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The assumption of cause-effect relationships in ex post facto research is a widely known issue in the field of research methods in social sciences. To address this important limitation, the use of causal inference techniques has become widespread in recent years. Causal inference establishes a set of statistical procedures for drawing causal conclusions in non-experimental research. Despite its wide popularity and diffusion in the social and health sciences, its use in educational research is still marginal. Thus, this paper introduces the main causal inference techniques available to the educational researcher when observational panel data are available. After addressing the key features and potential of propensity score matching, instrumental variables, and regression discontinuity design, we present an example application of each of these techniques. We used the available databases from the PISA 2018 assessments. We included the mathematical competence as the dependent variable in all the three models implemented. Given the different characteristics of each of these techniques, the independent variable used is different in the three models applied: attendance to early childhood education in propensity score matching; student academic expectations in instrumental variables; and size of the community in which the school is located in regression discontinuity design. The article concludes by discussing the potential of this set of techniques, taking into account the needs and methodological procedures most commonly applied in educational research. [ABSTRACT FROM AUTHOR]

Professional development for teachers is fundamental in the configuration and functioning of smart schools. This paper aims to characterize professional development with the participation of compulsory secondary teachers in Spain and to detect key factors in the functioning and organization of schools associated with higher levels of ongoing teacher training. A cross-cutting non-experimental design was used to conduct a secondary analysis of data from PISA 2018 tests, including over 20,000 teachers and more than 1000 schools in Spain. Descriptive results show great variability in teachers' commitment to their professional development; this variability is not associated with the grouping of teachers by school. The decision tree model completed with data mining tools shows that intensive professional teacher development in schools is associated with a better school climate and higher levels of innovation, cooperation, taking on shared goals and responsibilities, and leadership distributed among the education community. The conclusions highlight the importance of ongoing teacher training and how this improves educational quality in schools. [ABSTRACT FROM AUTHOR]

The statistical multivariate analysis of Likert response scales, given their widespread use, is a controversial issue in the scientific community, mainly from the specification of the problem of measurement. This work aims to study various conditions of these ordinal scales affect the calculation of the product-moment and tetrachoric-polychoric correlation coefficients. For this purpose, a simulation study was applied in which 90 databases with 10 items each were generated. In the estimation of the databases, the following variables were controlled: number of response categories, symmetrical or asymmetric distributions of data, sample size and level of relationship between items. Thus, 90 matrices (10x10) were obtained which included the difference between the product-moment and tetrachoric-polychoric correlations. The graphical and variance analysis show how the product-moment correlation coefficient significantly underestimates the relationship between variables mainly when the number of response categories of the ordinal scale is small and the relationship between the variables is large. On the other hand, the statistical estimation of both coefficients is very similar when the starting relationship between pairs of variables is small and/or when the number of response options of the variables is greater than 5. The study concludes by making a recommendation to the applied researcher on the most appropriate correlation coefficient depending on the type of data available. Finally, the results are discussed from the previous studies, which reach some similar conclusions. [ABSTRACT FROM AUTHOR]

This study proposed to identify and select high and low-effectiveness schools in Baja California based on ENLACE (Quality of Educational Attainment Exams) scores and context tests. A representative sample of 85 schools and around 7,000 students was obtained for 2010 and 2011. Hierarchical linear models were applied to calculate residual scores at a school level. After adjustment of the 8 final models, which isolate the effect of significant contextual variables, statistical criteria were used to select 15 schools with high and low residual scores. The results show that the distributions of schools selected are similar in both cases to the reference population. The results show the robustness of the selection procedure used and highlight its significance in detecting good practices in high-effectiveness schools. [ABSTRACT FROM AUTHOR]

The multivariate characteristics of the IL-HUMASS scale are studied. This scale is formed by 26 Likert scale items and 4 dimensions and evaluate the information literacy self-perceived level of students. A sample of 402 subjects, all of them Spanish future teachers from secondary education, is obtained. It is implemented a multidimensional scaling technique by ALSCAL based on the distance matrix from the data. The results detected two empirical dimensions, which accounted for 95.9% of the variance. The first dimension is related to the level of familiarity with the content of the item and the second dimension is related to cognitive or instrumental aspect of the item. In the conclusions, two dimensions obtained are connected with the original scale, in relation to the four theoretical dimensions. On the other hand, the conclusions highlight the importance of considering the two dimensions obtained, in addition to the classical dimensions, in the design of assessment scales of the construct information literacy. [ABSTRACT FROM AUTHOR]

Background: Computer-based programs have been implemented from a psychosocial approach for the care of people with dementia (PwD). However, several factors may determine adherence of older PwD to this type of treatment. The aim of this paper was to identify the sociodemographic, cognitive, psychological, and physical-health determinants that helped predict adherence or not to a "GRADIOR" computerized cognitive training (CCT) program in people with mild cognitive impairment (MCI) and mild dementia. Method: This study was part of a randomized clinical trial (RCT) (ISRCTN: 15742788). However, this study will only focus on the experimental group (n = 43) included in the RCT. This group was divided into adherent people (compliance: ≥60% of the sessions and persistence in treatment up to 4 months) and non-adherent. The participants were 60–90 age and diagnosed with MCI and mild dementia. We selected from the evaluation protocol for the RCT, tests that evaluated cognitive aspects (memory and executive functioning), psychological and physical health. The CCT with GRADIOR consisted of attending 2–3 weekly sessions for 4 months with a duration of 30 min Data analysis: Phi and Biserial-point correlations, a multiple logical regression analysis was obtained to find the adherence model and U Mann–Whitney was used. Results: The adherence model was made up of the Digit Symbol and Arithmetic of Wechsler Adult Intelligence Scale (WAIS-III) and Lexical Verbal Fluency (LVF) -R tests. This model had 90% sensitivity, 50% specificity and 75% precision. The goodness-of-fit p-value of the model was 0.02. Conclusions: good executive functioning in attention, working memory (WM), phonological verbal fluency and cognitive flexibility predicted a greater probability that a person would be adherent. [ABSTRACT FROM AUTHOR]

Background: Cognitive rehabilitation is a highly individualised, non-pharmacological intervention for people with mild cognitive impairment (MCI) and dementia, which in recent years has also been developed for various IT platforms.Methods: In this study, we aim to evaluate the effectiveness of the cognitive rehabilitation software GRADIOR in a multi-centre, single-blinded randomised controlled trial with people with MCI and mild dementia. A total of 400 people with MCI and mild dementia will be randomly allocated to one of four groups. This trial will compare the cognitive rehabilitation treatment using the GRADIOR programme with a psychosocial stimulation intervention (PSS) using the ehcoBUTLER platform, with a combined treatment consisting of GRADIOR and ehcoBUTLER, and with a group receiving treatment as usual during a period of 1 year.Discussion: The outcomes of this clinical trial will be to determine any relevant changes in cognition, mood, quality of life, activities of daily living and quality of patient-carer relationship after 4 months and 1 year of intervention in a cross-sectional group comparison. Participants will be followed-up for 1 year to investigate potential long-term effects of the conducted treatments.Trial Registration: Current Controlled Trials ISRCTN, ID: 15742788 . Registered on 12 June 2017. [ABSTRACT FROM AUTHOR]