基于PSO-BP算法的弹性力学课程教学质量评估模型研究
Establishment and Analysis of PSO-BP Model for Evaluating the Teaching Quality of"Elasticity Mechanics"Course
刘小虎 1唐彬 1王雪松 1熊礼军 2纪帅杰2
作者信息
- 1. 安徽理工大学土木建筑学院,安徽 淮南 232001;安徽理工大学矿山地下工程教育部工程研究中心,安徽 淮南 232001
- 2. 合肥工业大学土木与水利工程学院,安徽 合肥 230009
- 折叠
摘要
国家人才培养的战略核心是提高教育教学质量,构建切实可行的教学质量评价体系,优选合理的质量评估方法十分必要.本文以本科弹性力学课程的教学质量评价为研究对象,建立包括教师个人素质及教学内容、方法、效果的 4 个一级指标及 19 个二级指标的教学效果评价体系,并对1 082 名本科生进行数据调研,通过对调研数据的信度及效度分析,证明了评价系统因素选择合理有效;建立基于粒子群算法优化的神经网络分析方法(PSO-BP组合算法),利用调研数据进行训练分析,得出组合算法平均评价精度高于BP神经网络算法,可以更准确有效地进行弹性力学课程教育质量的评估,以期为本科课程教学质量的考核评价提供新思路.
Abstract
Teaching quality is the core element of talent cultivation,and it is necessary to construct a practical and feasible teaching quality evaluation system and select reasonable methods.This article takes the teaching quality evaluation of the undergraduate course"Elastic Mechanics"as the research object.Firstly,a teaching effectiveness evaluation system is established,which includes 4 first-lev-el and 19 second-level indicators such as teacher personal quality,teaching content,teaching methods,and teaching effectiveness.A data survey was conducted on 1 082 undergraduates,and the reliability and validity analysis of the survey data proved that the selection of evaluation system factors is reasonable and effective;Secondly,a neural network analysis method based on particle swarm optimization(PSO-BP combination algorithm)was established,and training and analysis were conducted by using survey data.It was found that the average evaluation accuracy of the combination algorithm was higher than that of the BP neural network algorithm,which can evaluate the education quality of the"Elasticity Mechanics"course more accurately and effectively.The research provides a new approach for the assessment and evaluation of undergraduate course teaching quality.
关键词
教学质量评价体系/信度分析/效度分析/PSO-BP评价模型/案例分析Key words
teaching quality evaluation system/reliability analysis/validity analysis/PSO-BP combination algorithm model/case analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据