大数据赋能本科教学质量评价:价值意蕴、现实困境与路径选择

Big Data Empowering Undergraduate Teaching Quality Evaluation:Realistic Dilemma,Value Implication and Path Choice

大数据为本科教学质量评价转型提供了新的发展机遇,大数据赋能本科教学质量评价已成为教育质量评价数字化转型关注的热点议题,展现出巨大的价值底蕴。在评价主体方面,人机协作助力多元主体评价机制优化;在评价依据方面,伴随式数据采集提供多维证据支持;在评价实施方面,立足数据治理助推教学评价数字化转型;在评价反馈方面,基于数字画像助力学生发展精准预测。目前,大数据赋能本科教学质量评价主要存在教学质量评价主体的数据素养较为缺乏、评价依据缺乏高质量数据支持与标准参照、算法黑箱制约循证教学评价的迭代优化、评价反馈合规性受困于数据伦理失范等多个现实问题。大数据赋能本科教学质量评价需要关注评价主体素养,创设基于循证理念的数据素养培育机制;加强多模态数据采集,完善基于技术规范的本科教学质量评价标准;注重数据价值释放,推进以人为本的数字化教学质量评价模式建设;聚焦数据伦理规约,构建数据向善的本科教学质量管理体系。

Big data has provided new development opportunities for the transformation of undergraduate teaching quality evaluation,and big data empowering undergraduate teaching quality evaluation has become a hot topic of concern for the digital transformation of education quality evaluation,and it shows great value implication.In terms of evaluation subjects,man-machine collaboration helps optimize the multi-agent evaluation mechanism;in terms of evaluation basis,adjoint data collection provides multidimensional evidence.In the evaluation implementation,data governance promotes digital transformation in teaching evaluation;in terms of evaluation feedback,digital portraits are used to assist students in developing accurate predictions.At present,the practical dilemmas of big data empowering undergraduate teaching quality evaluation are mainly reflected in the lack of data literacy of teaching quality evaluation subjects,the lack of high-quality data support and standard reference for evaluation basis,algorithm black box restricting iterative optimization of evidence-based teaching evaluation,and the compliance of evaluation feedback trapped by data ethics failure.Big data empowering undergraduate teaching quality evaluation needs to focus on the quality of the evaluation subject,and create a data literacy cultivation mechanism based on the evidence-based concept;strengthen multimodal data collection and improve undergraduate teaching quality evaluation standards based on technical specifications;emphasize the release of data value and promote the construction of a people-oriented digital teaching quality evaluation model;focus on data ethics regulations,and build a quality management system for undergraduate teaching with data oriented goodness.