A Realtime Classroom Assessment System for Analysis of Students’ Evaluation of Teaching Through a Deep Learning and Emotional Contagion Mechanism
Autor:
Lin, Kuan-Cheng
; Lin, Ya-Hsuan
; Chen, Ya-Hsuan
Fecha:
28/11/2025Palabra clave:
Revista / editorial:
UNIRCitación:
Please cite this article as: K. C. Lin, Y. H. Lin, M. Y. Chen. A Realtime Classroom Assessment System for Analysis of Students’ Evaluation of Teaching Through a Deep Learning and Emotional Contagion Mechanism, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 9, no. 5, pp. 51-59, 2025Tipo de Ítem:
articleDirección web:
https://www.ijimai.org/index.php/ijimai/article/view/859
Resumen:
Student evaluations of teacher performance are often derived from end-of-semester assessments, significantly impacting the authenticity of teaching evaluations but failing to provide real-time feedback. In addition, teachers' emotional states affect student performance, including in terms of learning motivation and classroom participation, which reflect the students' emotional state. This teacher-student emotional contagion mechanism focuses on the interaction of teacher-student emotions and can be used to observe the quality of instructional performance. Therefore, automatically detecting teacher-student emotional interaction and then providing real-time class satisfaction feedback can provide teachers with a more effective basis for adjusting classroom content. This research proposes an end-to-end classroom real-time teaching evaluation system based on automatic facial-emotion recognition, which can accurately detect and directly analyze the emotions of students and teachers in streaming frames. The system consists of two parts: First, a YOLO model based on deep learning approaches is used to automatically detect the emotional states of teachers and students during the teaching process; Then, combining the emotional contagion mechanism with the teaching evaluation scale, teaching satisfaction can be predicted using a Long Short-Term Memory (LSTM) model to output a classroom satisfaction score within a fixed period. Further analysis of the testing dataset confirms that the model has a high reliability in predicting teaching satisfaction. Research results show the proposed system can achieve an emotional recognition accuracy rate of 98.1% for teachers and 99.5% for students based on the emotion datasets. Further development could potentially provide teachers with strategies to improve classroom teaching effectiveness, better understand students' emotions and learning motivation, and improve learning outcomes.
Ficheros en el ítem
Nombre: A Realtime Classroom Assessment System for Analysis.pdf
Tamaño: 400.5Kb
Formato: application/pdf
Este ítem aparece en la(s) siguiente(s) colección(es)
Estadísticas de uso
| Año |
| 2012 |
| 2013 |
| 2014 |
| 2015 |
| 2016 |
| 2017 |
| 2018 |
| 2019 |
| 2020 |
| 2021 |
| 2022 |
| 2023 |
| 2024 |
| 2025 |
| 2026 |
| Vistas |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 7 |
| Descargas |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 1 |
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Predicting Consumer Electronics E-Commerce: Technology Acceptance Model and Logistics Service Quality
Wu, Cheng-Feng; Zhang, Kunkun; Lin, Meng-Chen; Chiou, Chei-Chang (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 09/2024)In online shopping for consumer electronics, information and physical flows are crucial determinants of consumer purchase intentions. This study examines these factors by integrating the Technology Acceptance Model with ... -
An Ensemble Classifier for Stock Trend Prediction Using Sentence-Level Chinese News Sentiment and Technical Indicators
Chen, Chun-Hao; Chen, Po-Yeh; Chun-Wei Lin, Jerry (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2022)In the financial market, predicting stock trends based on stock market news is a challenging task, and researchers are devoted to developing forecasting models. From the existing literature, the performance of the forecasting ... -
What Drives IoT-Based Smart Pet Appliances Usage Intention? The Perspective of the Unified Theory of Acceptance and Use of Technology Model
Chen, Chia-Chen; Lin, Chia-Pei (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2024)The advancement of IOT (Internet of Things) has facilitated the development of smart pet appliances, and the market for these products has growing rapidly, this study seeks to identify key factors for pet owner adoption ...





