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지성공간

교육연구와 연구방법론
판매가
수량
저자
리처드 J. 머네인, 존 B. 윌렛 저/ 박현정, 이준호, 김전옥, 손윤희, 변상민, 홍유정 공역
발행일
2020-03-30
ISBN
978-89-254-1475-1(93370)
페이지
440
판형
46배
통계적 기법에 대한 엄밀한 증명보다 계량 분석 모형의 핵심 아이디어를 직관적으로 설명하고자 한 본 저서는 특히 국내의 교육연구자들에게도 큰 가치를 지닐 것이라 생각합니다. 본 저서에서 다루고 있는 많은 방법은 계량경제학 분야에서 개발되고 경제학 분야에서 널리 활용된 방법으로 의학, 생물통계학, 교육학 등에서도 응용되고 있는 추세입니다. 이러한 방법을 차근히 익힘으로써 독자 여러분은 해당 방법론을 개발한 선행 연구자들의 아이디어를 이해할 수 있을 것입니다.
또한, 이 저서의 큰 장점은 단순히 이론을 설명하는 데 그치지 않고 다양한 통계분석법을 실제 분석에 적용하는 방법과 적용 단계에서 발생하는 다양한 이슈에 대해 선행연구자들이 어떻게 대처했는가를 다루었다는 것입니다. 대체적으로 많은 이론서는 이론만을 수식으로 전개하다 보니 이를 실제 분석에서 구현하기 위해 별도로 수고를 들여야 하는 경우가 많습니다. 반면, 실제 분석 과정을 다룬 저서의 경우, 지나치게 기술적인 측면만을 강조하다 보니 그 원리를 이해하기 어렵고 기계적으로 분석 단계만을 받아들이게 되어 연구 과정에서 의도치 않은 실수나 오류를 범하게 되는 경우도 있습니다. 이 저서를 읽다 보면, 저자인 머네인(Murnane)과 윌렛(Willett)이 그러한 한계를 새기고 이론과 실제의 균형을 잡기 위해 노력하였다는 흔적을 곳곳에서 찾을 수 있습니다.
1장에서 3장은 그와 같이 교육 연구에서의 인과 추론을 위한 여러 조건을 제시하고 있습니다. 또한, 4장에서 5장은 연구 설계에서 매우 중요한 가정 중 하나라고 할 수 있는 무선할당에 대해 다룹니다. 6장은 통계적 검정력과 표본 크기로 이론적 논의와 달리 실제 표본을 적절한 크기에서 정해야 하는 연구자들에게 도움이 되는 내용을 다루고 있습니다. 7장은 무선 할당을 교육학에서 흔히 발생하는 다층 구조의 상황으로 확장한 것으로, 최근 교육학에서 널리 사용되는 다층 모형에 관심 있는 독자에게 유용할 것입니다. 8장 이후에는 자연 실험 설계를 다루고 9장에서는 회귀 불연속, 10장과 11장에서 걸쳐서는 도구변수를 다룹니다. 그리고 12장에 대해서는 비실험 설계에서 비롯되는 편의를 교정하기 위한 제안을 다루는데, 역시 최근 교육학에서 많은 연구자들이 관심을 가지고 있는 경향점수 방식을 소개합니다. 이와 같이, 이 저서에서는 연구 설계와 관련된 여러 이슈를 폭넓게 다루고 있습니다. 따라서, 전반적으로 연구와 방법론에 대한 개론을 펼치는 1장부터 읽을 수도 있겠으나, 경우에 따라 연구에 필요한 부분만을 선별하여 활용할 수도 있을 것입니다.
