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      Design and validation of a questionnaire (LLQ) on facilitating the development of the learning to learn competence in university educators Translated title: Diseño y validación de un cuestionario (CAA) sobre la facilitación del desarrollo de la competencia aprender a aprender en el profesorado Universitario

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          Abstract

          Abstract Within the European Higher Education Area framework, educators must have acquired professional skills in order to promote the learning to learn competence, which refers to the ability to self-regulate the learning process itself, in their students. The objective of this work was to design and validate a questionnaire, the learning to learn questionnaire (LLQ), to measure the facilitative learning contexts implemented by university educators to develop the learning to learn competence. First, based on a theoretical and empirical review, 86 items belonging to 7 dimensions were defined. Next, content validity (n = 20 experts), validity based on response processes (n = 10 teachers), validity based on internal structure (n = 415 teachers), and concurrent validity were examined. Our results showed sufficient psychometric quality, reliability of scores and goodness of fit. The final version of the LLQ consisted of 4 dimensions and 39 items. This instrument can be considered a valid and reliable tool that can be quickly applied in order to identify the development of facilitative learning contexts in the evolution of the learning to learn competence. Likewise, it can also serve to detect training needs in the development of this competence in university educators.

          Translated abstract

          Resumen En el marco del Espacio Europeo de Educación Superior, el profesorado ha de contar con capacidades profesionales para impulsar en el alumnado la competencia aprender a aprender, que hace referencia a la capacidad de autorregulación del propio proceso de aprendizaje. El objetivo del presente trabajo consistió en diseñar y validar un cuestionario para medir los contextos facilitadores de aprendizaje que el profesorado universitario activa para el desarrollo de la competencia aprender a aprender, el CAA. En primer lugar, partiendo de la revisión teórica y empírica, se definieron 86 ítems. A continuación, se examinaron la validez de contenido (n = 20 expertos), la validez basada en los procesos de respuesta (n = 10 docentes), la validez basada en la estructura interna (n = 415 docentes) y la validez concurrente. Los resultados mostraron una adecuada calidad psicométrica, fiabilidad de las puntuaciones y bondad de ajuste. La versión final del CAA comprendió 4 dimensiones y 39 ítems. Este instrumento puede ser una herramienta de rápida aplicación, válida y fiable, para conocer el desarrollo de los contextos facilitadores de aprendizaje de la competencia aprender a aprender. Asimismo, puede servir para detectar necesidades de formación profesional en el desarrollo de dicha competencia.

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          A New Incremental Fit Index for General Structural Equation Models

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            Dimensionality assessment of ordered polytomous items with parallel analysis.

            Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a variable set. PA is known in different variants, which may yield different dimensionality indications. In this article, the authors considered the most appropriate PA procedure to assess the number of common factors underlying ordered polytomously scored variables. They proposed minimum rank factor analysis (MRFA) as an extraction method, rather than the currently applied principal component analysis (PCA) and principal axes factoring. A simulation study, based on data with major and minor factors, showed that all procedures consistently point at the number of major common factors. A polychoric-based PA slightly outperformed a Pearson-based PA, but convergence problems may hamper its empirical application. In empirical practice, PA-MRFA with a 95% threshold based on polychoric correlations or, in case of nonconvergence, Pearson correlations with mean thresholds appear to be a good choice for identification of the number of common factors. PA-MRFA is a common-factor-based method and performed best in the simulation experiment. PA based on PCA with a 95% threshold is second best, as this method showed good performances in the empirically relevant conditions of the simulation experiment. © 2011 American Psychological Association
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              Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide

              This paper provides a conceptual, empirical, and practical guide for estimating ordinal reliability coefficients for ordinal item response data (also referred to as Likert, Likert-type, ordered categorical, or rating scale item responses). Conventionally, reliability coefficients, such as Cronbach’s alpha, are calculated using a Pearson correlation matrix. Ordinal reliability coefficients, such as ordinal alpha, use the polychoric correlation matrix (Zumbo, Gadermann, & Zeisser, 2007). This paper presents (i) the theoretical-psychometric rationale for using an ordinal version of coefficient alpha for ordinal data; (ii) a summary of findings from a simulation study indicating that ordinal alpha more accurately estimates reliability than Cronbach's alpha when data come from items with few response options and/or show skewness; (iii) an empirical example from real data; and (iv) the procedure for calculating polychoric correlation matrices and ordinal alpha in the freely available software program R. We use ordinal alpha as a case study, but also provide the syntax for alternative reliability coefficients (such as beta or omega). Accessed 35,197 times on https://pareonline.net from January 17, 2012 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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                Author and article information

                Journal
                ap
                Anales de Psicología
                Anal. Psicol.
                Universidad de Murcia (Murcia, Murcia, Spain )
                0212-9728
                1695-2294
                September 2021
                : 37
                : 2
                : 298-310
                Affiliations
                [2] País Vasco orgnameUniversidad del País Vasco Spain
                [1] País Vasco orgnameMondragon Unibertsitatea Spain
                Article
                S0212-97282021000200011 S0212-9728(21)03700200011
                10.6018/analesps.37.2.345151
                bd782797-d23d-4b37-9447-e9aa36322446

                This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

                History
                : 05 November 2020
                : 08 October 2018
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 38, Pages: 13
                Product

                SciELO Spain

                Categories
                Developmental and Educational Psychology

                Aprender a aprender,instrumentos evaluación,competencia,educación superior,evaluación educativa,competencia profesional,Tool evaluation,Competence,Higher education,Educational assessment,Professional competence,Learning to learn

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