국가수준 학업성취도 평가에 기초한 학교평가 통계 모형의 고찰
Monitoring School Performance Based on National-level Achievement Test
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이 글은 최근 한국에서 뜨거운 감자로 부각되어 있는 교육이슈 중 하나인 국가수준 학업성취도평가 자료를 어떻게 분석하고, 그 결과를 어떻게 보고하고, 또 활용할 것인가 하는 문제의식에서출발하였다. 이러한 문제의식에서 이 글은 국가수준 학업성취도 평가에 기초한 학교평가의 방향,평가 설계, 평가 지표에 대한 이해, 평가를 위한 검사척도의 문제, 통계적 모형 등을 종합적으로고찰하였다. 성장평가 모형을 같은 학생을 반복적으로 측정한 자료를 이용하는 종단연구설계 모형과 같은 학년의 학생을 반복적으로 측정하는 코호트 성장모형으로 구분하고, 각각의 통계모형을 제시하였다. 현행 국가수준 학업성취도 평가는 기본적으로 같은 학년의 학생을 반복적으로 측정하는코호트 설계에 따른 평가방법이다. 하지만, 수년 후에는 한 학생의 학업성취도의 변화를 종단적으로 추정할 수 있으며, 이러한 학생의 학업성취도의 변화에 학교급별로 - 초등학교, 중학교, 고등학교- 어떤 영향을 주었는지를 통계적으로 모형화 할 수도 있다.
Abstract
Our purpose in writing this paper is to present and discuss a statistical model that is suitable for the national-level achievement test that has been implemented for the past two years. We first examine the multiple aspects of school performance evaluation – 1) perspectives of monitoring school performance including goals,contents, evaluation units, and status vs. growth; 2) school performance indicators;3) test metrics such as percentiles, normal curve equivalents, and vertically equated scale score; 4) status model vs. growth model; 5) longitudinal data structure for measuring growth over time; 6) the consequence of evaluating school performance based on different criteria. The principle of design in national-level achievement test is called quasi-longitudinal, or cohort design, and measures the same grade of students over time in contrast to true longitudinal, or panel design, in which the same students are measured over time. In the second part of this paper, we present two different 3-level hierarchical models; one model for the true longitudinal design and the other for cohort design. Lastly, we provide policy-related suggestions regarding how to take full advantage of the results from the national-level achievement test and analyze the implications of doing so.
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