scholarly journals Student Factors Affecting Latent Transition of Mathematics Achievement Measuring From Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

2016 ◽  
Vol 217 ◽  
pp. 729-737
Author(s):  
Korawan Saengtrakul ◽  
Sirichai Kanjanawasee ◽  
Nonglak Wiratchai
Politics ◽  
2019 ◽  
Vol 40 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Steven M Van Hauwaert ◽  
Christian H Schimpf ◽  
Flavio Azevedo

Recent research in the populism literature has devoted considerable efforts to the conceptualisation and examination of populism on the individual level, that is, populist attitudes. Despite rapid progress in the field, questions of adequate measurement and empirical evaluation of measures of populist attitudes remain scarce. Seeking to remedy these shortcomings, we apply a cross-national measurement model, using item response theory, to six established and two new populist indicators. Drawing on a cross-national survey (nine European countries, n = 18,368), we engage in a four-folded analysis. First, we examine the commonly used 6-item populism scale. Second, we expand the measurement with two novel items. Third, we use the improved 8-item populism scale to further refine equally comprehensive but more concise and parsimonious populist measurements. Finally, we externally validate these sub-scales and find that some of the proposed sub-scales outperform the initial 6- and 8-item scales. We conclude that existing measures of populism capture moderate populist attitudes, but face difficulties measuring more extreme levels, while the individual information of some of the populist items remains limited. Altogether, this provides several interesting routes for future research, both within and between countries.


2001 ◽  
Vol 9 (1) ◽  
pp. 5-22 ◽  
Author(s):  
Cheryl T. Beck ◽  
Robert K. Gable

The benefits of item response theory (IRT) analysis in obtaining empirical support for construct validity make it an essential step in the instrument development process. IRT analysis can result in finer construct interpretations that lead to more thorough descriptions of low- and high-scoring respondents. A critical function of IRT is its ability to determine the adequacy with which the attitude continuum underlying each dimension is assessed by the respective items in an instrument. Many nurse researchers, however, are not reaping the benefits of IRT in the development of affective instruments. The purpose of this article is to familiarize nurse researchers with this valuable approach through a description of the Facets computer program. Facets uses a one parameter (i.e., item difficulty) Rasch measurement model. Data from a survey of 525 new mothers that assessed the psychometric properties of the Postpartum Depresssion Screening Scale are used to illustrate the Facets program. It is hoped that IRT will gain increased prominence in affective instrument development as more nurse researchers become aware of computer programs such as Facets to assist in analysis.


2010 ◽  
Vol 7 (2) ◽  
Author(s):  
Alenka Hauptman

In Slovene General Matura, Mathematics is one of the compulsory subjects and it can be taken either at Basic or Higher Level of Achievement. Basic Level of Achievement is expressed by the classic five-grade scale from 1 to 5. Candidates at Higher Level of Achievement can get grades on scale from 1 to 8. Conversion of points into grades (i.e. getting points on tests and points at internal examination and then calculating those grades from the sum of points) on each Level is set independently, and we tried to find out if the same grade on each Level of Achievement corresponds to the same knowledge. Once grades are assigned they are used comparatively in selection procedures for admission to University. Both Basic and Higher Level in Mathematics include the same Part 1 of the exam. The second part of the exam (Part 2) is applied only to the Higher Level's candidates. Part 1 amounts to 80% of the total points at Basic Level, and 53.3% of total points at Higher Level. Higher Level's candidates get other 26.7% of points in Part 2. Oral part of the exam represents 20% of the grades at both Levels. In this paper we show discrepancy between knowledge within the same grades for candidates at Basic and Higher Level of Achievement on an example of a Mathematics exam from General Matura 2008. Rasch model within Item Response Theory framework was used to place item difficulties on common scale and the comparability of grade conversion on both Basic and Higher Level of Achievement was explored. The results show interesting differences in knowledge of candidates with the same grade at Basic and Higher Level of Achievement.


2021 ◽  
Vol 9 ◽  
Author(s):  
Ron D. Hays ◽  
David Hubble ◽  
Frank Jenkins ◽  
Alexa Fraser ◽  
Beryl Carew

The National Children's Study (NCS) statistics and item response theory group was tasked with promoting the quality of study measures and analysis. This paper provides an overview of six measurement and statistical considerations for the NCS: (1) Conceptual and Measurement Model; (2) Reliability; (3) Validity; (4) Measurement Invariance; (5) Interpretability of Scores; and (6) Burden of administration. The guidance was based primarily on recommendations of the International Society of Quality of Life Research.


