컴퓨터 기반 협력학습 환경에서 인식정보 제공을 위한 학습분석 기법 설계 연구
The Design Research of Awareness Information UsingLearning Analytics in Computer-Supported Collaborative Learning
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초록
최근 국가나 대학 주도로 고등교육의 질을 개선하고 혁신하기 위하여 컴퓨터를 기반으로 한 학습 환경인 무크(MOOCs: Massive Open Online Courses)나 KOCW(Korea Open CourseWare), 플립러닝(flipped learning) 등을 대학 교육에 적용하고 있다. 이러한 변화는 그동안 블랙박스로 여겨졌던 고등교육의 학습과정을 빅데이터의 형태로 누적·분석할 수 있는 기회를 제공해주며, 이를 통해 고등교육 기관은 학습자들의 학습 활동을 촉진하거나 학습 성공을 예측할 수 있게 되었다. 이러한 학습분석 기법(learning analytics)과 관련된 연구들은 대부분 개인 학습자들의 학습과정에 초점을 두고 있는데, 본 연구에서는 동료 학습자의 학습 활동과 관련된 빅데이터를 분석하여 컴퓨터기반협력학습 환경에서 학습자간 상호작용을 촉진시켜주는 인식정보의 설계 및 제공 방법에 대해 탐색해보고자 한다.
Abstract
In this paper, we examine workspace awareness information to promote the learners' interaction by using learning analytics in computer-supported collaborative learning environments. Recently, many universities have adopted new educational innovations like MOOCs(Massive Open Online Courses), KOCW(Korea Open CourseWare) and flipped learning to improve quality of higher education. These computer-supported collaborative learning environments can capture, report, process and act on the university students learning process data although viewing it as "the black box" so far. The analysis of learner-produced data, what we might call, the learning analytics(LA), is used to assess academic progress, predict future performance and make informed decisions aimed at improving outcomes. But most LA researches focus on data at individual level, and they are limited to profiling peer learners behavior in workspace for promoting learners' interaction. So, this paper explores design and implementation of workspace awareness information to help learner to understanding how co-learner socially interact in computer-supported collaborative learning.
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