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Highlights: [•] Teaching in the EHEA requires varied teaching methodologies. [•] Attitudes towards ICTs are a determining factor in their integration in teaching. [•] A one-dimensional scale was designed for evaluation of attitudes towards ICT use. [•] The scale designed has adequate psychometric characteristics. [Copyright &y& Elsevier]

• Decision trees enable the detection of factors that predict school effectiveness. • The predictive model is more accurate for low effectiveness schools. • A single negative factor at school escalates the risk of low effectiveness. With the main goal of identifying the process factors associated with school effectiveness in secondary education, this work presents an innovative methodological proposal. Based on secondary data from the Spanish sample of PISA 2015, high- and low-effectiveness schools were selected by analysing the residuals of the school level (level 2) in multilevel models. Subsequently, decision trees were used to identify the process variables with a greater predictive power for the identification of high- and low-effectiveness schools. While the hierarchical linear models obtained show inter-school variance scores greater than 10%, decision trees achieve a precision greater than 90%. We conclude by analysing the suitability of using decision trees in data originating from large-scale assessments, and examining the obtained factors associated with school effectiveness. [ABSTRACT FROM AUTHOR]

• The studied variables affect achievement, with some gender and country differences. • Male achievement tends to be more affected by the variables in Finland and the UK. • All correlations yielded significant results except the feeling of belonging in Spain. • Parent support, belonging and motivation reduce gender differences in achievement. The aim of this study is to define the moderating effect of gender on the relationship between academic achievement and some explanatory factors, according to the PISA 2015 results in the United Kingdom, Finland and Spain. Based on an exploratory correlational study, multivariate statistical techniques were applied with moderate regression analysis in these countries, which were considered relevant examples for understanding the current situation. The results obtained suggest that gender is a variable that, at a general level, moderates the relationship between the explanatory factors studied, with the exception of anxiety, and academic achievement, mainly in the Finnish student population. Ultimately, the relevance of gender as a moderating variable for the improvement of student achievement and educational quality is verified. [ABSTRACT FROM AUTHOR]