Artificial Intelligence Assisted Creativity
Conceptualization, Instrument Development and Validation
Bibliographic Data
| ID | 7170893 |
|---|---|
| Authors | Pui Yi Mok (0009-0004-4516-4794, Institute of Education National Sun Yat‐sen University Kaohsiung Taiwan), Hsueh-Hua Chuang (0000-0001-8580-7652, Institute of Education National Sun Yat‐sen University Kaohsiung Taiwan, corresponding author), Ming‐min Cheng (0000-0002-7085-201X, Institute of Education National Sun Yat‐sen University Kaohsiung Taiwan), Thomas J Smith (0000-0003-1310-8742, Department of Educational Technology, Research and Assessment Northern Illinois University DeKalb Illinois USA) |
| Year | 2025 |
| Volume | 59 |
| Issue | 1 |
| Publication date | 2025-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Journal of Creative Behavior (JOURNAL) |
| Journal identifiers | ISSN: 0022-0175 • E-ISSN: 2162-6057 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/jocb.70004 |
| OpenAlex | W4408310331 |
| Language | EN |
| Citations received | 1 |
| References cited | 86 |
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
Conceptualization · Concurrent validity · Confirmatory factor analysis · Construct (python library) · Construct validity · Convergent validity · Creativity · Developmental psychology · Discriminant validity · Exploratory factor analysis · Internal consistency · Machine learning · Psychometrics · Reliability (semiconductor) · Sample (material) · Structural equation modeling · Applied Psychology · Artificial Intelligence · Computer Science · Creativity in Education and Neuroscience · Psychology · Social Psychology · Sport Psychology and Performance · Virtual Reality Applications and Impacts
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Comparisons of creativity performance and learning effects through digital game-based creativity learning between elementary school children in rural and urban areas
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |