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Using Agents for Training Students Collaborative Skills
A multi-agent model developed to recognize conflicts in a group dynamics, and personal training skills of collaboration expressed by the students, and an appropriate training strategy for each individual is presented.
The knowledge-based simulation
- Elena B. Durán, R. Costaguta
- Computer ScienceProceedings 31st Annual Simulation Symposium
- 5 April 1998
A definition of the possible contributions that the expert systems can give to the different life cycle stages of the discrete event simulation and consequently constructing production rules to be applied in model development, parameter estimation and results analysis and interpretation is proposed.
Algorithms and Machine Learning Techniques in Collaborative Group Formation
- R. Costaguta
- 25 October 2015
This paper surveys the most relevant researches carried out in this field to date and describes the applied criterion to form learning groups and the way in which the grouping criterion is applied.
Genetic algorithm for automatic group formation considering student's learning styles
- Germán Lescano, R. Costaguta, A. Amandi
- Computer Science8th Euro American Conference on Telematics and…
- 1 April 2016
This paper proposes a genetic algorithm for automatic generation of groups considering learning styles of your members, using historical data about performance of groups and creating association rules which are used in the fitness function.
COLLAB: Conflicts and Sentiments in chats
An application to support the communication of collaborative groups when the members work together to make collaborative activities by generating data that will be employed to build and validate automatic classifiers to recognize conflicts in synchronous dialogues through the analysis of sentiments exchanged in the interactions.
Training collaboration skills to improve group dynamics
This work presents a multiagent model applied to CSCL environment, which aims both at recognizing conflicts occurring in group dynamics and at providing personalized training of collaborative skills demonstrated by group members.
Analysis of a GPU implementation of Viola-Jones’ Algorithm for Features Selection
The aim was to reduce the time needed during training phase when using one computer with a cheap graphical processing unit (GPU) and showed that combining C language, CUDA, etc., it is possible to reach acceptable times for training phase.
An assistant agent for group formation in CSCL based on student learning styles
A new approach for automatically creating student groups in CSCL systems by considering their individual learning styles is proposed, and the assistant agent will be implemented in an existing CSCL tool, and its performance will be validated with real students.
A Technique for Conflict Detection in Collaborative Learning Environment by Using Text Sentiment
A technique to recognize conflicts in a group and the members involved in them by focusing in the socio-emotional interactions is proposed, able to detect conflicts automatically, reducing the human effort required to detect these conflicts by other means.
A Multi-agent Model That Promotes Team-Role Balance in Computer Supported Collaborative Learning
A multi-agent model is presented that monitors students' participation in a group, recognizes their team roles as they work collaboratively, automatically builds their profiles, diagnoses the state of the collaboration, and proposes corrective actions when the group behavior is far from this ideal.