大数据驱动下汉语言文学专业教学质量评价与优化研究
Study on Evaluation and Optimization of Chinese Language and Literature Teaching Quality Driven by Big Data
杨思琪1
作者信息
摘要
为研究大数据驱动下汉语言文学专业教学质量评价与优化问题,编辑并发放问卷进行调研,借助SPSS 26.0 软件分析所得数据发现,汉语言文学专业整体教学质量较高,其课程设计、教学体验、学科融合、教学效果 4 个维度显著相关,其中权重最大的为课程设计(34.323%),最小的为教学体验(19.467%).性别差异对教学评价具有一定的影响,男生与女生在教学体验、学科融合、教学效果与总分层面存在差异,女生的表现优于男生.故加强课程设计的专业性与实用性,关注性别差异,实施差异化教学策略,促进跨学科融合,实时调整教学策略等,能更好地提升汉语言文学专业的课程教学效果.
Abstract
In order to study the evaluation and optimization of Chinese language and literature teaching quality driven by big data,the study compiles and distributes questionnaires for investigation,and analyzes the data with SPSS 26.0 software.The overall teaching quality of Chinese language and literature major is high,and there is significant correlation between the four dimensions:course design,teaching experience,discipline integration and teaching effect,among which the weight of course design is the largest(34.323%),and that of teaching experience is the smallest(19.467%).There is certain influence of gender difference on teaching evaluation.There are differences between boys and girls in teaching experience,subject integration,teaching effect and total score.The performance of girls is better than that of boys.Therefore,it suggested to strengthen the professionalism and practicability of course design,pay attention to gender differences,implement differentiated teaching strategies,promote interdisciplinary integration,and adjust teaching strategies in real time,etc.,so as to better improve the teaching effect of Chinese language and literature majors.
关键词
教学质量评价/汉语言文学专业/课程设计/教学融合/性别差异Key words
Teaching quality evaluation/Chinese language major/Course design/Teaching integration/Gender difference引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据