Pierre Dillenbourg

Computer-supported collaborative learning & work, Learning technologies, MOOCs Human-computer interaction, Educational Robotics, Eye Tracking, Tangible Interfaces, AR & VR, vocational education

Biography

A former teacher in elementary school, Pierre Dillenbourg graduated in educational science (University of Mons, Belgium). He started his research on learning technologies in 1984. In 1986, he applied machine learning for developing a self-improving teaching system. He obtained a PhD in computer science from the University of Lancaster (UK), in the domain of artificial intelligence applications for education. He has been senior scientist at the University of Geneva. He joined EPFL in 2002. He has been the director of Center for Research and Support on Learning and its Technologies, then academic director of Center for Digital Education, which implements the MOOC strategy of EPFL. He is full professor in learning technologies in the School of Computer & Communication Sciences, where he leads the CHILI Lab: "Computer-Human Interaction for Learning & Instruction ». He has been the director of the leading house DUAL-T, which develops technologies for dual vocational education systems (carpenters, florists,...). With EPFL colleagues, he launched in 2017 the Swiss EdTech Collider, an incubator with more than 90 start-ups in learning technologies. He (co-)-founded 5 start-ups, does consulting missions in the corporate world and joined the board of several companies or institutions. In 2018, he co-founded LEARN, the EPFL Center of Learning Sciences that brings together the local initiatives in educational innovation. He is a fellow of the International Society for Learning Sciences. He currently is the Associate Vice-President for Education at EPFL.

Mission

We conduct research on interactive technologies for learning and collaboration, addressing both computational and cognitive aspects.

Current work

See my lab page: http://chili.epfl.ch/

All papers

See EPFL InfoScience repository

Teaching & PhD

Teaching

Computer Science

Communication Systems

PhD Students

Burget Lucas Gérard Julien, Khodr Hala, Norman Utku, Shahmoradi Sina, Wang Chenyang, Yeo Shuqing Teresa,

Past EPFL PhD Students

Asselborn Thibault Lucien Christian , Bachour Khaled , Bonardi Stéphane , Bonnard Quentin , Chandra Shruti , Cherubini Mauro , Cuendet Sébastien , Do Lenh Hung Son , Faucon Louis Pierre , Fink Julia , Güneysu Özgür Arzu , Jacq Alexis David , Kim Kevin Gonyop , Li Nan , Lucignano Lorenzo , Mazzei Andrea , Nasir Jauwairia , Nova Nicolas , Nüssli Marc-Antoine , Raca Mirko , Riedo Fanny , Roman Flaviu , Sangin Mirweis , Seiied Alavi Hamed , Sharma Kshitij , Shirvani Boroujeni Mina , Tarniceriu Adrian Dan , Verma Himanshu , Yadollahi Elmira , Yazdanian Ramtin , Zufferey Guillaume , Özgür Ayberk ,

Courses

Digital education

This course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies on this topic: do student actually learn due to technologies?

Theoretical Foundations of Learning Sciences 1

How do people learn and how can we support learning? This is part 1 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and serves as an introduction to interpreting education as a means of designing learning environments.

Theoretical Foundations of Learning Sciences 2

How do people learn and how can we support learning? This is part 2 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and serves as an introduction to interpreting education as a means of designing learning environments.

Introduction to Methods in Learning Sciences 1

This is part 1 of a two part course that provides students with knowledge and skills in collecting, processing and analyzing educational data, including different lenses to view the nature of inquiry in the field, research designs, and an overview of quantitative and qualitative methods.

Introduction to Methods in Learning Sciences 2

This is part 2 of a two part course that provides students with knowledge and skills in collecting, processing and analyzing educational data, including different lenses to view the nature of inquiry in the field, research designs, and an overview of quantitative and qualitative methods.

Robotics practicals

The goal of this lab series is to practice the various theoretical frameworks acquired in the courses on a variety of robots, ranging from industrial robots to autonomous mobile robots, to robotic devices, all the way to interactive robots.

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