Differential socioemotional and educational profiles in early childhood and primary education students in a lockdown situation.

Recent lockdown situations have highlighted social relationship deprivation of schoolchildren and the need to develop the teaching-learning process in informal contexts. The aim of this study was to analyze differential socioemotional and educational profiles in Early Childhood and Primary Education students using variables relating to academic performance during the COVID-19 pandemic. Correlational, descriptive, and inferential statistical analyses were performed that yielded differential explanatory models depending on the stage of education. The results reveal statistically significant differences in all the variables except for family-school relationship. In the linear regression models, the most statistically significant variable for school performance in both stages was family-school relationship. However, differences were found between both profiles: emotional impact for Early Childhood Education students and social impact for Primary Education students. Lastly, leisure activities at home were included as an explanatory variable only in the Primary Education regression model. The final conclusions highlight the need to attend to the evolutionary characteristics of students in each stage to improve school performance in similar lockdown situations.

Socio-Economic and Cultural Context in the Development of Early Mathematical Competencies: A Comparative Study of Specific Educational Contexts in Chile and Spain.

This research presents the findings of a comparative study of mathematical competence among 130 students (M = 54.08 months; SD = 2.57) from vulnerable school contexts in Chile and the Spanish public school system. The study analyses a set of general and specific domain precursors for which evidence of socioeconomic background exists. Using multivariate regression and discriminant analysis techniques, we calculated similarities and differences between groups by comparing these precursors. Significant differences were found between the Spanish and Chilean groups (p < .05); however, no differences were observed in non-symbolic comparison and receptive vocabulary. Possible reasons for the existence and extent of these differences are discussed in terms of socio-cultural and educational contexts.

Contributions of the psychology of mathematical cognition in early childhood education using apps.

Educational interventions are necessary to develop mathematical competence at early ages and prevent widespread mathematics learning failure in the education system as indicated by the results of European reports. Numerous studies agree that domain-specific predictors related to mathematics are symbolic and non-symbolic magnitude comparison, as well as, number line estimation. The goal of this study was to design 4 digital learning app games to train specific cognitive bases of mathematical learning in order to create resources and promote the use of these technologies in the educational community and to promote effective scientific transfer and increase the research visibility. This study involved 193 preschoolers aged 57-79 months. A quasi-experimental design was carried out with 3 groups created after scores were obtained in a standardised mathematical competence assessment test, i.e., low-performance group (N = 49), high-performance group (N = 21), and control group (N = 123). The results show that training with the 4 digital learning app games focusing on magnitude, subitizing, number facts, and estimation tasks improved the numerical skills of the experimental groups, compared to the control group. The implications of the study were, on the one hand, provided verified technological tools for teaching early mathematical competence. On the other hand, this study supports other studies on the importance of cognitive precursors in mathematics performance.

Individual differences in general and specific cognitive precursors in early mathematical learning / Diferencias individuales en los precursores cognitivos generales y específicos del aprendizaje matemático temprano

Background: The acquisition of mathematical abilities is associated not only with several academic aptitudes but also with the development of particular cognitive skills. This study analysed the role of the general and specific domain precursors of informal mathematical thinking. Method: A total of 109 4-year-old children (M = 59.30 months; SD = 3.56) participated in the study, in which the participants’ informal math and cognitive variables were assessed. A stepwise regression model was calculated. Results: The complex inferential model evidenced the role of the three general-domain variables analysed, in addition to numerical estimation as a specific-domain variable. 48.5% of participants’ variability in informal mathematical thinking, evaluated with the TEMA-3 test, was explained by three of the general domain precursors: working memory, processing speed and receptive vocabulary; as well as by estimation, a specific-domain precursor. The model showed a higher explanatory statistical weight for boys (48.9%) than girls (37.5%). Conclusions: The model indicated that working memory and processing speed were the main predictors of informal mathematical thinking at the age of four. A joint remedial or preventative intervention, taking into account predictors of the specific and general domains, could be the optimal option to improve achievement in mathematics

Antecedentes: la adquisición de habilidades matemáticas está asociada no solo con aptitudes académicas, sino también con el desarrollo de habilidades cognitivas específicas. Este estudio analizó el papel de los precursores del dominio general y específico en el pensamiento matemático informal. Método: un total de 109 niños de 4 años participaron en el estudio (M= 59.30; SD= 3.56). Se evaluaron el pensamiento matemático informal con la prueba TEMA-3, y diferentes variables cognitivas. Resultados: tras la realización de un análisis de regresión por pasos, el modelo inferencial evidenció que el 48,5% de la variabilidad de los participantes en el pensamiento matemático informal fue explicado por la memoria de trabajo, velocidad de procesamiento y vocabulario receptivo, así como por la estimación. El modelo indicó que la memoria de trabajo y la velocidad de procesamiento fueron los principales predictores del pensamiento matemático informal a la edad de cuatro años. Mostró también un mayor peso estadístico explicativo para los niños (48,9%) que para las niñas (37,5%). Conclusiones: los datos sugieren que una intervención conjunta correctiva o preventiva, teniendo en cuenta los factores predictivos de los dominios específicos y generales, podría ser la opción óptima para mejorar el rendimiento en matemáticas en niños en riesgo de tener dificultades en esta materia

Individual differences in general and specific cognitive precursors in early mathematical learning.

