BRIDGING THE GAP: METHODOLOGICAL VALIDATION OF A RASCH-BASED DIAGNOSTIC TOOL FOR MATH KNOWLEDGE

Many students transitioning from secondary school to higher education face significant challenges with foundational mathematics, impacting academic success. This study investigates the one-parameter Rasch model within Item Response Theory (IRT) as a diagnostic tool to assess mathematical skills and identify weaknesses in this population. The aim of this paper is twofold: first, to conduct a literature review on standardized assessment instruments; second, to exemplify how a Rasch-based diagnostic instrument can assess mathematical proficiency. The literature review examined psychometrics and IRT, highlighting the Rasch model’s potential for analysing student responses. Microdata from the 2023 Brazilian National High School Exam (ENEM) for 160 students were used. Student responses to 45 mathematics items were analysed using the Rasch model implemented in R. The analysis included estimating item difficulty, visualising the distribution of student abilities, and comparing Rasch-generated scores with official ENEM scores derived from a three-parameter IRT model. The results suggest that the Rasch model provides valuable insights into mathematical proficiency, even with smaller sample sizes. These findings have implications for developing targeted interventions and support programmes, as identifying weaknesses allows institutions to improve support programme effectiveness and enhance student success and retention.

Authors

Institutions

Publication Details

Journal
Cadernos de Educação Tecnologia e Sociedade
Published
2026-10-31
DOI
https://doi.org/10.14571/brajets.v19.n3.875-903
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BRIDGING THE GAP: METHODOLOGICAL VALIDATION OF A RASCH-BASED DIAGNOSTIC TOOL FOR MATH KNOWLEDGE

Fábio Roberto Chavarette, Jorge Manuel Vieira Capela, Marisa Veiga Capela, Henrique Antônio Mendonça Faria
Cadernos de Educação Tecnologia e Sociedade
Psychometric Methodologies and Testing
article

BRIDGING THE GAP: METHODOLOGICAL VALIDATION OF A RASCH-BASED DIAGNOSTIC TOOL FOR MATH KNOWLEDGE

Fábio Roberto Chavarette, Jorge Manuel Vieira Capela, Marisa Veiga Capela, Henrique Antônio Mendonça Faria
article en

Abstract

Many students transitioning from secondary school to higher education face significant challenges with foundational mathematics, impacting academic success. This study investigates the one-parameter Rasch model within Item Response Theory (IRT) as a diagnostic tool to assess mathematical skills and identify weaknesses in this population. The aim of this paper is twofold: first, to conduct a literature review on standardized assessment instruments; second, to exemplify how a Rasch-based diagnostic instrument can assess mathematical proficiency. The literature review examined psychometrics and IRT, highlighting the Rasch model’s potential for analysing student responses. Microdata from the 2023 Brazilian National High School Exam (ENEM) for 160 students were used. Student responses to 45 mathematics items were analysed using the Rasch model implemented in R. The analysis included estimating item difficulty, visualising the distribution of student abilities, and comparing Rasch-generated scores with official ENEM scores derived from a three-parameter IRT model. The results suggest that the Rasch model provides valuable insights into mathematical proficiency, even with smaller sample sizes. These findings have implications for developing targeted interventions and support programmes, as identifying weaknesses allows institutions to improve support programme effectiveness and enhance student success and retention.

Cadernos de Educação Tecnologia e SociedadeVol. 19(3)
Universidade Estadual Paulista (Unesp) (BR)
Openalex Percentile: Top 9%
Psychometric Methodologies and Testing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon