CAJ | 학술논문

学习分析是“大数据”在教育领域的应用，引发了教育技术发展的第三次浪潮，并获得学术界的广泛关注。本文梳理了学习分析的形成过程，然后从利益相关者、研究目标、研究对象、技术方法四个维度，回顾了近五年来国内外学者在学习分析方面的研究成果，并提出未来发展趋势和可能遇到的挑战，便于相关人员制定教育决策、优化教育管理过程以及完善学习过程。研究结果表明，学习分析研究主题主要涵盖学习者知识建模、学习情绪建模、学习行为特征抽取、学习活动跟踪、学习者建模、学位获取分析、教学资源和教学策略优化、自适应学习系统和个性化学习、在线学习影响因素分析九个方面；分析数据主要来源于集中式学习环境、分布式学习环境以及身体活动数据；常用分析方法包括统计分析、信息可视化、数据挖掘、社会网络分析、话语分析和网站分析。目前，学习分析研究遇到的挑战包括教育数据预处理难度大、数据访问权限不明确、学习分析适用性有限。虽然学习分析尚处于发展初期，但由于能够为教育系统各级决策提供科学参考，已经成为教育信息化的重要内容之一。
학습분석시“대수거”재교육영역적응용，인발료교육기술발전적제삼차랑조，병획득학술계적엄범관주。본문소리료학습분석적형성과정，연후종이익상관자、연구목표、연구대상、기술방법사개유도，회고료근오년래국내외학자재학습분석방면적연구성과，병제출미래발전추세화가능우도적도전，편우상관인원제정교육결책、우화교육관리과정이급완선학습과정。연구결과표명，학습분석연구주제주요함개학습자지식건모、학습정서건모、학습행위특정추취、학습활동근종、학습자건모、학위획취분석、교학자원화교학책략우화、자괄응학습계통화개성화학습、재선학습영향인소분석구개방면；분석수거주요래원우집중식학습배경、분포식학습배경이급신체활동수거；상용분석방법포괄통계분석、신식가시화、수거알굴、사회망락분석、화어분석화망참분석。목전，학습분석연구우도적도전포괄교육수거예처리난도대、수거방문권한불명학、학습분석괄용성유한。수연학습분석상처우발전초기，단유우능구위교육계통각급결책제공과학삼고，이경성위교육신식화적중요내용지일。
Learning analytics is a big data application in the field of education, triggering the development of the third wave in educational technology, and receiving wide attention from international and domestic academics. The ar-ticle reviews the origin of learning analytics, and then from four dimensions of whom, why, what, how, recalling the past five years relevant research results, and puts forward future development challenges that may be encountered. Spe-cifically, based on macro, meso and micro perspective, this research facilitates related personnel to make education de-cisions, optimize the educational management process and improve the learning process. <br> Research topics cover nine aspects including:learners' knowledge modeling, learners' emotion modeling, learning behavior feature extraction, learning activities tracking, the learner modeling, obtaining degree analytics, the teach-ing resources and the teaching strategy optimization, adaptive learning system and personalized learning, and online learning influence factors analysis. The data mainly comes from the centralized learning environment, distributed learning environment, and physical activity data. The common analysis methods include statistical analysis, informa-tion visualization,data mining, social network analysis, discourse analysis, and web analytics. The challenges in-clude:the difficulty of data preprocessing, the uncertainty of data accessing rights, and the limited application scope. Although the study is still in the initial stages of development, it has become an important part of educational informa-tionization as it provides scientific reference for decision-making at all levels of the education system.