Evaluating English Language Test Items Developed by Teachers: An Item Response Theory Approach

Evaluating students’ abilities in educational settings is crucial for assessing learning outcomes and instructional effectiveness. In Indonesia, many schools have developed local English language assessments, yet these tests often lack psychometric validation. This study aims to evaluate the quality of a teacher-developed English language test instrument using the Item Response Theory (IRT) approach. A total of 25 multiple-choice items created by the English teacher group in Muna Regency were administered to 162 students from five randomly selected schools. A descriptive quantitative method was employed with the aid of R Studio for data analysis. Initial sample adequacy was confirmed using the Kaiser-Meyer-Olkin (KMO = 0.686) and Bartlett’s Test of Sphericity (p < .001). The study applied model fit analyses for 1-PL, 2-PL, and 3-PL logistic models, with the 2-PL model emerging as the most appropriate, as 16 items demonstrated good fit. Further analysis of item characteristics under the 2-PL model revealed that only 11 items had acceptable difficulty and discrimination indices. In comparison, the remaining 14 items were either too easy, too complex, or poorly discriminating. These results indicate that a substantial portion of the test requires revision. The study highlights the importance of psychometric evaluation in teacher-made assessments and recommends capacity-building for teachers in test development and validation practices.

Authors

Publication Details

Journal
Voices of English Language Education Society
Published
2025-04-29
DOI
https://doi.org/10.29408/veles.v9i1.27644
Primary Topic
Educational Technology and Assessment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating English Language Test Items Developed by Teachers: An Item Response Theory Approach

Edi Istiyono, Widihastuti, Muhammad Istiqlal, Nur Hidayanto Pancoro Setyo Putro et al.
1 links
Voices of English Language Education Society
Educational Technology and Assessment
article

Evaluating English Language Test Items Developed by Teachers: An Item Response Theory Approach

Edi Istiyono, Widihastuti, Muhammad Istiqlal, Nur Hidayanto Pancoro Setyo Putro, Rezkilaturahmi Rezkilaturahmi
article en

Abstract

Evaluating students’ abilities in educational settings is crucial for assessing learning outcomes and instructional effectiveness. In Indonesia, many schools have developed local English language assessments, yet these tests often lack psychometric validation. This study aims to evaluate the quality of a teacher-developed English language test instrument using the Item Response Theory (IRT) approach. A total of 25 multiple-choice items created by the English teacher group in Muna Regency were administered to 162 students from five randomly selected schools. A descriptive quantitative method was employed with the aid of R Studio for data analysis. Initial sample adequacy was confirmed using the Kaiser-Meyer-Olkin (KMO = 0.686) and Bartlett’s Test of Sphericity (p < .001). The study applied model fit analyses for 1-PL, 2-PL, and 3-PL logistic models, with the 2-PL model emerging as the most appropriate, as 16 items demonstrated good fit. Further analysis of item characteristics under the 2-PL model revealed that only 11 items had acceptable difficulty and discrimination indices. In comparison, the remaining 14 items were either too easy, too complex, or poorly discriminating. These results indicate that a substantial portion of the test requires revision. The study highlights the importance of psychometric evaluation in teacher-made assessments and recommends capacity-building for teachers in test development and validation practices.

Voices of English Language Education SocietyVol. 9(1)
Openalex Percentile: Top 88%
Educational Technology and Assessment
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.