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

Abstract 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 mod...

Description complète

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Peter M. C. Harrison, Tom Collins, Daniel Müllensiefen
Format:	article
Langue:	EN
Publié:	Nature Portfolio 2017
Sujets:	Medicine R Science Q
Accès en ligne:	https://doaj.org/article/3e936ebbd19341c8b02a32c5fb303c6f
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

id	oai:doaj.org-article:3e936ebbd19341c8b02a32c5fb303c6f
record_format	dspace
spelling	oai:doaj.org-article:3e936ebbd19341c8b02a32c5fb303c6f2021-12-02T15:05:37ZApplying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation10.1038/s41598-017-03586-z2045-2322https://doaj.org/article/3e936ebbd19341c8b02a32c5fb303c6f2017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03586-zhttps://doaj.org/toc/2045-2322Abstract 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.Peter M. C. HarrisonTom CollinsDaniel MüllensiefenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-18 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Peter M. C. Harrison Tom Collins Daniel Müllensiefen Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
description	Abstract 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.
format	article
author	Peter M. C. Harrison Tom Collins Daniel Müllensiefen
author_facet	Peter M. C. Harrison Tom Collins Daniel Müllensiefen
author_sort	Peter M. C. Harrison
title	Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
title_short	Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
title_full	Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
title_fullStr	Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
title_full_unstemmed	Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation
title_sort	applying modern psychometric techniques to melodic discrimination testing: item response theory, computerised adaptive testing, and automatic item generation
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/3e936ebbd19341c8b02a32c5fb303c6f
work_keys_str_mv	AT petermcharrison applyingmodernpsychometrictechniquestomelodicdiscriminationtestingitemresponsetheorycomputerisedadaptivetestingandautomaticitemgeneration AT tomcollins applyingmodernpsychometrictechniquestomelodicdiscriminationtestingitemresponsetheorycomputerisedadaptivetestingandautomaticitemgeneration AT danielmullensiefen applyingmodernpsychometrictechniquestomelodicdiscriminationtestingitemresponsetheorycomputerisedadaptivetestingandautomaticitemgeneration
_version_	1718388759666360320

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

Documents similaires