Journal Article

A Multimodal Teaching Quality Evaluation for Hybrid Education Based on Stepwise Regression Analysis

Ma, Lei, Yang, Hongxue, Yang, Jianxing

2023

Overview

To solve the problems of low evaluation accuracy and satisfaction in the complex evaluation index differences of hybrid education models in schools, this paper designs a multimodal teaching quality evaluation for hybrid education based on stepwise regression analysis. The proposed method introduces a stepwise regression analysis algorithm by constructing multimodal reliability fusion, and gradually analyzes the evaluation indicators of hybrid teaching modes based on a multiple linear regression model. By combining sensitivity and specificity, ensure the accuracy of evaluation methods and achieve teaching quality evaluation of hybrid education models. The experimental results show that for the hybrid teaching mode, the satisfaction level of the quality evaluation method using multimodal teaching is above 94.7 points, the evaluation efficiency reaches 1.1s, the evaluation accuracy reaches 97.0%, and the sensitivity and specificity reached above 0.94, which has a superior teaching quality evaluation effect. The proposed method effectively improves the accuracy of teaching quality evaluation in the hybrid joint education model, and has feasibility and effectiveness, which can provide reliable reference for schools.

• Publisher: Springer Nature B.V
• Subject: Accuracy / Algorithms / Education / Quality assessment / Regression analysis / Regression models