What is creative in childhood writing? Computationally measured linguistic characteristics explain much of the variance in subjective human-rated creativity scores

The present study investigated the extent to which linguistic features of children's stories (analysed using automated techniques), predicted human-rated Creative Expressiveness and Logic scores (both assessed with the Consensual Assessment Technique). A sample of 160 children (Mage = 8.99 years, SD = 0.3) wrote stories based on three pictures. Eleven linguistic characteristics were measured: Length, Grammar, Originality, Controlled Lexical Diversity, Uncontrolled Lexical Diversity, Divergent Semantic Integration (DSI), Referential Cohesion, Narrativity, Syntactic Simplicity, Word Concreteness and Deep Cohesion. The results showed that 51 % of the variance in Creative Expressiveness was explained by Length, DSI, Originality, Grammar, and Controlled Lexical Diversity ( sr 2 = 0.01 to 0.14). In comparison, 28 % of the variance in Logic scores was accounted for by DSI, Grammar, Controlled Lexical Diversity, Syntactic Simplicity, and Narrativity ( sr 2 = 0.01 to 0.06). These findings offer insights for educational practices by identifying the linguistic characteristics relevant to children's creative writing as opposed to logical narration. • A study on human-rated creativity and computationally measured linguistic characteristics in childhood stories. • Five linguistic characteristics (length, grammar, originality, lexical diversity, DSI) predicted creativity scores. • Story length and DSI scores (ability to connect divergent ideas) were the strongest predictors of creativity scores. • To enhance creative content in storytelling, children could be guided to use diverse language. • Automated measures can complement human creativity ratings but not replace them entirely.

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Publication Details

Journal
Learning and Individual Differences
Published
2025-01-10
DOI
https://doi.org/10.1016/j.lindif.2025.102626
Citations
2
Primary Topic
Creativity in Education and Neuroscience
Type
article
Field-Weighted Citation Impact
4.24

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article

What is creative in childhood writing? Computationally measured linguistic characteristics explain much of the variance in subjective human-rated creativity scores

Birsu Kandemirci, Dan R. Johnson, Bonamy R. Oliver, Roger E. Beaty et al.
2 citations
Learning and Individual Differences
Creativity in Education and Neuroscience
4.24
article

What is creative in childhood writing? Computationally measured linguistic characteristics explain much of the variance in subjective human-rated creativity scores

Birsu Kandemirci, Dan R. Johnson, Bonamy R. Oliver, Roger E. Beaty, Yulia Kovas, Teemu Toivainen
article en
2 citations

Abstract

The present study investigated the extent to which linguistic features of children's stories (analysed using automated techniques), predicted human-rated Creative Expressiveness and Logic scores (both assessed with the Consensual Assessment Technique). A sample of 160 children (Mage = 8.99 years, SD = 0.3) wrote stories based on three pictures. Eleven linguistic characteristics were measured: Length, Grammar, Originality, Controlled Lexical Diversity, Uncontrolled Lexical Diversity, Divergent Semantic Integration (DSI), Referential Cohesion, Narrativity, Syntactic Simplicity, Word Concreteness and Deep Cohesion. The results showed that 51 % of the variance in Creative Expressiveness was explained by Length, DSI, Originality, Grammar, and Controlled Lexical Diversity ( sr 2 = 0.01 to 0.14). In comparison, 28 % of the variance in Logic scores was accounted for by DSI, Grammar, Controlled Lexical Diversity, Syntactic Simplicity, and Narrativity ( sr 2 = 0.01 to 0.06). These findings offer insights for educational practices by identifying the linguistic characteristics relevant to children's creative writing as opposed to logical narration. • A study on human-rated creativity and computationally measured linguistic characteristics in childhood stories. • Five linguistic characteristics (length, grammar, originality, lexical diversity, DSI) predicted creativity scores. • Story length and DSI scores (ability to connect divergent ideas) were the strongest predictors of creativity scores. • To enhance creative content in storytelling, children could be guided to use diverse language. • Automated measures can complement human creativity ratings but not replace them entirely.

Learning and Individual DifferencesVol. 118
Pennsylvania State University (US), Washington and Lee University (US), University of Manchester (GB), University College London (GB), Goldsmiths University of London (GB)
National Science Foundation, National Institutes of Health, Medical Research Council
Quality Education
Openalex Percentile: Top 9%
Creativity in Education and Neuroscience
4.24
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