A learning scientist approach to modeling human cognition in individual and collaborative problem solving tasks. 12 février 2021. Mini-cours. NeuroMod Institute. Université Côte d'Azur.

1. A learning scientist approach to modeling human cognition
in individual and collaborative problem solving tasks
@margaridaromero
Margarida.Romero@unice.fr
Dir. Laboratoire d’Innovation et Numérique pour l’Education (LINE)
12 février 2021. Mini-cours

2. What is your current mood ?
1
2
4
3
5 6 7
8 other
moods...

3. Some references in relation to this workshop
Romero, M., Alexandre, F., Roux, L., Giraudon, G., & Viéville, T. (2020). From computational neuroscience to computational learning science : Modeling the brain of the learner and the
context of the learning activity. SophIA-summit 2020. https://hal.inria.fr/hal-03018617
Romero, M., Viéville, T. & Heiser, L. (accepted). Analyse d'activités d'apprentissage médiatisées en robotique pédagogique. Dans Alberto, B., Thievenaz, J. (in press). Traité de méthodologie
de la recherche en Sciences de l’Éducation et de la Formation.
https://www.researchgate.net/publication/344151929_Analyse_d'activites_d'apprentissage_mediatisees_en_robotique_pedagogique
Leroy, A., Romero, M., & Cassone, L. (2021). Interactivity and materiality matter in creativity: educational robotics for the assessment of divergent thinking. Interactive Learning Environments,
1-12.
Kalmpourtzis, G., & Romero, M. (2020, December). Artifactual Affordances in Playful Robotics. In International Conference on Games and Learning Alliance (pp. 316-325). Springer, Cham.
Roux, L., Romero, M., Alexandre, F., Viéville, T., & Mercier, C. (2020). Développement d’une ontologie pour l’analyse d’observables de l’apprenant dans le contexte d’une tâche avec des
robots modulaire. Inria. 2020, 48. https://hal.archives-ouvertes.fr/LINE/hal-03013685v1
Romero, M., & Chevré, A. M. (2020). ANR-18-CE38-0001-OpenAccess-20201201-Rapport Intermédiaire.
https://www.researchgate.net/publication/346629855_ANR-18-CE38-0001-OpenAccess-20201201-Rapport_Intermediaire
Cassone, L., Romero, M., & Basiri, S. (2020). Group processes and creative components in a problem-solving task with modular robotics, Journal of Computing in Education.
https://doi.org/10.1007/s40692-020-00172-7
Romero, M. (2019, July). Analyzing Cognitive Flexibility in Older Adults Through Playing with Robotic Cubes. In International Conference on Human-Computer Interaction (pp. 545-553).
Springer, Cham.
Romero, M., DeBlois, L., & Pavel, A. (2018). Créacube, comparaison de la résolution créative de problèmes, chez des enfants et des adultes, par le biais d’une tâche de robotique modulaire.
MathémaTICE (61).
Romero, M., David, D., & Lille, B. (2018, December). CreaCube, a Playful Activity with Modular Robotics. In International Conference on Games and Learning Alliance (pp. 397-405).
Springer, Cham.
Romero, M., & Loos, E. F. (2018). Playing with robotic cubes: age matters. Intergenerationality in a digital world: Proposals of activities. Publisher: Edições Universitárias Lusófonas.
Romero, M. (2017). CreaCube, analyse de la résolution créative de problèmes par le biais d’une tâche de robotique modulaire. Journées Nationales de la Recherche en Robotique, JNRR
2017. https://jnrr2017.sciencesconf.org/167023/document
ANR CreaMaker website
https://creamaker.wordpress.com/

4. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

5. European PhD (cotutelle) UAB-UT2
(Extraordinary Thesis Award at UAB)
Multimedia
Project Management
Graduate studies
Master in Computer Sciences
(Knowledge engineering)
Master in Psychology of
Education
Master studies
2009-2013 Associate professor on psychology
of education
2013-2017 Associate professor on educational
technology (tenured in 2015)
Since 2017 Full professor on learning sciences
Academic career
Laboratoire d’Innovation et Numérique pour
l’Education director

