Elyanti Elyanti
State University of Malang

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Diagnosing Students’ Vector Concept Understanding Through Rasch Model Analysis Elyanti Elyanti; Khusaini Khusaini; Lia Yuliati
Jurnal Pendidikan Fisika dan Teknologi (JPFT) Vol 12 No 1 (2026): January-June
Publisher : Department of Physics Education, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpft.v12i1.11558

Abstract

Accurate measurement of students’ conceptual understanding of vectors requires assessment instruments with sound psychometric properties. This study aims to examine the validity, reliability, and item difficulty of a vector concept understanding instrument for high school students using Rasch model analysis. The study employed a descriptive quantitative design involving 30 high school students who had studied vector material. Data were collected through a 25-item multiple-choice test and analyzed using the Rasch model via Winsteps version 3.68.0. The results indicated that 15 items met the Rasch model fit criteria and could be retained as valid items, while 10 items required revision. The instrument demonstrated good internal consistency with a Cronbach’s alpha of 0.83, item reliability of 0.81, and test-retest reliability of 0.75. Item difficulty analysis revealed a variation in difficulty levels capable of effectively distinguishing students’ abilities. Items regarding vector components were found to be the most difficult concept for students to understand, whereas the concept of vector direction was relatively easier to grasp. These findings indicate that Rasch analysis is not only effective for evaluating instrument quality but also useful for identifying students’ misconceptions and learning difficulties regarding vector material. Pedagogically, these research results can help teachers design more targeted learning strategies, particularly in strengthening students’ understanding of vector components through visual and representational approaches. This study contributes to the development of diagnostic-based physics assessment and supports the use of the Rasch model as a robust approach in refining physics learning evaluation instruments.