<p>Despite persistent criticism and mixed empirical support, the use of learning styles as a basis for personalising instruction remains prevalent in higher education. This study examined the agreement between two self-report approaches to classifying students’ learning style preferences: a brief self-classification task and the Index of Learning Styles (ILS), a structured self-report questionnaire. A total of 696 undergraduate and master’s students, most of them enrolled in online programmes, completed a brief self-classification task before responding to the ILS. Agreement beyond chance was assessed primarily using Cohen’s Kappa, while McNemar’s test was used as a secondary analysis to examine directional asymmetries in mismatches between the two measures. Across the four dimensions, disagreement rates ranged from 28.30% to 49.60%. Kappa values ranged from − 0.01 to 0.16, indicating little agreement beyond chance, whereas McNemar’s test showed no significant directional asymmetries (<i>p</i> &gt; .05). These findings suggest that a brief self-classification provides only a limited approximation to students’ ILS-based profiles, restricting its usefulness as the sole basis for instructional personalisation. At the same time, the low concordance observed raises questions about the robustness of the ILS as an individual-level diagnostic tool. Importantly, both measures relied on self-report, and the study did not assess learning outcomes or actual study behaviours. The findings should therefore be interpreted as evidence of limited agreement between two self-report approaches to learning style classification, rather than as direct evidence on the effectiveness of matching instruction to learning styles.</p>

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The illusion of personalization: An empirical study of self-reported learning styles in higher education

  • Guiomar Garrido Álvarez-Coto,
  • Quirós-Alpera Susana,
  • Luis Pedraza-Gómara,
  • Mariluz Diago-Egaña

摘要

Despite persistent criticism and mixed empirical support, the use of learning styles as a basis for personalising instruction remains prevalent in higher education. This study examined the agreement between two self-report approaches to classifying students’ learning style preferences: a brief self-classification task and the Index of Learning Styles (ILS), a structured self-report questionnaire. A total of 696 undergraduate and master’s students, most of them enrolled in online programmes, completed a brief self-classification task before responding to the ILS. Agreement beyond chance was assessed primarily using Cohen’s Kappa, while McNemar’s test was used as a secondary analysis to examine directional asymmetries in mismatches between the two measures. Across the four dimensions, disagreement rates ranged from 28.30% to 49.60%. Kappa values ranged from − 0.01 to 0.16, indicating little agreement beyond chance, whereas McNemar’s test showed no significant directional asymmetries (p > .05). These findings suggest that a brief self-classification provides only a limited approximation to students’ ILS-based profiles, restricting its usefulness as the sole basis for instructional personalisation. At the same time, the low concordance observed raises questions about the robustness of the ILS as an individual-level diagnostic tool. Importantly, both measures relied on self-report, and the study did not assess learning outcomes or actual study behaviours. The findings should therefore be interpreted as evidence of limited agreement between two self-report approaches to learning style classification, rather than as direct evidence on the effectiveness of matching instruction to learning styles.