摘要
在线精品课程作为MOOC中的高质量教育资源,有效促进了教育公平和均衡发展.但在保持快速增长的态势时,仍存在质量参差不齐的困境.为促进教师深度反思,支持教学问题的诊断与改进,提升课程质量,构建在线精品课程评论情感分类与主题挖掘研究模型.首先,采用网络爬虫技术采集MOOC平台中25门"教育技术学"专业在线精品课程评论数据,并进行数据预处理和情感分类;其次,对负性课程评论进行词云分析、社会网络分析和主题挖掘.结果表明:教师教学能力、学习资源质量、课程内容设计、互动和反馈机制、课程考核评价是导致学生差评、影响课程学习体验和学习质量的主要因素.据此,提出促进在线教育中教师教学能力专业化提升、开发优质在线精品课程学习资源、打造实用生动的在线精品课程内容、优化互动和反馈机制、优化在线精品课程考核评价等课程优化建议.
Abstract
Online high-quality courses,as valuable educational resources in MOOCs,have effectively promoted educational equity and balanced development.However,despite the rapid growth,there still exist challenges in maintaining consistent quality.To facilitate deep reflection among instructors,support diagnosis and improvement of teaching problems,and enhance course quality,this study proposes a research model for sentiment classification and topic mining of online high-quality course comments.Firstly,comments data from 25"Educational Technology"professional online high-quality courses on the MOOC platform are collected using web crawlers,followed by data preprocessing and sentiment classification.Then,negative course comments are analyzed through word cloud analysis,social network analysis,and topic mining.The results indicate that teaching competence,learning resource quality,course content design,interaction and feedback mechanisms,and course assessment and evaluation are the main factors contributing to negative student feedback,influencing course learning experiences and quality.Finally,based on the research findings,suggestions for course optimization are proposed,providing valuable insights and decision-making basis for educational reform and practice in the field of educational technology.This study has important guiding implications for improving and enhancing the quality of MOOC courses.
基金项目
2022年湖北省教育厅哲学社会科学研究项目(22Y105)
2023年湖北师范大学研究生创新科研项目(2023Y042)
NETL
NSTL
维普
万方数据