现代信息科技2024，Vol.8Issue(11)：130-134,140,6.DOI:10.19850/j.cnki.2096-4706.2024.11.026
基于多维连续情感识别的在线学习风险预警
Online Learning Risk Early Warning Based on Multi-dimensional Continuous Emotion Recognition
摘要
Abstract
Online teaching teachers are unable to predict academic performance in a timely manner and intervene in advance like traditional face-to-face classrooms due to a lack of emotional interaction with students.To this end,it establishes an online teaching academic risk prediction method based on sentiment analysis.Firstly,by obtaining the multidimensional emotional parameters of Valence-Arousal-Dominance(VAD),more comprehensive and detailed emotional information can be obtained.Secondly,it uses orthogonal convolutional neural networks for multi-dimensional emotion parameter recognition.Finally,multiple classic regression models are selected for academic performance and academic risk prediction experiments,and the most suitable model for predicting academic risk is ultimately selected.The experimental results show that compared with the unconstrained model,the neural network with orthogonal convolutional constraints improves the accuracy of emotion parameter prediction.The introduction of VAD emotional parameters in predicting academic achievements significantly improves the accuracy of prediction compared to using only cognitive data.The ADA-RF-EXP model performs the best in predicting final grades and warning of failure risks.关键词
面部表情识别/情感计算/智能教学系统/学业风险预警系统Key words
facial expression recognition/Affective Computing/intelligent teaching system/academic risk early warning system分类
信息技术与安全科学引用本文复制引用
霍奕..基于多维连续情感识别的在线学习风险预警[J].现代信息科技,2024,8(11):130-134,140,6.基金项目
教育部人文社会科学研究项目(23YJE880001) （23YJE880001）
