Exploring differential bundle functioning in mathematics by gender: the effect of hierarchical modelling

Ong, Yoke Mooi; Williams, Julian; Lamprianou, Iasonas

doi:10.1080/1743727x.2012.675263

Cited by 6 publications

(3 citation statements)

References 32 publications

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“…Ignoring clustering in nested data structures impacts the statistical tests performed and the potential conclusions that could be reached (Dorman 2008;Ong, Williams, and Lamprianou 2013). Ignoring clustering in nested data structures impacts the statistical tests performed and the potential conclusions that could be reached (Dorman 2008;Ong, Williams, and Lamprianou 2013).…”

Section: Methodsmentioning

confidence: 99%

A multilevel analysis of late entry in Nigeria

Delprato

Sabatés

2014

International Journal of Research & Method in Education

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This paper explores how factors operating at the state and community levels are associated with the prevalence of late school enrolment in Nigeria. We investigate the following three research themes. First, whether late entry varies across states and across communities and how much of this variation can be explained by the composition of communities and states. Second, whether community wealth and state wealth are stronger predictors of late entry than household wealth. Third, whether wealth has different effects on the probability of late school entry in different states and in different communities within states. Using the 2010 Nigeria Education Data Survey, and a three-level multilevel logit model, we show that a substantial proportion of the variation in late school entry is explained by community-and state-level factors. We further find that children living in specific communities in Nigeria may face a double disadvantage in terms of on-time school enrolment. In these communities, not only is there a large proportion of children entering school late, but also household wealth has strong effects on the probability that a child is sent to school on on time. These communities could be targeted for educational interventions aimed at promoting on-time school enrolment.

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Section: Methodsmentioning

confidence: 99%

A multilevel analysis of late entry in Nigeria

Delprato

Sabatés

2014

International Journal of Research & Method in Education

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“…However, at this stage this and other DIF evidence was not strong enough in itself to force the deletion of items; for one thing the gender balance in the participating subjects varies and this complicates interpretation. Indeed, in general the difficulty with such interpretations in developing scales is to decide if the DIF is due to 'real gender differences' that we might want to study or to bias in the expression of the items themselves (Ong, Williams, & Lamprianou, 2012). We therefore look for clusters of DIF and for some reasonable explanatione.g.…”

Section: Validation Resultsmentioning

confidence: 99%

Validating constructs of learners’ academic self-efficacy for measuring learning gain

Pampaka

Swain

Jones

et al. 2018

Higher Education Pedagogies

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Following previous research which showed the significance of learners' self-efficacy and dispositions towards progression in school and university transition, we developed and validated similar measures for use in modelling undergraduate students' Learning Gain (LG). We validated three dimensions of confidence using data from a sample of (mainly first year) undergraduate students in various departments of one major UK University which we call: 'confidence in learning through. . .' a) 'traditional university transmission pedagogy' (e.g. in lectures), b) 'social means' (e.g. working in teams), and c) 'problem solving, reflection and critical thinking'. We explored psychometric properties of these measures and then focus on their association with other perceptions of students' experience in HE and other measures of attainment. We then used these academic self-efficacy variables to inform (regression) models of LG. Finally, we discuss the prospects for measurements and modelling of LG involving dispositions and affect as well as attainment. ARTICLE HISTORY

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“…As such, methods that can reveal whether feature-related DIF results can be expected to generalize outside of the test setting are needed. The importance of distinguishing the test-level and population-level results was earlier discussed by Ong et al (2013).…”

Section: Introductionmentioning

confidence: 99%

Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features

Bolsinova¹,

Tijmstra

Rutkowski³

et al. 2023

Journal of Educational and Behavioral Statistics

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Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test whether conclusions about the item-feature effects generalize outside of the considered set of items. This article addresses both of these limitations, by generalizing profile analysis to work under the two-parameter logistic model and by proposing a permutation test that allows for generalizable conclusions about item-feature effects. The developed methods are evaluated in a simulation study and illustrated using Programme for International Student Assessment 2015 Science data.

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Exploring differential bundle functioning in mathematics by gender: the effect of hierarchical modelling

Cited by 6 publications

References 32 publications

A multilevel analysis of late entry in Nigeria

A multilevel analysis of late entry in Nigeria

Validating constructs of learners’ academic self-efficacy for measuring learning gain

Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features

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