我国教育大数据的研究现状、问题与对策——基于CNKI学术期刊的内容分析  

The Research Status,Problems and Countermeasures of Educational Big Data in China——Content Analysis based on CNKI Academic Journals

作　　者：李振[1] 周东岱[1,2] 董晓晓 黄雪娇 LI Zhen;ZHOU Dongdai;DONG Xiaoxiao;HUANG Xuejiao(School of Information Science and Technology,Northeast Normal University,Changchun,Jilin,China 130117;Science and Technology Innovation Center in “Internet+ ” Education of Jilin Province,Changchun,Jilin,China 130117)

机构地区：[1]东北师范大学,吉林长春130117 [2]吉林省"互联网+"教育科技创新中心,吉林长春130117

出　　处：《现代远距离教育》2019年第1期46-55,共10页Modern Distance Education

基　　金：2017年度吉林省科技发展计划项目"智能移动终端教学软件平台构建的关键技术与应用示范"(编号:20170204001GX)

摘　　要：教育大数据现已成为促进教育变革与创新的技术力量和思维方式,也成为当前教育技术领域研究的热点问题。但目前国内教育大数据的研究主题相对分散,缺乏系统性的梳理总结。鉴于此,以CNKI 2010—2018年刊发的相关学术论文为研究对象,采用内容分析法,从基础理论、分析模型、关键技术与方法、典型应用等方面对其进行分析、归纳,以构建国内教育大数据研究的全景框架。研究发现,当前我国教育大数据研究形态以模型构建为主,基础理论研究不足、关键技术方法有待突破、应用及实证研究有待加强等问题突出。针对这些问题,我国教育大数据的发展急需强化跨学科探索性研究,加强研究数据融合等关键技术,加强基于深度学习的教育大数据智能分析,强化大数据的常态化应用并开展广泛的实证研究。Educational big data has become a technological force and a way of thinking to promote educational reform and innovation.But at present,the research literature related to educational big data in China is relatively fragmented,lacking systematic combing and research.Therefore,we use content analysis method to analyze and summarize the basic theory,analysis model,key technology and methods,and typical applications,trying to build a panoramic framework for educational big data.It is found that the main research of educational big data in China is focus on model construction,while the research of basic theory is insufficient,and the key technology and methods need to be broken through,and the application and empirical research are few.In order to solve these problems,the research on educational big data in China needs to strengthen the interdisciplinary exploration,solve the key technologies,strengthen the intelligent analysis of big data based on deep learning,strengthen the consistent use of big data and carry out extensive empirical research.

关 键 词：教育大数据 教育数据科学 分析模型 学科交叉 深度学习 

分 类 号：G43[文化科学—教育学]