摘要
基于大数据应用的课程教学质量评价是引导混合式教学中教、学、管理不同角色持续改进的关键。采用对照实验法,对23个专业的51门课程分别开展两种评价:"专家主体评价"和"基于大数据感知的评价",探究基于大数据应用的课程教学质量评价模型、评价方法及评价效果。研究表明,"基于大数据感知的评价"能有效解决现行课程教学质量评价体系普遍存在的评价结果准确性、教学感知有效性、反馈改进及时性不足问题。研究启示,建立客观、综合、伴随式的课程教学质量评价体系,应注重:(1)基于可靠性原则建立评价模型;(2)基于有效性原则探索大数据感知;(3)基于及时促进原则完善过程反馈改进;(4)应用大数据技术迭代优化综合评价。
The Evaluation of course teaching quality based on big data is the key to guide the continuous improvement of different roles in teaching, learning and management in blended learning. This paper evaluated 51 courses of 23 majors in two ways respectively:“expert subject evaluation”and“evaluation based on big data perception”, by using the controlled experiment method to explore the evaluation model, method and effect of course teaching quality based on big data application. The research shows that“perception evaluation based on big data”can effectively solve the problems commonly existing in the current course teaching quality evaluation system, such as the accuracy of evaluation results, the effectiveness of teaching perception, and the lack of timeliness of feedback and improvement. In order to establish an objective, comprehensive and concomitant course teaching quality evaluation system, we should pay attention to:(1)The establishment of evaluation model based on the reliability principle;(2)The exploration of big data perception based on the validity principle;(3) The improvement of the process feedback and process improvement based on the prompt promotion principle;(4) The application of big data technology to iterative optimization comprehensive evaluation.
作者
张阳
郭权
ZHANG Yang;GUO Quan(Dalian Neusoft University of Information,Dalian 116023,China)
出处
《辽宁大学学报（哲学社会科学版）》
2021年第3期177-184,共8页
Journal of Liaoning University(Philosophy and Social Sciences Edition)
基金
辽宁省教育科学“十三五”规划课题“结果导向的实践类课程评估模式研究”(JG18DB031)。
关键词
大数据感知
课程教学质量评价
混合式教学
big data perception
course teaching quality evaluation
blended learning
