@inproceedings{a13317c723f54bac8f98da4989e57cba,
title = "Evaluation Method of Teaching Styles Based on Multi-modal Fusion",
abstract = "Teaching style refers to the teaching performance of the teacher's personal characteristics, teaching skills and teaching methods formed in the long-term teaching process. It plays an important role in helping students achieve academic success. With the continuous reform of the teaching system, more and more courses are taught in the form of videos. In this paper, we established a teaching style evaluation system and classification model based on teachers' teaching behavior based on facial expressions, voices and postures in the teaching process. We adopted principal component analysis and autoencoder feature selection methods, and designed based on The multi-modal step-by-step fusion algorithm of deep neural network classifies teaching styles.",
keywords = "Deep neural network, Feature selection, Multi-modal fusion, Teaching styles",
author = "Wen Tang and Chongwen Wang and Yi Zhang",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 7th International Conference on Communication and Information Processing, ICCIP 2021 ; Conference date: 16-12-2021 Through 18-12-2021",
year = "2021",
month = dec,
day = "16",
doi = "10.1145/3507971.3507974",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "9--15",
booktitle = "2021 7th International Conference on Communication and Information Processing, ICCIP 2021",
}