Assessing Associative Distance Among Ideas Elicited by Tests of Divergent Thinking

发散思维 结合属性 创造力 心理学 流利 文字联想 认知心理学 独创性 联想(心理学) 可靠性(半导体) 收敛性思维 灵活性(工程) WordNet公司 认知 创造性思维 社会心理学 人工智能 计算机科学 统计 数学教育 数学 功率(物理) 神经科学 物理 纯数学 心理治疗师 量子力学 精神分析
作者
Selçuk Acar,Mark A. Runco
出处
期刊:Creativity Research Journal [Taylor & Francis]
卷期号:26 (2): 229-238 被引量:192
标识
DOI:10.1080/10400419.2014.901095
摘要

Tests of divergent thinking represent the most commonly used assessment of creative potential. Typically they are scored for total ideational output (fluency), ideational originality, and, sometimes, ideational flexibility. That scoring system provides little information about the underlying process and about the associations among ideas. It also does not really capture the key principle of divergent thinking, namely that ideas may be found when cognition explores new (divergent) directions. The investigation reported here used 3 independent semantic networks, each computerized and previously validated, to quantify the distance between responses (ideas) to several tests of divergent thinking. These sources were WordNet (WN), Word Associations Network (WAN), and IdeaFisher (IF). Statistical analyses indicated that remote and close associations can be reliably measured when different sources of associative strength are used. Inter-item reliability (alpha coefficients) of what these networks had identified as remote associations were higher than those from close associations. Inter-item reliability values were higher in the WAN and IF, which provided shorter lists than the WN. Therefore, longer associative lists did not necessarily produce better indices of remote and close associations. Also, scores from a measure of creative attitudes and values were significantly correlated with remote, but not with close, associations across all 3 networks. This finding is very important because it shows that people with a higher tendency of creative attitudes and values, as measured by divergent thinking tests, are more likely to make remote associations rather than close associations. Limitations and future directions are discussed.
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