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창의성과 지능 그리고 개방성의 구조모형 검증

Examining the Structural Models for Creativity, Intelligence and Openness

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초록

본 연구의 목적은 창의성에 대한 지능과 개방성의 구조를 확인하고자 하는 것이다. 이를 위하여 4개 대학교 학생 296명에게 창의적 은유 생성 검사와 Gf, Gc, Glr 지능 검사, 그리고 개방성 검사를 실시하였다. 창의성 점수는 피험자들이 가장 창의적이라고 선택한 반응 2개를 전문가 3인이 사정하는 Top 2 방법으로 산출하였다. 연구문제 1에서 지능의 구조에 따라 창의성에 대한 예측력에 차이가 있는지 분석한 결과, 상위 지능요인이 하위 지능요인들보다 창의성에 대한 설명력이 높은 것으로 나타났다. 하위 지능요인들은 창의성의 21.4%를 설명하였으며, Gf(β=.364, p<.001)와 Gc(β=.251, p<.01)의 영향이 유의하게 나타났다. 상위 지능요인은 창의성을 28.5% 설명하였으며, β값은 .534(p<.001)였다. 연구문제 2에서는 성격의 개방성 요인에서 지적 국면을 제외하는 경우, 모델이 보다 간명해지고, 창의성을 보다 적합하게 예측하는지를 확인해보았다. 지적국면을 포함한 모형(X2/df=1.633, IFI=.899, CFI=.897, RMSEA=.046, AIC= 475.812)보다 제외한 모형(X2/df = 1.490, IFI=.923, CFI=.921, RMSEA=.041, AIC=411.185)이 보다 간명하게 모델을 설명하는 것으로 나타났다.

Abstract

The purpose of this study was to examine the effects of intelligence and openness on creativity. A sample of 296 college students completed two tasks of creative metaphor generation, measures of fluid intelligence, crystallized intelligence, long-term storage and retrieval, and a measure of openness. Results indicate that the three lower-order intelligence factors accounted for 21.4% of the variance in the creativity scores, and the effects of fluid intelligence (β = .364, p < .001) and crystallized intelligence (β = .251, p < .01) were significant. A higher-order intelligence factor (β = .534, p < .001) composed of the lower-order factors accounted for 28.5% of the variance in the creativity scores. Also, we examined if the models were simpler and predicted creativity better when the intellect aspect was excluded from openness. Although the variances of explanation and β values between the two models were very similar, the model fits were more appropriate when the intellect aspect was excluded (X2/df = 1.490, IFI = .923, CFI = .921, RMSEA = .041, AIC = 411.185) than when it was included (X2/df = 1.633, IFI = .899, CFI = .897, RMSEA = .046, AIC = 475.812).

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