학습분석학 국내 문헌 고찰: 로그 데이터를 이용한 실증연구를 중심으로

초록

Learning analytics is a research method used in data collection, analysis, and reporting of learners' progress, for purposes of understanding, predicting, and optimizing learners' learning process. Along with the rapidly increasing use of online learning, data derived analytics methods are anticipated to improve the quality of education. However, research on learning analytics is relatively new in Korean academia. This study aims to identify research trends in Korea on the (1) learning settings, (2) research objectives, and (3) research methods used in learning analytics literatures. Using Papamitsiou & Economides‘s(2014) review process as a guideline, we surveyed empirical studies published in Korea between 2008 and 2016, and 61 were aggregated for in-depth analysis. The results show that most research published in Korea is limited to applying learning analytics in the context of VLEs/LMSs and web-based learning platforms. For research objectives and research methods also narrowly focused on objectives and research methods. The implication of this study is that the Korean academia needs to expand to different applications of learning analytics to include instructional strategies, prediction of student success, and prevention of dropouts. Furthermore, we need to expand to include the design of MOOC, cognitive tutor system, and mobile learning systems to offer automated data extraction and data mining, and capablities of visualized personalized data. These data-driven learning environment could foster learning analytics research and improve quality of teaching and learning.

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