Rasch & Modern Test Theory Quest

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TEST THEORY BASICS

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Sumaia Zaid

Malaysia

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Rasch & Modern Test Theory Quest


Froggy Jumps Rasch & Modern Test Theory QuestVersion en ligne TEST THEORY BASICS par Sumaia Zaid 1 What are the four building blocks in Mark Wilson’s framework for test theory? a Test administration, scoring rubric, test length, item bias b Construct maps, item design, outcome space, measurement model 2 Which model is central to modern test theory in the Rasch family? a Two-parameter logistic model b Rasch Model c 3-parameter logistic model 3 What type of data are included in the outcome space of Rasch analysis? a Ordinal data ( Stevens’ types ) b Nominal data c Interval data 4 What concept measures the precision of person estimates in Rasch analysis? a Kuder-Richardson reliability b Cronbach’s alpha c Standard error of measurement 5 Which statistic indicates item fit in Rasch models? a Infit and Outfit statistics b Chi-square statistic c Guttman index 6 What does the Wright Map primarily visualize? a Person ability and item difficulty together b Test time and item length c Distractor effectiveness 7 What primarily causes differential item functioning (DIF)? a Uniform response patterns across groups b Item functioning differs across groups after controlling ability c Random guessing by all test takers 8 Why is unidimensionality important in Rasch analysis? a One underlying trait should explain responses b Multiple dimensions improve fit c Dimensionality does not affect Rasch 9 Which technique checks for local dependence and dimensionality in Rasch using residuals? a Factor rotation b Cluster analysis c PCA of residuals 10 Which Rasch model is used for polytomous (multiple-category) items like Likert scales? a Binary Rasch Model b Rating Scale Model (RSM) c Partial Credit Model (PCM) 11 What does unidimensionality mean in Rasch analysis? a Items measure multiple traits. b All items measure a single latent trait. c There is no latent trait involved. 12 What is the purpose of PCA of residuals in Rasch? a To detect secondary dimensions beyond the main trait. b To estimate person ability. c To compute raw test scores. 13 How is local dependence between items indicated? a Zero residual correlation. b High residual correlation after accounting for ability. c Low item difficulty. 14 Why does Rasch fail if multiple dimensions exist? a It requires multidimensional scaling. b It violates unidimensionality, leading to misfit. c It becomes too easy to fit data. 15 What are Item Characteristic Curves? a Graphs of item timing. b Curves showing the probability of a correct response by ability. c Curves of sampling distributions. 16 What does the Test Information Function describe? a Precision of measurement across the trait continuum. b Item-level difficulty only. c Number of test items. 17 How can multidimensionality be mitigated in Rasch? a Increasing test length without review. b Ignoring misfitting items. c Careful test construction and checking item fit. 18 What does a high residual dependence imply for test data? a Perfect unidimensional fit. b Independence of items and persons. c Local dependence between items. 19 What consequence arises from local dependence on Rasch fit? a No impact on results. b Better model fit. c Inflated information and biased estimates.

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Rasch & Modern Test Theory Quest

Froggy Jumps

À propos de cette activité

Créé par

Téléchargez la version pour jouer sur papier

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Rasch & Modern Test Theory QuestVersion en ligne

par Sumaia Zaid

What are the four building blocks in Mark Wilson’s framework for test theory?

Which model is central to modern test theory in the Rasch family?

What type of data are included in the outcome space of Rasch analysis?

What concept measures the precision of person estimates in Rasch analysis?

Which statistic indicates item fit in Rasch models?

What does the Wright Map primarily visualize?

What primarily causes differential item functioning (DIF)?

Why is unidimensionality important in Rasch analysis?

Which technique checks for local dependence and dimensionality in Rasch using residuals?

Which Rasch model is used for polytomous (multiple-category) items like Likert scales?

What does unidimensionality mean in Rasch analysis?

What is the purpose of PCA of residuals in Rasch?

How is local dependence between items indicated?

Why does Rasch fail if multiple dimensions exist?

What are Item Characteristic Curves?

What does the Test Information Function describe?

How can multidimensionality be mitigated in Rasch?

What does a high residual dependence imply for test data?

What consequence arises from local dependence on Rasch fit?