Personalized Inductive Learning Based on Emotion Recognition with Support from Artificial Intelligence “MENTALUD”

EasyChair Preprint 13223

Abstract

MENTALUD addressed the need to improve learning in basic education, specifically aimed at children ages 6 to 12, in an educational system that follows obsolete models of the Industrial Revolution. The main purpose of MENTALUD was to modernize the educational process by implementing artificial intelligence to provide better personalized and relevant learning for each student, taking into account their abilities and emotions. MENTALUD used psychophysiological recognition techniques through a facial mesh to capture and measure relevant gestures during learning. This data is processed to identify the student's feelings and provide personalized educational intervention. The results highlight MENTALUD's ability to timely detect and address factors that negatively affect reading, critical and visual comprehension, among other fundamental skills, thus improving the learning process. It is concluded that MENTALUD represents a significant advance in the new ways of integrating with the support of artificial intelligence in the educational field, offering new possibilities of obtaining personalized and effective learning in the 21st century. The implications of MINDSET include better teaching and learning in a personalized way and consideration of students' emotions, which could have a significant impact on the virtue of the education system.

Keyphrases: Artificial Intelligence, MENTALUD, basic education, emotional understanding, personalized learning, psychophysiological recognition

@booklet{EasyChair:13223,
  author    = {Armando Escobar Benitez and Rubi Marlene Lopez Perez},
  title     = {Personalized Inductive Learning Based on Emotion Recognition with Support from Artificial Intelligence “MENTALUD”},
  howpublished = {EasyChair Preprint 13223},
  year      = {EasyChair, 2024}}