whether they are engaged in meaningful learning behaviours. Specifically, building on the previously proposed concept of Productive Engagement, that inherently links learning with engagement, we hereby propose methods to quantify and compute it reliably in real-time. The training and testing of the methods is done using the open access PE-HRI-temporal dataset, that provides team level multi-modal temporal behavioral data, built from a study done with 68 students (34 teams) in a collaborative human-human educational activity mediated by a robot.

2022

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Barbara Bruno, Pierre Dillenbourg, Hala Khodr, Aditi Kothiyal

Swarming behaviors are ubiquitous in nature, and an important topic to teach and learn. In the learning sciences domain of complex systems understanding, studies have shown that novices tend to assume that centralized control and leadership should exist whenever they see complex patterns. In this paper, we present an educational framework consisting of a swarm of virtual and/or physical agents (robots) as a game-based learning environment to introduce the underlying rules of swarm behaviors.

IFAAMAS2022

Designing Online Multiplayer Games with Haptically and Virtually Linked Tangible Robots to Enhance Social Interaction in Therapy

Mehdi Akeddar, Pierre Dillenbourg, Arzu Güneysu Özgür, Hala Khodr

The social aspects of therapy and training are important for patients to avoid social isolation and must be considered when designing a platform, especially for home-based rehabilitation. We proposed an online version of the previously proposed tangible Pacman game for upper limb training with haptic-enabled tangible Cellulo robots. Our main objective is to enhance motivation and engagement through social integration and also to form a gamified multiplayer rehabilitation at a distance. Thus, allowing relatives, children, and friends to connect and play with their loved ones while also helping them with their training from anywhere in the world. As well as connecting therapists to their patients through haptically linking capabilities. This is especially relevant when there are social distancing measures which might isolate the elderly population, a majority of all rehabilitation patients.

IEEE2022

Educational Technologies for Vocational Education. Experiences as Digital Clay

Richard Lee Davis, Pierre Dillenbourg

This book summarises 15 years of research (2007-2021) on the exploitation of digital technologies for VET. In other words, our activities started the same year as the first iPhone was launched! Four research groups formed the leading house on the topic, named DUAL-T, where T stands for technologies and DUAL refers to the Swiss VET system, relying to a great extent upon the alternating of days at school and days in the workplace. This uniquely long-term research scheme has gathered more than 50 research scientists, produced 13 doctoral theses, led to the development of multiple digital learning environments and enabled dozens of empirical studies on thousands of apprentices and hundreds of teachers and company trainers. DUAL-T developed a network of stakeholders, including vocational schools and companies, but also many professional organizations and cantonal or national public entities. This book does not provide a detailed account of all these activities, which have been published elsewhere. But it proposes several answers to the question: “Which digital technologies contribute to the enhancement of vocational education?"

EPFL2022

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In a group, the collective dynamics is governed by the inter- actions between individuals, which can manifest differently depending on the available means of communication. In this paper, we compare 3 conditions of communication affordances (global chat, local chat and no chat) in an online multiplayer game and investigate their effect on team performance. An experiment involving a total of 108 participants (grouped in teams of 6 players) revealed that while the three conditions allow for the emergence of different communication systems, they yield no significant difference on the time taken to complete the task.

Springer2022

Efficacy of a ‘Misconceiving’ Robot to Improve Computational Thinking in a Collaborative Problem Solving Activity: A Pilot Study

Barbara Bruno, Alexandra Lara Chin, Pierre Dillenbourg, Utku Norman

Robot-mediated learning activities are often designed as collaborative exercises where children work together to achieve the activity objectives. Although miscommunications and misunderstandings occur frequently, humans, unlike robots, are very good at overcoming them and converging to a shared solution. With the aim of equipping a robot with these abilities and exploring its effects, in this article we investigate how can a humanoid robot collaborate with a human learner to construct a shared solution to a problem via suggesting actions and (dis)agreeing with each other. Concretely, we designed a learning activity aiming to improve the computational thinking skills of children, in which the robot makes suggestions on what to do, that may be in line with what the human thinks or not. Furthermore, the robot may suggest wrong actions that could essentially prevent them from finding a correct solution. Via a pilot study conducted remotely with 9 school children, we investigate whether the interaction results in positive learning outcomes, how does the collaboration evolve, and how these relate to each other. The results show positive learning outcomes for the participants in terms of finding better solutions, suggesting that the collaboration with the robot might have helped trigger the learning mechanisms.

2022

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We have developed a new tool that makes it possible for people with zero programming experience to intentionally and meaningfully explore the latent space of a GAN. We combine a number of methods from the literature into a single system that includes multiple functionalities: uploading and locating images in the latent space, image generation with text, visual style mixing, and intentional and intuitive latent space exploration. This tool was developed to provide a means for designers to explore the "design space" of their domains. Our goal was to create a system to support novices in gaining a more complete, expert understanding of their domain's design space by lowering the barrier of entry to using deep generative models in creative practice.

PMLR2022