数字化转型背景下综合素质评价数据优化:现实问题、框架建设与实践路径  

Data Optimization of Comprehensive Quality Assessment in the Context of Digital Transformation:Challenges,Framework Construction and Practice Approaches

作　　者：李鲁越 柴唤友 郭利明 郑勤华[1] LI Luyue;CHAI Huanyou;GUO Liming;ZHENG Qinhua(Beijing Normal University,Beijing 100875,China;Central China Normal University,Wuhan 430079,China;Wenzhou University,Wenzhou 325035,China)

机构地区：[1]北京师范大学,北京100875 [2]华中师范大学,武汉430079 [3]温州大学,浙江温州325035

出　　处：《中国考试》2024年第12期49-55,93,共8页journal of China Examinations

基　　金：2021年度科技部“社会治理与智慧社会科技支撑”重点专项“大规模学生跨学段成长跟踪研究”(2021YFC3340800)。

摘　　要：当前,综合素质评价尚存在数据真实性存疑、准确性不足等现实问题,以人工智能、大数据为代表的新一代信息技术为破解这些问题提供了重要手段和工具。基于此,本文提出建设包含多场域评价感知环境、智能化评价技术支撑体系、全量化评价数据集在内的综合素质评价框架,在此基础上转变评价理念,构建统一平台,研发多样化工具,抓牢数据安全,构筑政产学研用一体化的综合素质评价运转体系,从而推动综合素质评价向数字化、过程化、精准化方向发展。Currently,challenges regarding the authenticity and accuracy of data in comprehensive quality assessments persist.The new generation of information technologies,represented by artificial intelligence and big data,offers crucial means and tools to address these issues.This paper proposes the development of a comprehensive quality assessment framework that encompasses a multi-domain assessment perception environment,an intelligent technical support system for assessments,and comprehensive assessment data sets.Building on this foundation,we aim to transform assessment concepts,establish a unified platform,develop diverse tools,ensure data security,and create an integrated operation system for comprehensive quality assessment that combines government,industry,academia,research,and application,promoting the development of comprehensive quality assessment towards digitalization,process orientation,and precision.

关 键 词：综合素质评价 评价数据 智能技术 数字化转型 

分 类 号：G405[文化科学—教育学原理]