규칙장과 주요소장에서의 문항반응유형의 통계적 분류

서지정보

· 발행기관 : 한국교육학회
· 수록지 정보 : 교육학연구 / 34권 / 1호
· 저자명 : 金成勳

목차

요약
Ⅰ. 연구의 목적 및 필요성
Ⅱ. 연구의 내용
Ⅲ. 연구 방법
Ⅳ. 문항반응유형의 시뮬레이션 결과
Ⅴ. 규칙장과 주요소장에서의 통계적 분류 결과
Ⅵ. 논의
參考文獻
Abstract

초록

학생들의 오류 방략(strategy) 또는 오개념 유형을 진단하기 위해서는 규칙장에서 통계적 분류 방법 중 판별분석을 사용하는 것이 효과적임이라는 사전 연구에 이어 첫째, 이 연구에서는 규칙장을 이용한 판별분석이 주요소장에서의 분류보다 효과적인지, 둘째, 이론상 기대되는 슬립(slip : 5쪽 참조)의 수를 가정한 분류와 이외의 경우의 분류 결과는 어떤 차이가 있을 것인지, 셋째, 각 규칙 집단간 분류 결과는 어떤 양상을 보일 것인지를 몬테칼로 연구를 동하여 분석하였다. 그 결과 주요소장에서의 분류가 슬립이 작게 일어날 경우에는 더 정확했으나 슬립의 수가 많아지는 경우에는 규칙장이 더 효과적일 것으로 나타났다. 그리고, 슬립의 수가 많을수록 오분류비율이 늘어나고, 근접한 집단간 오분류가 많음을 알 수 있었다. 이어서 슬립의 수를 재 개념화, 비슷한 규칙들의 통합에 의한 분석 등을 위하여 실지로 학생들의 검사 결과를 자세히 분석해 볼 필요가 있음을 논의하였다.

영어초록

This study was to investigate a practicability of rule space theory. Three research research questions were hypothesized. First, the classfications of item response patterns in rule spaces would result in the same error rates as those in the fields composed of the first two principal components which were computed from the item response patterns which were used in the classifications in rule spaces. Second, the classifiers would equally behave over the varying number of slips. Third, misclassification rates would be the same among the rule groups within a dataset.
A Mont-Carlo study was processed in four steps. First, using MCGENPC developed by Tatsuoka & Bailie(1988). two equivalent sets of 1800 40-item response patterns. a total of 3600. were simulated for each number of slips. which were varied 1 through 5 and expected numbers. One set was consisted of 9 rule groups. each of which contained 200 item response patterns. Those 9 groups were specially selected to form three triplets. one in the center area of ability continuum, and the other two in both extremes fo the continuum. Second, from each set of item response patterns, rule space variables and prinipal component scores were computed separately. These datesets then fomulated to enable to test the hypotheses on the effects of rule/principal-component field, the number of slips, and group memberships on the error rates. Third, a series of discriminant analyses were processed, which resulted in four types of error rates. two apparant error rates and two error rates from separate samples from each equivalent dataset. Fourth, hypotheses were tested.
Ahead of presenting the classification results, equivalence of the mathched datasets was tested. T-test of the mean differences and F-tests of the variance differences evidenced the equivalences of locations and shapes, respectively.
Findings enabled to reject all of the null hypotheses. First, the classfications in rule spaces were more erroneous when the number of slips were less than 5. But, the use of rule space provided more consistent and less errornous results when the number of slips were set to the theoretically expected ones. Second, as number of slips increased. error rates rised. Third, misclassifications happenned more frequently between the groups located closer.
Based on the results, three points were discussed. First, the comparison between the classifications in rule-space and in principal-component space was basically to research a effectiveness of rule-space model. It was clarified that even a positive result for principal component space could not replace the rule space for cognitive diagnostic measure. Second, number of slips might well be studied for its redefinition. Finally, a practical research deserves for a possibililty of a broader grouping of similar rules and of redefinition of the number of slips.

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