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Learning environments in compulsory secondary education (ESO): validation of the physical, learning, teaching and motivational scales
We present the validation of a questionnaire for compulsory secondary school students (seventh to tenth grade), designated “Educational learning environments for ESO pupils” (CEApA_ESO), for the purpose of evaluating learning environments. Although many instruments have been developed in this area,...
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Published in: | Learning environments research 2024-04, Vol.27 (1), p.53-75 |
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description | We present the validation of a questionnaire for compulsory secondary school students (seventh to tenth grade), designated “Educational learning environments for ESO pupils” (CEApA_ESO), for the purpose of evaluating learning environments. Although many instruments have been developed in this area, our work attempts to comprehensively cover some factors that most influence learning environments from the students’ perspective. Therefore, we included physical, learning, teaching and motivational elements, by adapting different already-validated scales to our intended overall approach and the Spanish context. We conducted a pilot study with 207 students from four grades (two classes per educational level). We performed descriptive and factor analyses with maximum likelihood extraction method and varimax rotation to identify factors underlying each scale. The factors extracted from each scale were used to evaluate the fit of the model, using the AMOS v.18 software for structural equation analysis, taking as reference the criteria set by Byrne (Structural equation modeling with AMOS: Basic concepts, applications, and programming, Taylor & Francis Group, 2010) and Kline (Principles and practice of structural equation modeling, The Guilford Press, 2010) (CMIN/DF between 2 and 5, CFI and IFI > 0.9, RMSEA 200). Finally, we present the factorial validity of the complete scale and analyse the internal consistency of the scale and its subscales using Cronbach’s alpha coefficient. This instrument, with adequate psychometric properties, offers educators and researchers a valid tool for assessing the learning environments of their schools. |
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Although many instruments have been developed in this area, our work attempts to comprehensively cover some factors that most influence learning environments from the students’ perspective. Therefore, we included physical, learning, teaching and motivational elements, by adapting different already-validated scales to our intended overall approach and the Spanish context. We conducted a pilot study with 207 students from four grades (two classes per educational level). We performed descriptive and factor analyses with maximum likelihood extraction method and varimax rotation to identify factors underlying each scale. The factors extracted from each scale were used to evaluate the fit of the model, using the AMOS v.18 software for structural equation analysis, taking as reference the criteria set by Byrne (Structural equation modeling with AMOS: Basic concepts, applications, and programming, Taylor & Francis Group, 2010) and Kline (Principles and practice of structural equation modeling, The Guilford Press, 2010) (CMIN/DF between 2 and 5, CFI and IFI > 0.9, RMSEA < 0.06 and HOELTER > 200). Finally, we present the factorial validity of the complete scale and analyse the internal consistency of the scale and its subscales using Cronbach’s alpha coefficient. 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The factors extracted from each scale were used to evaluate the fit of the model, using the AMOS v.18 software for structural equation analysis, taking as reference the criteria set by Byrne (Structural equation modeling with AMOS: Basic concepts, applications, and programming, Taylor & Francis Group, 2010) and Kline (Principles and practice of structural equation modeling, The Guilford Press, 2010) (CMIN/DF between 2 and 5, CFI and IFI > 0.9, RMSEA < 0.06 and HOELTER > 200). Finally, we present the factorial validity of the complete scale and analyse the internal consistency of the scale and its subscales using Cronbach’s alpha coefficient. 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subjects | Education Educational objectives Educational Technology Grade 10 Learning and Instruction Maximum Likelihood Statistics Motivation Original Paper School environment Secondary School Students Sociology of Education Structural equation modeling Structural Equation Models |
title | Learning environments in compulsory secondary education (ESO): validation of the physical, learning, teaching and motivational scales |
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