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Q-Herilearn: Assessing heritage learning in digital environments. A mixed approach with factor and IRT models

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  • Olaia Fontal
  • Alex Ibañez-Etxeberria
  • Víctor B Arias
  • Benito Arias

Abstract

The assessment of heritage learning in digital environments lacks instruments that measure it with sufficient guarantees of accuracy, validity, and reliability. This study attempts to fill this gap by developing an instrument that has shown solid metric qualities. The process of design and calibration of a scale applied to 1,454 participants between 19 and 63 years of age is presented in this article. Exploratory factor analysis (Exploratory Structural Equation Modeling ESEM) and Item Response Theory models (Graded Response Model GRM) were used. Sufficient evidence of both reliability and validity based on content and internal structure was obtained. Invariance of scores as a function of gender and age of participants has also been demonstrated. The discrimination parameters of the items have been found to be high, and the test information curves have shown that the subscales measure with sufficient precision wide ranges of the respective latent variables. The instrument presents wide possibilities of application to various areas of Heritage Education (e.g., design of programs in HE, definition and planning of teaching objectives, evaluation of programs, etc., in virtual environments).

Suggested Citation

  • Olaia Fontal & Alex Ibañez-Etxeberria & Víctor B Arias & Benito Arias, 2024. "Q-Herilearn: Assessing heritage learning in digital environments. A mixed approach with factor and IRT models," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-24, March.
    • Handle: RePEc:plo:pone00:0299733
    DOI: 10.1371/journal.pone.0299733
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