Psychometric Properties of the Pre-Literacy Test: Assessing Literacy Readiness Skills

This study examined the psychometric properties of the Pre-Literacy Test, developed to measure the literacy readiness skills of children who have completed preschool education. Using a quantitative, multistage design, the study was conducted with a total of 5966 children aged 6-7 who were about to enter elementary school in the 2024-2025 academic year (N<sub>1</sub> = 1911; N<sub>2</sub> = 1644; N<sub>3</sub> = 2411). Exploratory Factor Analysis revealed a three-factor structure-Reading Skills, Writing Skills (Dictation), and Writing Skills (Copying)-which explained 82.38% of the total variance. Confirmatory Factor Analysis demonstrated that this structure showed an acceptable model fit (CFI = 0.997, TLI = 0.997, SRMR = 0.030, RMSEA = 0.111). The internal consistency coefficients (α = 0.891-0.962; ω = 0.912-0.983) and convergent validity values (AVE = 0.867-0.949) of the PLT were found to be high. Discriminant validity was confirmed according to the Fornell-Larcker criterion, and measurement invariance across gender was supported through Multigroup Confirmatory Factor Analysis. Item analyses indicated that most test items were of moderate difficulty (mean difficulty = 0.409) and high discrimination (mean discrimination = 0.516). In conclusion, the PLT was determined to be a psychometrically robust, valid, and reliable instrument for assessing basic literacy skills prior to elementary school entry. These findings suggest that the test can be confidently used in early literacy research and school readiness assessments.

Authors

Institutions

Publication Details

Journal
Journal of Intelligence
Published
2025-12-02
DOI
https://doi.org/10.3390/jintelligence13120155
Citations
1
Primary Topic
Reading and Literacy Development
Type
article
Field-Weighted Citation Impact
3.44
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Psychometric Properties of the Pre-Literacy Test: Assessing Literacy Readiness Skills

Muhammet Baştuğ
1 citations
Journal of Intelligence
Reading and Literacy Development
3.44
article

Psychometric Properties of the Pre-Literacy Test: Assessing Literacy Readiness Skills

Muhammet Baştuğ
article en
1 citations

Abstract

This study examined the psychometric properties of the Pre-Literacy Test, developed to measure the literacy readiness skills of children who have completed preschool education. Using a quantitative, multistage design, the study was conducted with a total of 5966 children aged 6-7 who were about to enter elementary school in the 2024-2025 academic year (N<sub>1</sub> = 1911; N<sub>2</sub> = 1644; N<sub>3</sub> = 2411). Exploratory Factor Analysis revealed a three-factor structure-Reading Skills, Writing Skills (Dictation), and Writing Skills (Copying)-which explained 82.38% of the total variance. Confirmatory Factor Analysis demonstrated that this structure showed an acceptable model fit (CFI = 0.997, TLI = 0.997, SRMR = 0.030, RMSEA = 0.111). The internal consistency coefficients (α = 0.891-0.962; ω = 0.912-0.983) and convergent validity values (AVE = 0.867-0.949) of the PLT were found to be high. Discriminant validity was confirmed according to the Fornell-Larcker criterion, and measurement invariance across gender was supported through Multigroup Confirmatory Factor Analysis. Item analyses indicated that most test items were of moderate difficulty (mean difficulty = 0.409) and high discrimination (mean discrimination = 0.516). In conclusion, the PLT was determined to be a psychometrically robust, valid, and reliable instrument for assessing basic literacy skills prior to elementary school entry. These findings suggest that the test can be confidently used in early literacy research and school readiness assessments.

Journal of IntelligenceVol. 13(12)
Yıldız Technical University (TR)
Openalex Percentile: Top 6%
Reading and Literacy Development
3.44
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.