<p>A well-defined creative climate is crucial for fostering creative engagement and problem-solving in design education. However, structured and validated indices for assessing creative climate in group-based design instruction remain underdeveloped. This study develops and validates an index for measuring creative climate using a systematic quantitative approach. Drawing on Ekvall's (<CitationRef CitationID="CR17">1996</CitationRef>) Creative Climate Questionnaire (CCQ) and Alencar &amp; Fleith's (<CitationRef CitationID="CR3">2004</CitationRef>) inventory of teaching practices that favor creativity in higher education, an initial 17-factor model was constructed and refined through item-to-total correlation analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) using structural equation modeling (SEM). Data were collected from 141 fourth-year design students, with 120 valid responses included in the analysis. The results support an eight-factor creative climate framework demonstrating strong reliability and construct validity. Further analysis indicates that several creative climate constructs vary significantly across instructors, highlighting the influence of instructional approaches on students' perceptions of creative climate. This validated index provides educators and researchers with a practical tool for assessing and enhancing creative learning environments in design education. Future research should examine its applicability across disciplines and cultural contexts.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Developing and validating an index for assessing creative climate in group-based learning environments in design education

  • Chiaoi Huang

摘要

A well-defined creative climate is crucial for fostering creative engagement and problem-solving in design education. However, structured and validated indices for assessing creative climate in group-based design instruction remain underdeveloped. This study develops and validates an index for measuring creative climate using a systematic quantitative approach. Drawing on Ekvall's (1996) Creative Climate Questionnaire (CCQ) and Alencar & Fleith's (2004) inventory of teaching practices that favor creativity in higher education, an initial 17-factor model was constructed and refined through item-to-total correlation analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) using structural equation modeling (SEM). Data were collected from 141 fourth-year design students, with 120 valid responses included in the analysis. The results support an eight-factor creative climate framework demonstrating strong reliability and construct validity. Further analysis indicates that several creative climate constructs vary significantly across instructors, highlighting the influence of instructional approaches on students' perceptions of creative climate. This validated index provides educators and researchers with a practical tool for assessing and enhancing creative learning environments in design education. Future research should examine its applicability across disciplines and cultural contexts.