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자기조절학습 행동데이터에 대한 탐색적 연구: 해외 학습분석 연구를 중심으로

An Exploration of Self-regulated Learning Behavior Data: International Research on Learning Analytics

이유경|박소영|함은혜|이성혜
한국교육공학회 (Korean Society Of Educational Technology)|2021.06|교육공학연구 (Journal of Educational Technology)|제37권 제2호|pp. 191-236|DOI http://dx.doi.org/10.17232/KSET.37.2.191

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참고문헌

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연구동향Research trends자기조절학습Self-regulated learning학습분석Learning Analytics분석데이터Analysis data
주제분류교육학

초록

본 연구의 목적은 학습분석 기반의 자기조절학습 연구의 해외 연구 동향을 분석하고, 자기조절학습의 하위전략과 전략별 분석데이터가 무엇인지 분석하는 데 있다. 이를 위해 2020년까지 발표된 해외 학술지 논문 및 학술대회 발표자료이면서, 자기조절학습 또는 자기조절학습의 하위요인을 학습분석 방법을 적용하여 분석한 논문 50편을 분석하였다. 학습분석 기반 자기조절학습 연구의 전반적인 동향을 분석하기 위해 연도별, 연구맥락별, 데이터 수집 환경별, 연구목적별, 자기조절학습 전략 및 하위요인별 빈도 분석을 실시하였다. 분석 대상 연구 중 자기조절학습의 하위요인을 명시한 연구를 바탕으로 이들이 분석한 요인과 이러한 요인을 측정하기 위해 활용된 분석데이터를 제시하였다. 분석결과 2012년 이후 꾸준히 연구수가 증가하는 추세를 보였으며, 대학 맥락에서 수행된 연구가 대부분이었다. 데이터가 수집된 학습환경은 MOOC를 포함한 학습관리시스템이 절반 이상을 차지했다. 연구목적별로는 자기조절학습 행동을 기반으로 학습자 및 학습 행동 모델링, 행동데이터를 활용하여 성취도 등 수행결과 예측, 수행결과와의 관계 분석, 자기보고식 자기조절학습 설문 결과와 행동데이터 비교 또는 그 관계를 살펴본 연구 등으로 분류되었다. 자기조절학습 전략별로는 메타인지전략, 행동조절전략, 인지전략, 환경조절전략, 학습전략 순으로 논문 수가 많았으며, 가장 많은 연구에서 분석된 하위요인은 시간관리, 자기평가 및 성찰이었다. 또한 이와 같은 요인을 측정하기 위한 데이터가 무엇인지를 제시하고, 이를 바탕으로 자기조절학습 행동 분석데이터의 특징과 학습분석 연구를 위한 시사점을 제안하였다.

Abstract

This study seeks to analyze trends in overseas research on self-regulated learning based on learning analytics, and to analyze sub-strategies of self-regulated learning and lists of data. For the analysis, 50 papers from overseas journals and conference proceedings prior to 2020 were screened. Frequency analyses are calculated by year, research context, data collection environment, research purpose, self-regulated learning strategy, and sub-factor. Sub-factors and analyzed data are then described in light of previous studies that specify sub-factors of self-regulated learning. The results indicated a steady increase in the number of studies since 2012, most of which were conducted in the context of universities. In over half of these studies, data was collected on Learning Management Systems (LMS) and Massive Open Online Courses (MOOC). With respect to research purpose, studies may be classified as learners and learning behaviors modeling, performance prediction, relationship analysis with performance results, and behavior comparison between survey and behavioral data. With respect to self-regulated learning strategy, the greatest number of papers concern metacognitive strategy, followed by behavior control strategy, cognitive control strategy, environmental control strategy, and learning strategy. Time management and self-evaluation and reflection are the most frequently analyzed sub-factors. Analyzed data were also collected to measure these factors. Based on these results above, analysis of data on the features of self-regulating learning behavior is presented and the implications for learning analysis research are suggested.

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