문제 풀이 상황에서 학습자의 시선 경로 유사도에 따라 구분한 집단 간 인지부하 및 성취도 차이
Cognitive Load and Achievement Differences according to Learner’s Scanpath Similarity in Problem Solving Learning
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초록
문제 풀이 상황에서 정보처리는 문제 풀이 전략에 따라 다르다. 따라서 시선 경로를 통해 나타나는 정보처리 과정은 학습자의 문제 풀이 전략 수준에 따라 차이를 보일 것이다. 본 연구에서는 문제 풀이 상황에서 발생하는 학습자의 시선 경로를 정보처리 과정으로 보고, 학습자가 정보처리 과정에서 경험하는 인지부하 및 성취도의 차이를 살펴보고자 하였다. 이를 위해 시선 경로 유사도 수준에 따라 집단을 나누고, 집단 간 인지부하 차이를 t-검정을 통해 측정하였다. 또한, 인지부하의 차이가 성취도의 차이를 예측하는지 살펴보기 위해 로지스틱 회귀분석을 실시하였다. 수도권 소재 대학의 학부생 26명을 대상으로 문제 풀이 중에 발생하는 시각 행동 데이터를 분석하였다. 시선 경로는 AOI(Area Of Interest)별 시선 고정(fixation) 순서와 시선 고정 지속시간(duration)을 고려하여 문자열로 구성하였고, 유사도는 Levenshtein method로 편집거리(edit distance)를 계산한 뒤 정규화하였다. 분석 결과 첫째, 시선 경로의 유사도 상․하 집단 간 인지부하를 나타내는 시각 운동 지표들(동공 확장 크기, 시선 고정횟수, 시선 고정 지속시간) 간에 차이가 있었다. 그 차이는 통계적으로 유의하였다. 둘째, 시선 경로 유사도 상-집단은 하-집단에 비해 높은 성취도를 나타냈다. 이는 통계적으로 유의하였다. 본 연구는 문제 풀이 상황에서 시선 경로 유사도가 정보탐색 및 정보처리의 특성을 대변하는 지표가 될 수 있음을 확인하였다. 이는 실시간-비간섭적 지표를 활용함으로써 지능형 개인별 맞춤화 처방을 위한 이론적 기반이 마련됐다는 점에서 교수학습적 의의가 있다.
Abstract
In problem-solving learning, information processing depends on the problem-solving strategy. Therefore, the information processing process that appears through the scanpath will differ depending on the level of the problem-solving strategy of the learner. In this study, the learner’s scanpath in a problem-solving learning was considered as an information processing and examine the differences in cognitive load and achievement that learners experience in the information processing process. To this end, the groups were divided according to the scanpath similarity level, the difference in cognitive load between groups were measured through t-test. In addition, logistic regression analysis was performed to see whether differences in cognitive load predicted the differences in achievement. 26 university students were analyzed for visual behavior data occurred during problem-solving learning. The scanpath was composed of strings in consideration of the gaze fixation order and gaze fixation duration by AOI. The similarity was normalized after calculating the edit distance using the Levenshtein method. As a result of the analysis, first, there was difference in visual behavior indicators indicating cognitive load between high and low groups of scanpath similarity. Second, the group with high scanpath similarity predicted achievement positively. This study confirmed that the scanpath similarity can be an indicator of information search and information processing in problem solving learning. This has the significance of teaching and learning in that the theoretical basis for the intelligent personalized prescription is prepared by using real-time and non-interfering indicators.
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