자동화된 피드백에 대한 체계적 문헌 고찰: 2013-2022년 국내 연구를 중심으로
A Systematic Literature Review of Automated Feedback: Research from 2013 to 2022 in Korea
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초록
테크놀로지를 활용하여 학습자의 학습 정보를 수집하고 수집한 데이터를 기반으로 피드백을 생성하고 전달하는 자동화된 피드백 관련 연구가 주목을 받고 있다. 이에 본 연구는 국내 연구에서 다루어진 자동화된 피드백의 연구 동향을 살펴보고 자동화된 피드백 연구의 교육적 기여에 대한 시사점을 도출하기 위해 체계적 문헌 분석을 실시하였다. 본 연구에서 자동화된 피드백이란 테크놀로지 기반 학습 환경에서 생성되고 전달되는 피드백으로, 학습자 반응의 옳고 그름에 대한 정보에 해당하는 미시적 관점의 자동화된 피드백뿐만 아니라 바람직한 성취로의 진행을 돕기 위해 제공되는 학습자의 현재 학습 상태 및 수행에 대한 정보인 거시적 관점의 자동화된 피드백까지 포함한다. 이를 위해 미시적 관점과 거시적 관점에서 각각 도출한 키워드로 2013년에서 2022년 사이에 출판된 문헌을 수집하여 자동화된 피드백 관련 실증연구 64편을 최종적으로 선정하였다. Deeva와 동료들(2021)이 제안한 자동화된 피드백 시스템 프레임워크에 따라 분석한 결과, 교정적 피드백 및 학습자가 피드백에 대해 통제권을 가지지 않는 경우가 주를 이뤘으며, 적응적 피드백 보다는 비적응적 피드백이, 학습자 요청 시 보다는 과제 완료 후 또는 즉각적으로 제공되는 피드백이 빈번하게 제공되었음을 파악하였다. 한편 본 연구에서 도출한 자동화 수준 관련 분석 틀을 기준으로 분석한 결과, 미시적 차원(68.75%)과 거시적 차원(31.25%)의 자동화된 피드백이 모두 나타났고, 일부 자동화된 피드백(25%)보다 완전 자동화된 피드백(75%)이 더 빈번하였음을 확인하였다. 연구 결과를 바탕으로 향후 자동화된 피드백의 설계 시에 고려해야 할 시사점을 논의하였다.
Abstract
Feedback plays a crucial role in enhancing students’ academic performance. With the advancement of technology, active research has been conducted on feedback automatically generated and delivered to learners. In this study, automated feedback refers to any kind of feedback provided by a technology-enhanced learning environment to help learners progress toward desired outcomes, including general information about their current learning status and performance, as well as information about the correctness of their responses. This study aims to explore the research trends of automated feedback in Korea by systematically reviewing domestic studies on automated feedback for the past decade. Sixty-four empirical studies on automated feedback published between 2013 and 2022 were selected, with keywords chosen from both the micro and macro perspectives. First of all, based on the framework for automated feedback systems proposed by Deeva and colleagues (2021), it was found that non-adaptive feedback was more frequently provided than adaptive feedback. In addition, feedback was more often provided after task completion or immediately rather than at the learner’s request. Corrective feedback was the most commonly provided, and learners had no or less control over feedback. Secondly, based on the framework developed in this study, we found that automated feedback at both micro and macro levels was discussed in domestic studies, with fully automated feedback accounting for 75 percent, more than partially automated feedback. Based on the findings, we discuss implications for future automated feedback design.
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