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# Prototype for the planning and vizualisation of training group

Laurie Acensio

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## To cite this version:

Laurie Acensio. Prototype for the planning and vizualisation of training group. CSCL Computer-Supported Collaborative Learning, Jun 2019, Lyon, France. 2019. [hal-05314779](https://hal.science/hal-05314779v1)

HAL Id: hal-05314779

https://hal.science/hal-05314779v1

Submitted on 14 Oct 2025

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# Prototype for the planning and vizualisation of training group

Lille University-Science and Technology

CRISTAL Laboratory-NOCE : New Tools for Cooperation and Education
(Research Center in Computer Science, Signal and Automatic Control of Lille)

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French Corner
CSCL 2019

Computer-Supported Collaborative Learning

Laurie Acensio-PhD
Laurie.acensio@lexiane.fr

## Prototype Application

### Context

- Adult training/Collaboration relationship

- Planning and Decision-making

### Objective

- Semi-automatic group composition based on multiple decision criteria

### Methods

- Definition of the decision criteria by a statistical and network analysis

- Optimization *via* Genetic Algorithm

- Graph visualization *via* dashboard

## Optimizing the composition of the training group

Derived from the theory of social constructivism (Vygotsky, L.), peer interactions and collaboration among learners are essential components of the training process. In the context of adult-learner training, the composition of face-to-face training groups involves taking into account multiple and interdependent criterias (social, cognitive, and organizational). The generation of results is based on an optimization algorithm and more precisely Genetic Algorithm (Holland, J.) whose fitness function is parameterized by a statistical analysis. The exploration of results is facilitated with the social network visualization based on graph.

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### Step 1: Learner Profile

User profile data: socio-professional position, training interest, seniority, activity sector, history of training...

### Step 3: Optimization *via* Genetic Algorithm

Definition of decision criteria and fitness function parameterization by statistical analysis

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### Step 2: Modeling and indexing based on graph database

Structuring database NoSQL that focuses on socio-professionnal relationships between Named-Entities (organization, person)

### Step 4: Dashboard

Relevance score of the training group
Visualization of results by graph

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Exemple :

- Red node represent the trainer and intermediary of two training group

- Arrow: directed relationship

- Solid line: intra-organizational relationship

- Dotted line: inter-organizational relationship

## Bibliography

- Vygotsky, L. S. (1978). *Mind in society: The development of higher psychological processes* (Vol. 86). Harvard university press.

- Holland, J. H. (1975). *Adaptation in Natural and Artificial Systems*. University of Michigan Press.

- Lifelong Training-(European Commission, 2002)

- Private/Public partnership : Lexiane Formation (Vocational Training Organization)

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