面向学习者画像的数据采集方法分析  

Analysis of Data Acquisition Methods for Learner Profiles

作　　者：高广尚 GAO Guangshang(Research Center for Modern Enterprise Management,Guilin University of Technology,Guilin 541004;School of Management,Guilin University of Technology,Guilin 541004)

机构地区：[1]桂林理工大学现代企业管理研究中心,桂林541004 [2]桂林理工大学商学院,桂林541004

出　　处：《现代计算机》2021年第17期99-105,共7页Modern Computer

基　　金：国家自然科学基金项目:面向数据演化的增量实体解析方法研究(No.71761008);广西高校人文社会科学重点研究基地基金资助项目:高精度用户画像构建方法研究(No.19YB001);基于学习者画像的个性化教学改革探索与实践(No.2021B38)。

摘　　要：本文旨在对学习者在学习过程中的状态、行为数据的采集方法进行归纳、整理和分析,以期为今后数据采集方法的深入研究提供重要参考,并为学习者画像的有效构建提供强有力的数据支撑。本文首先分析学习者画像的特征维度及相应数据,然后探讨多维度数据的采集方法,包括新兴信息类技术、管理平台类技术和传统线下方式等。现有的数据采集方法能一定程度上采集到学习者在学习活动过程中的近乎真实的状态、行为数据。没有深入分析数据采集方法之间的优劣、各维度数据之间的逻辑关系和数据采集过程中的注意事项等。尽管现有的数据采集方法能一定程度上满足学习者画像构建时的数据需求,但在大数据时代仍面临数据采集难、采集量小和时效性差等挑战。This paper aims to summarize,organize and analyze the data acquisition methods of learners’ state and behavior in the learning process,so as to provide an important reference for the further study of data acquisition methods in the future,and provide a strong data support for the effective construction of learner profiles. This paper firstly analyzes the characteristic dimensions and corresponding data of learner profiles,and then discusses the acquisition methods of multidimensional data,including emerging information technology,management platform technology and traditional offline mode. The existing data acquisition methods can,to a certain extent,collect nearly real state and behavior data of learners in the process of learning activities. There is no in-depth analysis of the pros and cons of data acquisition methods,the logical relationship between the data of all dimensions and the matters needing attention in the process of data acquisition. Although existing data acquisition methods can meet the data needs of the construction of learner profiles to a certain extent,in the era of big data,there are still challenges such as difficult data acquisition,small amount of data acquisition and poor timeliness.

关 键 词：学习者画像 学习者数据 数据来源 数据采集方法 

分 类 号：G434[文化科学—教育学] TP274.2[文化科学—教育技术学]