6. “Epistemological pluralism recognizes that, in any given
research context, there may be several valuable ways of knowing, and that accommodating this
plurality can lead to more successful integrated study” (Miller et al. 2008)
“methodological tribalism” vs
“pluralistic coexistence” as a way to foster dialogue and '”innovative
methodological cross-fertilization'” in the spirit of “openness” and “constructive criticism'” (Lamont
& Swidler 2014)
Lamont, M., & Swidler, A. (2014). Methodological pluralism and the possibilities and limits of interviewing. Qualitative Sociology, 37(2), 153-171.
Miller, T. R., Baird, T. D., Littlefield, C. M., Kofinas, G., Chapin III, F. S., & Redman, C. L. (2008). Epistemological pluralism: reorganizing interdisciplinary
research. Ecology and Society, 13(2).

7. Romero, M., & Belhassein, D. (2019). Interdisciplinarité et usages co-créatifs du numérique en éducation. Dans Darbellay, F. (Ed.). L'interdisciplinarité à
l'école: succès, résistance, diversité. Alphil.

8. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

9. 1. Prior knowledge and expectations
https://s.42l.fr/NeuroModT1

10. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

11. How humans learn ?

12. Learning sciences
How we learn ?

13. Learning sciences
How we learn ? Learning process as contextual, multilevel (intrapsychological,
interpsychological) in interaction with agents and artefacts

14. What we learn ?

15. Source : http://andre.tricot.pagesperso-orange.fr/2_ICLTC2019_Reasoning_more_efficiently_with_primary_knowledge_v2.pdf

16. Tricot (2015)

17. In primary
education, what are
the most important
aspects to learn in
mathematics ?
What we can do for
improving
mathematics
education ?
Performances en mathématiques, classe de CM1. Etude TIMSS 2019. (TIMSS / DEPP)

18. Singapore’s Mathematics Framework

19. Boaler, J. (2015). Mathematical mindsets: Unleashing students' potential through creative math, inspiring messages and innovative teaching. John Wiley
& Sons.

21. Efklides (2011)

23. How we solve problems ?

25. Team activity : creation of a problem solving model
https://docs.google.com/presentation/d/1RVaYtYNxkHjubOwEchqyadLNAaDF6zT9C
As9iBwOXwA/edit?usp=sharing

27. Problem solver (Newell & Simon 1972, p. 289)

29. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

30. Learning activity as a unit of analysis
For Conole and Fill (2005), the notion of a learning activity (LA) is composed of three elements:
● The context of the activity: e.g. subject, level of difficulty, intended learning outcomes and the
environment within which the activity takes place.
● The learning and teaching approaches: including theories and models.
● The learning tasks: This includes type of task, techniques used, associated tools and
resources, interaction and roles of those involved and learner assessment.

32. Diversity of learning activities

33. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

34. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity
6. Research program

35. Creativity assessment
through the CreaCube task

36. Problem
“Build a vehicle moving from a red point to a black point”
CreACubE @ aIde How we solve problems with technology ?
Material to solve the problem
Solution ?

37. Problem
“Build a vehicle moving from a red point to a black point”
CreACubE @ aIde How we solve problems with technology ?
Material to solve the problem
Solution ?
Norman (1986) designates as the gulf of execution, the distance between the
user's goals and the means of achieving them through the system.
What we can do ?
Explore the material
Be creative (association). Use the material in an
alternative way (AUT, Guilfort, 1967)
Learn about the material
features and exploit it
Evaluate solutions before
recombining in order to
inhibit unsuccessful ideas

38. CreACubE @ aIde How we solve problems with technology ?
Information inputs
Instructions
State of the system
(unitary and system
level)
Mental model of
the situation
Mental model of
the solution
Behaviors (grasp,
turn, explore…)
Goals :
performance
play/explore

