Analysis of Intrinsic Motivation during a Problem-Solving activity
Résumé
This literature review is part of the work carried out within the AIDE (Artificial Intelligence Devoted to Education) exploratory action. The team at the origin of this work allows researchers from digital sciences (computer science and applied mathematics), cognitive neurosciences and education sciences to join forces within this exploratory action to try to understand, within a specific framework, how learners learn.
How do we learn? This is one of the questions that the AIDE exploratory action tries to answer, in a specific paradigm. But what is learning? How can studying the functioning of the brain have an impact on education? What about digital technologies? To what extent does it intervene in the field of neuroscience and is it at the heart of educational sciences? At this stage, contextual and conceptual clarification is necessary.
This report proposes some answers from the existing literature.
Mots clés
learning science
cognition
intrinsic motivation
2 Educational sciences 1.1.3 Neuroeducation 1.2 Cognition: generalities 1.2.1 Cognition and learning 1.2.2 Knowledge and belief 1.2.3 Cognizance and Knowledge 1.2.4 Cognizance
competence
and experience 1.2.5 Cognizance and information 1.2.6 Knowledge and cognition: conclusion 1.3 Cognition: mental functions 1.3.1 Perception 1.3.2 Attention 1.3.3 Memories 1.3.4 Reasoning 1.3.5 Executive functions 1.3.6 Language and motor skills 1.3.7 Emotions 1.3.8 Mental functions: conclusion 1.4 Metacognition 1.4.1 General information 1.4.2 How metacognition works 1.4.3 Metacognition: conclusion 1.5 De la cognition à l'apprentissage humain: conclusion 2 The role of motivation in learning 2.1 Learning process 2.1.1 Theories of human learning 2.1.2 Acquisition methods 2.1.3 Problem resolution 2.2 Motivation 2.2.1 General Information 2.2.2 Extrinsic motivation 2.2.3 Intrinsic motivation 2.3 The role of motivation in human learning: conclusion 3 Modeling intrinsic motivation in learning 3.1 The involvement of curiosity in learning 3.2 Computational models of curiosity 3.2.1 Intelligent Tutoring Systems
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