Identifying predictors of physics item difficulty: A linear regression approach

Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To th...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Vanes Mesic, Hasnija Muratovic
Formato:	article
Lenguaje:	EN
Publicado:	American Physical Society 2011
Materias:	Special aspects of education LC8-6691 Physics QC1-999
Acceso en línea:	https://doaj.org/article/28c06b6383ce442bba33b3186f64ccfe
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:28c06b6383ce442bba33b3186f64ccfe
record_format	dspace
spelling	oai:doaj.org-article:28c06b6383ce442bba33b3186f64ccfe2021-12-02T11:51:49ZIdentifying predictors of physics item difficulty: A linear regression approach10.1103/PhysRevSTPER.7.0101101554-9178https://doaj.org/article/28c06b6383ce442bba33b3186f64ccfe2011-06-01T00:00:00Zhttp://doi.org/10.1103/PhysRevSTPER.7.010110http://doi.org/10.1103/PhysRevSTPER.7.010110https://doaj.org/toc/1554-9178Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge structures. Identified predictors point out the fundamental cognitive dimensions of student physics achievement at the end of compulsory education in Bosnia and Herzegovina, whose level of development influenced the test results within the conducted assessments.Vanes MesicHasnija MuratovicAmerican Physical SocietyarticleSpecial aspects of educationLC8-6691PhysicsQC1-999ENPhysical Review Special Topics. Physics Education Research, Vol 7, Iss 1, p 010110 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Special aspects of education LC8-6691 Physics QC1-999
spellingShingle	Special aspects of education LC8-6691 Physics QC1-999 Vanes Mesic Hasnija Muratovic Identifying predictors of physics item difficulty: A linear regression approach
description	Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge structures. Identified predictors point out the fundamental cognitive dimensions of student physics achievement at the end of compulsory education in Bosnia and Herzegovina, whose level of development influenced the test results within the conducted assessments.
format	article
author	Vanes Mesic Hasnija Muratovic
author_facet	Vanes Mesic Hasnija Muratovic
author_sort	Vanes Mesic
title	Identifying predictors of physics item difficulty: A linear regression approach
title_short	Identifying predictors of physics item difficulty: A linear regression approach
title_full	Identifying predictors of physics item difficulty: A linear regression approach
title_fullStr	Identifying predictors of physics item difficulty: A linear regression approach
title_full_unstemmed	Identifying predictors of physics item difficulty: A linear regression approach
title_sort	identifying predictors of physics item difficulty: a linear regression approach
publisher	American Physical Society
publishDate	2011
url	https://doaj.org/article/28c06b6383ce442bba33b3186f64ccfe
work_keys_str_mv	AT vanesmesic identifyingpredictorsofphysicsitemdifficultyalinearregressionapproach AT hasnijamuratovic identifyingpredictorsofphysicsitemdifficultyalinearregressionapproach
_version_	1718395092699447296

Identifying predictors of physics item difficulty: A linear regression approach

Ejemplares similares