2025/02/28 by Pui Yi Mok, Hsueh‐Hua Chuang, Ming‐Min Cheng +1 · 6 citations
Computer Science · Psychology · #Applied psychology #Artificial intelligence #Computer science #Conceptualization #Concurrent validity #Confirmatory factor analysis #Construct (python library) #Construct validity #Convergent validity #Creativity #Creativity in Education and Neuroscience #Developmental psychology #Discriminant validity #Exploratory factor analysis #Internal consistency #Machine learning #Psychology #Psychometrics #Reliability (semiconductor) #Sample (material) #Social psychology #Sport Psychology and Performance #Structural equation modeling #Virtual Reality Applications and Impacts
paper · pdf · doi:10.1002/jocb.70004
published in The Journal of Creative Behavior 59(1) (Wiley)
openalex publication_date 2025/02/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
ABSTRACT Considering the pivotal role of creativity across various eras and the rapid integration of Artificial Intelligence (AI) in both creative processes and education, this study introduces and provides validity evidence for the AI‐assisted Creativity Questionnaire (AICQ). This new 16‐item instrument aims to quantify human creative potential in AI‐assisted endeavors. Initially, a diverse cohort of 322 university students in Taiwan completed the AICQ from November to December 2023. Through exploratory factor analysis (EFA) of responses from this sample, three distinct factors emerged: (1) AI‐assisted functional creativity (AIFC), (2) AI‐assisted visual artistic creativity (AIVAC), and (3) AI‐assisted ideational creativity (AIIC). One item was removed due to cross‐loading. Subsequently, in September 2024, 330 university students in Taiwan engaged with both the AICQ and the 28‐item Creative Behavior Inventory (CBI). Based on responses from this sample, construct validity evidence for the AICQ was examined using confirmatory factor analysis (CFA), which affirmed that a three‐factor model provided a good fit to the data. Gender differences in AICQ scores were found in these subsequent data. Overall, data from participants provided evidence for the reliability as well as convergent, concurrent, and discriminant validity of the scores obtained from the AICQ.