Mood Inference Machine: Framework to Infer Affective Phenomena in ROODA Virtual Learning Environment

Authors

  • Magalí Teresinha Longhi Federal University of Rio Grande do Sul
  • Patricia Alejandra Behar Federal University of Rio Grande do Sul
  • Magda Bercht Federal University of Rio Grande do Sul

DOI:

https://doi.org/10.3991/ijac.v5i1.1740

Keywords:

Affective modeling, Bayesian networks, virtual learning environments

Abstract


This article presents a mechanism to infer mood states, aiming to provide virtual learning environments (VLEs) with a tool able to recognize the studentâ??s motivation. The inference model has as its parameters personality traits, motivational factors obtained through behavioral standards and the affective subjectivity identified in texts made available in the communication functionalities of the VLE. In the inference machine, such variables are treated under probability reasoning, more precisely by Bayesian networks.

Author Biographies

Magalí Teresinha Longhi, Federal University of Rio Grande do Sul

Post Graduation Program in Computer Science applied to Education Program

Patricia Alejandra Behar, Federal University of Rio Grande do Sul

Post Graduation Program in Computer Science applied to Education Program

Magda Bercht, Federal University of Rio Grande do Sul

Post Graduation Program in Computer Science applied to Education Program

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Published

2012-02-28

How to Cite

Longhi, M. T., Behar, P. A., & Bercht, M. (2012). Mood Inference Machine: Framework to Infer Affective Phenomena in ROODA Virtual Learning Environment. International Journal of Advanced Corporate Learning (iJAC), 5(1), pp. 14–20. https://doi.org/10.3991/ijac.v5i1.1740

Issue

Section

Papers