39. On divergent thinking, subjects generate new ideas
(configurations of the cubes)

40. Selecting/inhibiting (convergent thinking).

41. Having new ideas is not enough; creativity as a means of
finding different useful solutions (divergent + convergent +
critical thinking) for a given problem-situation.
F07
F06 F08
F01
F02
F11

42. Plan
1. Prior knowledge and expectancies
2. How learning happens ? How we solve problems ?
3. Analysis of activities
4. Play !
5. Analysis of the activity : modeling the activity
6. Research program

43. Learning
task
Analysis of the
activity
Task
model
Ontology
and data
model
Learner
model
Learning
activity
Traces of interaction
(learning analytics) generated
in the technological
environments
Data from coding schemas
(video, observations, etc.)
Memory
Goals
Technological environment
Stimulii
Affordances
Actions

44. CreACubE @ aIde How we solve problems with technology ?
Which observables (and grammar) for analysing exploratory and exploitation analysis ?

45. Objects-to-think-with
Creative exploration as a means of analyzing the problem
situation and the objects to be engaged in the solution.

47. Creative problem solving with interactive robotic cubes
CreACubE @ aIde How we solve problems with technology ?
Exploration
Explotation
At the unitary level (cubes)
At the system level (figure)

48. Creative problem solving with interactive robotic cubes
CreACubE @ aIde How we solve problems with technology ?

49. Creative problem solving with interactive robotic cubes
CreACubE @ aIde How we solve problems with technology ?

50. Creative problem solving with interactive robotic cubes
CreACubE @ aIde How we solve problems with technology ?

51. CreACubE @ aIde How we solve problems with technology ?
● Exploration (at the unitary level, at the figure level) and exploitation (testing specific features
at the unitary level, testing certain figures) should be combined.
● Which combination of exploratory and exploitation behavior happens in the
problem solving task ?
● Which states can be defined within the task ?
● Which observables (and grammar) for analysing exploratory and exploitation
analysis ?

52. Aide : Artificial Intelligence Devoted to Education (AIDE)

53. Older adults EHPAD
Action exploratoire Artificial Intelligence Devoted to
Education (AIDE)
Lifelong learning ⇒ ANR #CreaMaker 7 to 107 years
Critical thinking
Transformative agency
Computational thinking
Learning sciences research lab INRIA project-team in computational neurosciences
Adults
Children

54. A learning scientist approach to modeling human cognition
in individual and collaborative problem solving tasks
@margaridaromero
Margarida.Romero@unice.fr
Dir. Laboratoire d’Innovation et Numérique pour l’Education (LINE)
12 février 2021. Mini-cours

55. Annexes

56. Assessment of creativity
‘Ideation’ VS ‘creation’

58. ● The creativity results of AUT and CréaCube do not display
the same creativity results

60. Artificial creativity ?

61. AIDE tasks
Learning in specific tasks
CreACubE @ aIde How we solve problems with technology ?
Problem solving tasks engaging technological knowledge
(computational thinking)

62. CreaCube
Component 1: Organize & model the situation
Component 2: Identify problems
Component 5: Devise a solution
Component 6: Adopt an iterative process
Component 3: Hone formal systems (e.g. coding, maths, logic)
Component 4: Integrate physical systems
COMPO1
Understanding the
problem-situation
Concept of autonomous
vehicle
COMPO2
Imagining the use of the
cubes for meeting the task
objectives
COMPO3
Importance of the order of a sequence (system behaviour
defined by the order of the cubes)
COMPO4
Magnets
Sensors
Actuatuors
Electric circuit
Cubes assembled as a system
COMPO5
Creating a solution by
assembling by inverting the
distance sensor signal
COMPO6
Solution anlysis for improvement
through a new figure

63. Model of the task
(ontologie)
Modèles
neurosciences
computationnelles
(Mnémosyne)
CreACubE @ aIde How we solve problems with technology ?