Article: A machine learning framework for academic teaching and learning based on emotional reactions Journal: International Journal of Computational Systems Engineering (IJCSYSE) 2025 Vol.9 No.11 pp.1 - 8 Abstract: Education suffers from the most significant weakness, which is that teachers are unable to observe their students' learning and, as a consequence, are unable to determine the degree to which their pupils are concentrating on the activities they are being taught. The present model offers a solution to the aforementioned challenge. The courses can be made more difficult by utilising our algorithm's better concentration prediction, which allows us to offer more hard options. By contributing to the expansion of educational theory and practice, this work makes a contribution. The purpose of this paper is to extract facial expression characteristics by utilising a convolutional neural network and manual features from a multi-visual bag-of-words model and support vector machine (SVM) for emotion classification. This is accomplished through the utilisation of a multi-convolutional network-based facial expression identification approach. Inderscience Publishers - linking academia, business and industry through research

Title: A machine learning framework for academic teaching and learning based on emotional reactions

Authors: Yizhu Wang

Addresses: Chongqing Industry Polytechnic College, ChongQing, 401120, China

Abstract: Education suffers from the most significant weakness, which is that teachers are unable to observe their students' learning and, as a consequence, are unable to determine the degree to which their pupils are concentrating on the activities they are being taught. The present model offers a solution to the aforementioned challenge. The courses can be made more difficult by utilising our algorithm's better concentration prediction, which allows us to offer more hard options. By contributing to the expansion of educational theory and practice, this work makes a contribution. The purpose of this paper is to extract facial expression characteristics by utilising a convolutional neural network and manual features from a multi-visual bag-of-words model and support vector machine (SVM) for emotion classification. This is accomplished through the utilisation of a multi-convolutional network-based facial expression identification approach.

Keywords: artificial intelligence algorithms; teaching and learning; expression recognition; feature extraction recognition; convolutional neural network; CNN; loss and accuracy.

DOI: 10.1504/IJCSYSE.2025.146878

International Journal of Computational Systems Engineering, 2025 Vol.9 No.11, pp.1 - 8

Received: 08 Dec 2023
Accepted: 17 Jan 2024
Published online: 24 Jun 2025 *

Title: A machine learning framework for academic teaching and learning based on emotional reactions

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