Development of Learning Agility Measurement Instrument for Basic Education School Administrators: An Application of Latent Class Analysis for Cut-point Determination

Yada Muangkaew
Thailand
Keywords: Learning Agility, Latent Class Analysis, Measurement Instrument
Published: Dec 19, 2025

Abstract

Learning agility measurement instruments can assess and evaluate the characteristics of basic education administrators across different components, while latent class analysis serves to classify administrator characteristics within distinct groups. This research aimed to 1) develop and validate a learning agility measurement instrument for basic education school administrators, and 2) conduct latent class analysis of learning agility among basic education school administrators to establish cut-off scores. The research sample comprised 300 basic education school administrators from Thailand’s six geographical regions, selected through multistage sampling procedures. Data collection employed a learning agility measurement instrument featuring a 5-point Likert scale, encompassing 5 dimensions of learning agility across 30 items. Data analysis utilized descriptive statistics (means and standard deviations), confirmatory factor analysis, and latent class analysis. Research findings revealed that: 1) The learning agility measurement instrument demonstrated Index of Item-Objective Congruence (IOC) values ranging from 0.80 - 1.00, discriminant power coefficients from 0.257 - 0.766, and construct validity with factor loadings ranging from 0.413 - 0.873, all statistically significant at the .05 level, with overall reliability of 0.922; and 2) Latent class analysis successfully identified three distinct learning agility groups among basic education administrators: Latent Class 1 “Beginning-level Learning Agility Group” (n = 20, 6.667%), Latent Class 2 “Good-level Learning Agility Group” (n = 155, 51.667%), and Latent Class 3 “Excellent-level Learning Agility Group” (n = 125, 41.667%). The cut-off score of 18.250 effectively differentiates between Latent Classes 1 and 2, while the cut-off score of 21.335 distinguishes between Latent Classes 2 and 3 according to proficiency levels.

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Muangkaew, Y. (2025). Development of Learning Agility Measurement Instrument for Basic Education School Administrators: An Application of Latent Class Analysis for Cut-point Determination. Journal of Local Governance and Innovation, 9(3), 333–352. https://doi.org/10.65205/jlgisrru.2025.289704

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