Assessment of psychometric properties for Raven Advanced Progressive Matrices in measuring intellectual quotient (IQ) using Rasch model

Mohd Effendi Ewan Mohd Matore, Maat Siti Mistima, Mohd Affandi Haryanti, Suziyani Mohamad, Ahmad Zamri Khairani

Research output: Contribution to journalArticle

Abstract

Background and Objective: Items evaluation towards intellectual quotient (IQ) instruments is rarely focused on technical students for local contexts. Empirical evidence is essential for the purpose of assessing the quality of cognitive testing items. This study aimed at evaluating the quality of multiple choices of Ravens Advanced Progressive Matrices (RAPM) items in measuring IQ using Rasch model analysis in the polytechnics context. Methodology: The research design used a survey design with the fully quantitative approach. The total of 150 students from one of the polytechnics in Perak was selected by convenience sampling technique. Results: The results showed that 23 items have been dropped from 36 items of RAPM and 13 items found to fulfil Rasch model assumptions such as item fit, unidimensionality, local independence, item polarity, gender differential item functioning with evaluating the aspects of reliability and separation index. Conclusion: The items assessed are applicable for Malaysian polytechnics in order to measure IQ for the technical workers in future.

Original languageEnglish
Pages (from-to)393-400
Number of pages8
JournalAsian Journal of Scientific Research
Volume11
Issue number3
DOIs
Publication statusPublished - 1 Jan 2018

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Keywords

  • Intellectual quotient (IQ)
  • Psychometric
  • Rasch model
  • Ravens advanced progressive matrices

ASJC Scopus subject areas

  • General

Cite this

Assessment of psychometric properties for Raven Advanced Progressive Matrices in measuring intellectual quotient (IQ) using Rasch model. / Matore, Mohd Effendi Ewan Mohd; Siti Mistima, Maat; Haryanti, Mohd Affandi; Mohamad, Suziyani; Khairani, Ahmad Zamri.

In: Asian Journal of Scientific Research, Vol. 11, No. 3, 01.01.2018, p. 393-400.

Research output: Contribution to journalArticle

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