Harnessing collective intelligence for the future of learning – a co-constructed research and development agenda
Dusan Misevic
(1)
,
Ignacio Atal
(1)
,
Denis Bedard
(2)
,
Eric Cherel
(1)
,
José Escamilla
(3)
,
Linda Evans
(4)
,
Valerie Hannon
,
Caroline Huron
(1)
,
Olivier Irrmann
(5)
,
Rene Kizilcec
(6)
,
Emmanuel Lazega
(7)
,
Kerri Lemoie
,
Ariel Lindner
(1)
,
Mariana Macedo
(8)
,
Gaell Mainguy
(1)
,
Richard Mann
(9)
,
Camille Masselot
(1, 10)
,
Pietro Michelucci
,
Iryna Nikolayeva
(1)
,
Amy Ogan
(11)
,
Mar Pérez-Sanagustín
,
Niccolo Pescetelli
,
Sasha Poquet
,
Janet Rafner
,
Dominic Regester
,
Marc Santolini
(1)
,
Jean-Marc Sevin
(1, 12)
,
Dafna Shahaf
,
Jacob Sherson
,
Jacksón Smith
,
Mattias Söllner
,
Françoise Soulié
,
François Taddei
(1)
,
Liubov Tupikina
(1, 13)
,
Sander van der Leeuw
1
LPI -
Learning Planet Institute [Paris]
2 UdeS - Université de Sherbrooke
3 ITESM - Tecnológico de Monterrey = Monterrey Institute of Technology
4 University of Manchester [Manchester]
5 UCL - Université catholique de Lille
6 CU - Cornell University [Ithaca]
7 CSO - Centre de sociologie des organisations (Sciences Po, CNRS)
8 ANITI - Artificial and Natural Intelligence Toulouse Institute
9 University of Leeds
10 UPCité - Université Paris Cité
11 CMU - Carnegie Mellon University [Pittsburgh]
12 Learning Transitions - Learning Planet Institute (LPI) - 8bis Rue Charles V - 75004 Paris - RNSR: 202324521H
13 Nokia Bell Labs [Paris-Saclay]
2 UdeS - Université de Sherbrooke
3 ITESM - Tecnológico de Monterrey = Monterrey Institute of Technology
4 University of Manchester [Manchester]
5 UCL - Université catholique de Lille
6 CU - Cornell University [Ithaca]
7 CSO - Centre de sociologie des organisations (Sciences Po, CNRS)
8 ANITI - Artificial and Natural Intelligence Toulouse Institute
9 University of Leeds
10 UPCité - Université Paris Cité
11 CMU - Carnegie Mellon University [Pittsburgh]
12 Learning Transitions - Learning Planet Institute (LPI) - 8bis Rue Charles V - 75004 Paris - RNSR: 202324521H
13 Nokia Bell Labs [Paris-Saclay]
Valerie Hannon
- Fonction : Auteur
Kerri Lemoie
- Fonction : Auteur
Pietro Michelucci
- Fonction : Auteur
Mar Pérez-Sanagustín
- Fonction : Auteur
Niccolo Pescetelli
- Fonction : Auteur
Sasha Poquet
- Fonction : Auteur
Janet Rafner
- Fonction : Auteur
Dominic Regester
- Fonction : Auteur
Dafna Shahaf
- Fonction : Auteur
Jacob Sherson
- Fonction : Auteur
Jacksón Smith
- Fonction : Auteur
Mattias Söllner
- Fonction : Auteur
Françoise Soulié
- Fonction : Auteur
Sander van der Leeuw
- Fonction : Auteur
Résumé
Learning, defined as the process of constructing meaning and developing competencies to act on it, is instrumental in helping individuals, communities, and organizations tackle challenges. When these challenges increase in complexity and require domain knowledge from diverse areas of expertise, it becomes difficult for single individuals to address them. In this context, collective intelligence, a capacity of groups of people to act together and solve problems using their collective knowledge, becomes of great importance. Technologies are instrumental both to support and understand learning and collective intelligence, hence the need for innovations in the area of technologies that can support user needs to learn and tackle collective challenges. Use-inspired research is a fitting paradigm that spans applied solutions and scientific explanations of the processes of learning and collective intelligence, and that can improve the technologies that may support them. Although some conceptual and theoretical work explaining and linking learning with collective intelligence is emerging, technological infrastructures as well as methodologies that employ and evidence that support them are nascent. We convened a group of experts to create a middleground and engage with the priorities for use-inspired research. Here we detail directions and methods they put forward as most promising for advancing a scientific agenda around learning and collective intelligence.