Item Response Theory for Creativity Measurement

Item-response theory (IRT) is a significant advancement in measurement theory, yet it is often overlooked in curricula, textbooks, and popular statistical software. This element provides an overview of classical test theory (CTT) and its limitations in creativity measurement, introduces IRT and its core concepts, offers a practical strategic approach to IRT modeling, showcases example applications from creativity research, and proposes ideas for future work to enhance IRT's benefits in creativity research and its connections with other frameworks.

Format: Paperback / softback
Length: 102 pages
Publication date: 14 March 2024
Publisher: Cambridge University Press

Item-response theory (IRT) is a significant advancement in measurement theory, yet it is often overlooked in curricula, textbooks, and popular statistical software. This element, designed for creativity and innovation researchers, researchers-in-training, and anyone interested in measuring individual creativity, aims to provide an overview of classical test theory (CTT) and its limitations in creativity measurement situations. It also introduces IRT and its core concepts, highlighting the relationship between CTT models and IRT. The practical strategic approach to IRT modeling is discussed, along with example applications from creativity research and the associated advantages. Additionally, ideas for future work are proposed to enhance how IRT can benefit creativity research, as well as its connections with other popular frameworks.

IRT is a powerful tool for measuring individual creativity, as it allows for the assessment of complex and nuanced responses. By utilizing item-response models, researchers can examine the relationship between an individual's responses and the underlying construct being measured, such as creativity.

One of the key advantages of IRT is its ability to handle item discrimination, which is a common issue in creativity measurement. Item discrimination refers to the ability of an item to differentiate between individuals who possess the target trait or characteristic and those who do not. IRT models can account for item discrimination by using item parameters, such as difficulty, discrimination, and item characteristic curves, to estimate the ability of an item to measure the target construct.

Another advantage of IRT is its ability to handle item bias, which can occur when items are designed to favor certain individuals or groups. Item bias can introduce errors in measurement and can lead to inaccurate estimates of the true population mean. IRT models can account for item bias by using item response theory (IRT) models, which allow for the estimation of item parameters based on the observed responses of individuals.

IRT also provides a flexible framework for modeling complex response patterns, such as polytomous responses (multiple-choice items) and rating scales. Polytomous responses allow individuals to provide more nuanced responses, while rating scales allow individuals to rate the extent to which they agree or disagree with a statement or item. IRT models can handle these complex response patterns by using latent variable models, which allow for the estimation of multiple latent variables that represent different aspects of the target construct.

In conclusion, item-response theory (IRT) is a valuable tool for measuring individual creativity. It provides a robust framework for handling item discrimination, item bias, and complex response patterns, allowing for more accurate and reliable estimates of the true population mean. IRT is widely used in psychology, education, and business, and its applications are expanding rapidly in other fields, such as art and music. As research in creativity continues to evolve, IRT will likely play an increasingly important role in advancing our understanding of this complex and important construct.

ISBN-13: 9781009239004