Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation

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Harrison, Peter M. C.; Collins, Tom and Müllensiefen, Daniel. 2017. Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation. Scientific Reports, 7, 3618. ISSN 2045-2322 [Article]

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Official URL: https://doi.org/10.1038/s41598-017-03586-z

Abstract or Description

Modern psychometric theory provides many useful tools for ability testing, such as item response theory, computerised adaptive testing, and automatic item generation. However, these techniques have yet to be integrated into mainstream psychological practice. This is unfortunate, because modern psychometric techniques can bring many benefits, including sophisticated reliability measures, improved construct validity, avoidance of exposure effects, and improved efficiency. In the present research we therefore use these techniques to develop a new test of a well-studied psychological capacity: melodic discrimination, the ability to detect differences between melodies. We calibrate and validate this test in a series of studies. Studies 1 and 2 respectively calibrate and validate an initial test version, while Studies 3 and 4 calibrate and validate an updated test version incorporating additional easy items. The results support the new test’s viability, with evidence for strong reliability and construct validity. We discuss how these modern psychometric techniques may also be profitably applied to other areas of music psychology and psychological science in general.

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Article

Identification Number (DOI):

https://doi.org/10.1038/s41598-017-03586-z

Additional Information:

Part of this research appeared in a Master’s dissertation by the first author, who was partly supported by the EPSRC and AHRC Centre for Doctoral Training in Media and Arts Technology (EP/L01632X/1). The second author was partially supported by an Early Career Research Fellowship from De Montfort University. The authors wish to thank the Psychometrics Centre at the University of Cambridge, the International Cognitive Ability Resource (ICAR) project, and Przemyslaw Lis for advice on the psychometric and technical aspects of this project. They would also like to thank Amy Fancourt, Francesco Caprini, Iris Mencke, and the staff and pupils of Queen Anne’s School, Caversham for their assistance in data collection.

Author Contributions:
Study design: D.M., P.H. Design of materials and experimental procedure: P.H., T.C. Data collection and processing: P.H. Data analysis: P.H., D.M. Writing the manuscript: P.H. Editing the manuscript: P.H., D.M., T.C.