Discover and improve learners' feelings in e-learning using fuzzy inference system

Message:
Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:

Due to the separation of teachers and students in the online teaching system and not receiving the moods of learners and applying appropriate feedback, this study seeks to design an intelligent system that can first detect learners' emotions remotely and then suggest educational scenarios to the teacher. Increases positive emotions and reduces negative emotions in learners. This research was conducted in 1998. The study population is the tenth grade mathematics students of Farzanegan 7 High School in Tehran. The students were divided into 5 groups of 15 people, each of whom was exposed to one of the situations of happiness, anger, fear, despair and sadness, and their facial information was received and recorded through a webcam. Data analysis in this study was performed by data mining method by Clementine software. By comparing the change in the range of emotions recorded before the implementation of the training scenario and then by data mining method with the help of Cummins algorithm that first clustering and then classification The results show that after the implementation of educational scenarios, changes were made in the ranges and increased the mean of positive emotions and decreased the mean of negative emotions.

Language:
Persian
Published:
Information and Communication Technology in Educational Sciences, Volume:12 Issue: 1, 2021
Pages:
109 to 130
https://www.magiran.com/p2317493  
سامانه نویسندگان
  • Author (1)
    Leily Ghomashchi
    (1399) دکتری مدیریت فناوری اطلاعات، دانشگاه آزاد اسلامی واحد تهران جنوب
    Ghomashchi، Leily
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