CAJ | 학술논문

当前在商业和教育领域，分析技术已经成为研究的热点问题。实际上分析技术的历史发展由来已久，只不过近年来在大数据、新技术发展和商业需求三股力量的综合角力之下，使得分析技术在商业智能、Web分析、人工智能和数据挖掘、社会网络分析、信息可视化、学习分析等领域得到了进一步的发展。在教育领域，分析技术涵盖教学、机构和管理等范畴，其应用的焦点主要集中在学习分析上。学习分析的核心是如何对教育数据进行收集、整理、分析和预测，目的是利用数据挖掘和建模技术增强学生对教与学的理解，并为其提供有效的个性化教育，当前的教育应用主要体现在适应性测试与跟踪、早期预警与干预两个层面。然而分析技术在教育领域中的应用还存在一些问题和挑战，我们需要理性地认识其功能和特性，以谨慎的态度推动其应用。由于教育系统与学习过程本身的复杂性、技术的工具性、数据的情境性等因素，单纯依据一系列的数据来评判学生的学习并不科学，应将学习分析建基于获得广泛支持的教学理论之中，使其能够真正促进教育的发展。
당전재상업화교육영역，분석기술이경성위연구적열점문제。실제상분석기술적역사발전유래이구，지불과근년래재대수거、신기술발전화상업수구삼고역량적종합각력지하，사득분석기술재상업지능、Web분석、인공지능화수거알굴、사회망락분석、신식가시화、학습분석등영역득도료진일보적발전。재교육영역，분석기술함개교학、궤구화관리등범주，기응용적초점주요집중재학습분석상。학습분석적핵심시여하대교육수거진행수집、정리、분석화예측，목적시이용수거알굴화건모기술증강학생대교여학적리해，병위기제공유효적개성화교육，당전적교육응용주요체현재괄응성측시여근종、조기예경여간예량개층면。연이분석기술재교육영역중적응용환존재일사문제화도전，아문수요이성지인식기공능화특성，이근신적태도추동기응용。유우교육계통여학습과정본신적복잡성、기술적공구성、수거적정경성등인소，단순의거일계렬적수거래평판학생적학습병불과학，응장학습분석건기우획득엄범지지적교학이론지중，사기능구진정촉진교육적발전。
There is currently a growing interest in analytics across business and educational communities. Actually, analytics is not completely nothing new, just because the three main factors, including the big data, techniques and the business need, are coming together to stimulate interest in making more use of it in Business Intelligence, web analytics, Artificial Intelligence and data mining, Social Network Analysis, information visualization and learning analytics, etc. In education, analytics is applied into both inside and outside of the teaching and learning practice, with a focus on learning analytics in which the educational data is analyzed to identify students＇ behavior patterns and provide effective information to improve learning and learning-related activities. At the moment, most educational data-related projects under the umbrella of analytics or learning analytics include tracking students＇ learning, providing early alerts and interventions. However, a number of unanswered questions, concerns, and hesitations suggest that there is a need to move analytics forward with caution and reflection. Some early analytics projects found that it was dangerous to make decisions about students＇ learning based solely on a set of data, as it is essential to understand the context of the data and develop the relationship between the tutor and student. Furthermore, learning analytics does not offer a short cut to providing teaching professionals with universal advice on＂what works＂.