서문/ 3
Chapter 01 교육연구와 인과추론
교육연구에서 인과추론의 역사 ············································································· 13
인과추론에 대한 전 세계적 관심 ··········································································· 20
이 책의 개요 ········································································································· 21
더 읽을거리 ·········································································································· 23
Chapter 02 이론의 중요성
이론이란 무엇인가? ······························································································ 28
교육학에서의 이론 ································································································ 32
바우처 이론 ·········································································································· 34
어떤 종류의 이론인가? ························································································· 37
더 읽을거리 ·········································································································· 38
Chapter 03 인과적 질문을 위한 연구 설계
좋은 연구의 조건 ·································································································· 42
인과추론의 조건 ··································································································· 44
인과추론에 대한 과거의 접근 방식 ······································································· 47
인과추론의 핵심 문제 ··························································································· 49
더 읽을거리 ·········································································································· 54
Chapter 04 연구자-설계 무선 할당 실험
무선 할당 실험 ····································································································· 60
무선 할당 실험에서의 데이터 분석 ······································································· 67
더 읽을거리 ·········································································································· 79
Chapter 05 연구자-설계 무선 할당 실험에서의 이슈들
실험 설계 시 핵심적인 결정 사항 ·········································································· 84
무선 할당 실험의 타당성을 저해하는 요소들 ························································ 92
무선 할당 실험에 대한 피험자들의 저항에 대처하기:인도의 사례 ······················ 97
더 읽을거리 ········································································································ 105
Chapter 06 통계적 검정력과 표본 크기
통계적 검정력 ···································································································· 110
통계적 검정력에 영향을 미치는 요인 ·································································· 122
더 읽을거리 ········································································································ 134
Chapter 07 군집 수준의 무선 할당 실험
확률 절편 다층모형을 활용한 집단 수준의 처치 효과 추정 ································· 141
군집 수준 무선 할당 실험에서의 통계적 검정력 ················································· 151
고정효과 다층모형을 활용한 처치효과 추정 ······················································· 158
더 읽을거리 ········································································································ 165
Chapter 08 자연 실험 연구
자연 실험과 연구자 설계 실험의 비교 ································································ 170
자연 실험의 두 가지 연구 사례 ··········································································· 171
자연 실험 사례 찾기 ··························································································· 180
분석 대상의 범위 선정 문제 ··············································································· 184
자연 실험 연구의 타당도에 영향을 미치는 요인 ················································· 187
더 읽을거리 ········································································································ 199
Chapter 09 회귀 불연속 설계
학급당 학생 수가 학업 성취도에 미치는 영향 ····················································· 204
결과변수와 할당변수의 관계 일반화하기 ···························································· 224
회귀 불연속 설계의 타당성에 대한 추가적인 위협 ·············································· 235
더 읽을거리 ········································································································ 240
Chapter 10 도구변수 추정에 대한 소개
도구변수 분석에 대한 소개 ················································································· 244
교육수준이 시민참여에 미치는 인과적 영향에 대한 OLS 추정치에서 발생하는 편의 ···································································································· 247
도구변수 추정 ···································································································· 255
IVE(도구변수 추정)의 두 가지 주요 가정 ··························································· 264
도구변수 추정치를 얻기 위한 대안적인 방법들 ················································· 267
도구변수 추정 접근의 확장 ················································································· 278
도구변수 탐색 및 방어하기 ················································································· 294
더 읽을거리 ········································································································ 305
Chapter 11 준실험에서 처치 효과를 구하기 위한 도구변수의 활용
“준실험”의 개념 ·································································································· 311
준실험에서 처치의 인과효과를 추정하기 위해 도구변수 활용하기 ····················· 312
준실험 맥락에서 도구변수 추정치에 대한 더 깊은 통찰 ······································ 318
회귀 불연속 설계에서의 “불분명함”을 해결하기 위해 도구변수 추정 활용하기 ··· 323
더 읽을거리 ········································································································ 328
Chapter 12 비실험자료로 추정된 처치 효과의 편의 교정
층화 방법을 통해 관측 편의 줄이기 ···································································· 333
회귀분석에서 공변인 직접 통제를 통해 관측 편의 줄이기 ·································· 349
경향점수 접근을 통해 관측 편의 줄이기 ····························································· 354
경향점수 매칭을 활용한 처치 효과 추정 ····························································· 364
실제적인 질문 ···································································································· 372
더 읽을거리 ········································································································ 373
Chapter 13 오랜 탐구로 얻은 방법론적 교훈
확실한 이론을 가져라 ························································································· 378
연구 대상과 관련된 문화, 규칙, 제도를 파악하라 ··············································· 380
반사실(counterfactual)을 이해하라 ································································· 382
선택 편의를 항상 경계하라 ················································································· 383
다양한 결과변수를 사용하라 ·············································································· 385
장기적 영향을 고려하라 ····················································································· 386
하위집단에 대한 효과를 검증하라 ······································································ 387
결과를 정확하게 해석하라 ·················································································· 389
비정상적인 결과에 주목하라 ·············································································· 391
좋은 연구는 언제나 새로운 질문으로 이어진다 ·················································· 392
더 읽을거리 ········································································································ 394
Chapter 14 중요한 교훈과 앞으로의 과제
정책 가이드라인 1:학교 입학을 위한 비용(등록금)을 줄여라 ··························· 399
정책 가이드라인 2:아이들의 일상적인 학교생활을 변화시켜라 ························ 402
정책 가이드라인 3:동기부여를 개선하라 ························································· 406
정책 가이드라인 4:가난한 학생들에게 보다 많은 학교교육 선택지를 제공하라 ············································································ 412
요 약 ·················································································································· 415
나가며 ················································································································ 417
참고문헌 ············································································································· 418
찾아보기 ············································································································· 434
박현정
서울대학교 교육학과를 졸업하고 동 대학원에서 석사학위를 취득하였으며 University of Minnesota에서 교육측정 및 통계를 전공으로 박사학위를 취득하였다. 현재 서울대학교 교육학과 교수(교육측정평가전공)로 재직 중이며, 주요 관심분야는 국제비교분석, 종단자료의 분석, 다층자료 분석 등이다.
이준호
서울대학교 교육학과에서 학사 및 석사학위(교육측정평가 전공)를 받았다. 현재 University of California, Berkeley에서 양적 연구방법 박사과정을 마치고 University of Alabama 조교수 임용을 앞두고 있다. 교육재정 및 경제 현상에 관한 이론적 연구와 처치효과 변이성에 대한 방법론적 연구에 관심이 있다.
김전옥
서울대학교 교육학과를 졸업한 후, 동대학원에서 교육측정평가 전공으로 석사학위를 받았다. 현재 UCLA 교육학과 박사과정에 재학 중이다. 세부전공은 양적방법연구로, 관심분야는 다층모형, 베이지안추론, 인과추론 등이다. 이와 같은 통계모형을 적용하여, 기존의 교육학 연구들을 통합, 검증하는 메타분석과 재현연구의 분석방법을 개선하는 것이 목표이다. UCLA 산하 교육연구소인 CRESST에서 통계분석을 담당하는 연구조교로 근무하고 있다.
손윤희
서울대학교 지구과학교육과를 졸업한 후, 교육학과 대학원에서 교육측정평가 전공으로 석사, 박사학위를 받았다. 주요 관심 분야는 다층 모형, 구조방정식모형, 혼합모형, 매개효과 분석 등이다. 현재 한국교육과정평가원에서 부연구위원(위촉)으로 근무하고 있으며, 국가 수준 학업성취도 평가 관련 업무를 수행하고 있다.
변상민
서울대학교 교육학과를 졸업하고, 동 대학원의 교육측정평가 전공으로 석사학위를 취득하였다. 현재 동 대학원 박사과정을 수료하였다. 연구 관심 분야는 구조방정식, 다층모형, 종단자료 분석을 위한 모형 개발 및 실증 자료 분석이다. 또한, 준실험 및 비실험 자료에서의 인과추론을 위한 방법론, 가중치 활용 등에 관심을 두고 있다.
홍유정
경인교육대학교를 졸업하고, 서울대학교 교육학과에서 교육측정평가 전공으로 석사학위를 취득하였다. 현재 동 대학원 박사과정에 재학 중이다. 주 연구 분야는 국제비교연구, 다층모형연구, 종단자료를 이용한 인과효과 연구 등이다. 더불어 인과추론에 기반한 교육정책효과 연구에 관심이 있다.
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