2019 ◽  
Vol 45 (3) ◽  
pp. 339-368 ◽  
Author(s):  
Chun Wang ◽  
Steven W. Nydick

Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve model and extended the assessment of growth to multidimensional IRT models and higher order IRT models. However, there is a lack of synthetic studies that clearly evaluate the strength and limitations of different multilevel IRT models for measuring growth. This study aims to introduce the various longitudinal IRT models, including the longitudinal unidimensional IRT model, longitudinal multidimensional IRT model, and longitudinal higher order IRT model, which cover a broad range of applications in education and social science. Following a comparison of the parameterizations, identification constraints, strengths, and weaknesses of the different models, a real data example is provided to illustrate the application of different longitudinal IRT models to model students’ growth trajectories on multiple latent abilities.


2021 ◽  
Vol 20 (1) ◽  
pp. 55-62
Author(s):  
Anthony Pius Effiom

This study used Item Response Theory approach to assess Differential Item Functioning (DIF) and detect item bias in Mathematics Achievement Test (MAT). The MAT was administered to 1,751 SS2 students in public secondary schools in Cross River State. Instrumentation research design was used to develop and validate a 50-item instrument. Data were analysed using the maximum likelihood estimation technique of BILOG-MG V3 software. The result of the study revealed that 6% of the total items exhibited differential item functioning between the male and female students. Based on the analysis, the study observed that there was sex bias on some of the test items in the MAT. DIF analysis attempt at eliminating irrelevant factors and sources of bias from any kind for a test to yield valid results is among the best methods of recent. As such, test developers and policymakers are recommended to take into serious consideration and exercise care in fair test practice by dedicating effort to more unbiased test development and decision making. Examination bodies should adopt the Item Response Theory in educational testing and test developers should therefore be mindful of the test items that can cause bias in response pattern between male and female students or any sub-group of consideration. Keywords: Assessment, Differential Item Functioning, Validity, Reliability, Test Fairness, Item Bias, Item Response Theory.


2014 ◽  
Vol 31 (2) ◽  
pp. 19-34 ◽  
Author(s):  
Cees A.W. Glas

Item response theory provides a useful and theoretically well-founded framework for educational measurement. It supports such activities as the construction of measurement instruments, linking and equating measurements, and evaluation of test bias and differential item functioning. It further provides underpinnings for item banking and flexible test administration designs, such as multiple matrix sampling, flexi-level testing, and computerized adaptive testing. First, a concise introduction to the principles of IRT models is given. The models discussed pertain to dichotomous items (items that are scored as either correct or incorrect) and polytomous items (items with partial credit scoring, such as most types of openended questions and performance assessments). Second, it is shown how an IRT measurement model can be enhanced with a structural model, such as, for instance, an analysis of variance model, to relate data from achievement and ability tests to students’ background variables, such as socio-economic status, intelligence or cultural capital, to school variables, and to features of the schooling system. Two applications are presented. The first one pertains to equating and linking of assessments, and the second one to a combination of an IRT measurement model and a multilevel linear model useful in school effectiveness research.


2019 ◽  
Vol 6 (4) ◽  
pp. 205316801987956 ◽  
Author(s):  
Kyle L. Marquardt ◽  
Daniel Pemstein ◽  
Brigitte Seim ◽  
Yi-ting Wang

Experts code latent quantities for many influential political science datasets. Although scholars are aware of the importance of accounting for variation in expert reliability when aggregating such data, they have not systematically explored either the factors affecting expert reliability or the degree to which these factors influence estimates of latent concepts. Here we provide a template for examining potential correlates of expert reliability, using coder-level data for six randomly selected variables from a cross-national panel dataset. We aggregate these data with an ordinal item response theory model that parameterizes expert reliability, and regress the resulting reliability estimates on both expert demographic characteristics and measures of their coding behavior. We find little evidence of a consistent substantial relationship between most expert characteristics and reliability, and these null results extend to potentially problematic sources of bias in estimates, such as gender. The exceptions to these results are intuitive, and provide baseline guidance for expert recruitment and retention in future expert coding projects: attentive and confident experts who have contextual knowledge tend to be more reliable. Taken as a whole, these findings reinforce arguments that item response theory models are a relatively safe method for aggregating expert-coded data.


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