BACKGROUND: The acquisition of mathematical abilities is associated not only with several academic aptitudes but also with the development of particular cognitive skills. This study analysed the role of the general and specific domain precursors of informal mathematical thinking. METHOD: A total of 109 4-year-old children (M = 59.30 months; SD = 3.56) participated in the study, in which the participants' informal math and cognitive variables were assessed. A stepwise regression model was calculated. RESULTS: The complex inferential model evidenced the role of the three general-domain variables analysed, in addition to numerical estimation as a specific-domain variable. 48.5% of participants' variability in informal mathematical thinking, evaluated with the TEMA-3 test, was explained by three of the general domain precursors: working memory, processing speed and receptive vocabulary; as well as by estimation, a specific-domain precursor. The model showed a higher explanatory statistical weight for boys (48.9%) than girls (37.5%). CONCLUSIONS: The model indicated that working memory and processing speed were the main predictors of informal mathematical thinking at the age of four. A joint remedial or preventative intervention, taking into account predictors of the specific and general domains, could be the optimal option to improve achievement in mathematics.

The Open Algorithm Based on Numbers (ABN) Method: An Effective Instructional Approach to Domain-Specific Precursors of Arithmetic Development.

This article presents the results of a comparative study regarding the impact and contribution of two instructional approaches to formal and informal mathematical reasoning with two groups of Spanish students, aged four and five. Data indicated that for both age groups, children under the ABN method [Open Algorithm Based on Numbers (ABN)] (n = 147) achieved better results than the group under the CBC approach (Closed Algorithms Based on Ciphers) (n = 82), which is the widespread approach in Spanish schools to teach formal and informal mathematical reasoning. Furthermore, the comparative analyses showed that the effect is higher in the group of students who received more instruction on skills considered domain-specific predictors of later arithmetic performance. Statistically significant differences were found in 9 of the 10 dimensions evaluated by TEMA-3 (p < 0.01), as well as on estimation tasks in the number-line for the 5-year-old-group. However, the 4-year-old group only presented significant results in calculation and concepts tasks about informal mathematical reasoning. We discuss that these differences arise by differential exposure to specific number-sense tasks, since the groups proved to be equivalent in terms of receptive vocabulary, processing speed, and working memory. The educational consequences of these results were also analyzed.

Coming Together: R&D and Children's Entertainment Company in Designing APPs for Learning Early Math.

Information and Communication Technologies (ICT) have an increasing influence on the way we interact, learn, and live. The increase in teaching and learning methodologies that are mediated by ICT in the field of education and in the domestic settings encourages the design of new effective technological tools, supported by scientific research and development to improve student learning. The challenge psychology is facing in the education field is to promote those technologies and make them available to the education community. Technologies also would produce attractive items for users and realistic commercial issues for businesses. This also allows an effective transfer for scientific work, providing visibility to Research and Development. In this context, the main aim of the article is to describe the process to get an agreement between Babyradio (a children's entertainment company: https://babyradio.es/) and our research team, starting a collaborative work between two groups of people (Babyradio's technical designer and Psychologist-Engineers software designer), in order to create several educative applications (APPs) in the field of early mathematics cognition. The institutional framework of the relationship of the R&D project and a children's entertainment company is described. The article also focuses on experience in Psychology, Technological Innovation, and Entrepreneurship. In considering the efficiency of the agreement, we present different APPs designed for tablets and smartphone devices, adapted to the different operating systems (IOS, Android, Windows). APPs are designed to instill the cognitive fundamentals associated with early math learning for students aged 4 to 7 years. The study developed after this babyradio-university enterprise agreement contributes to the development of mathematics skills in children, aged 4-7 years, so that they can successfully meet the mathematics school requirements; it also contributes to encouraging a more positive attitude toward mathematics. This study also suggests how the education system and software and educational content developers' companies would manage verified instructional APPs, with a more realistic commercial perspective.

Predictive model for early math skills based on structural equations.

Early math skills are determined by higher cognitive processes that are particularly important for acquiring and developing skills during a child's early education. Such processes could be a critical target for identifying students at risk for math learning difficulties. Few studies have considered the use of a structural equation method to rationalize these relations. Participating in this study were 207 preschool students ages 59 to 72 months, 108 boys and 99 girls. Performance with respect to early math skills, early literacy, general intelligence, working memory, and short-term memory was assessed. A structural equation model explaining 64.3% of the variance in early math skills was applied. Early literacy exhibited the highest statistical significance (ß = 0.443, p < 0.05), followed by intelligence (ß = 0.286, p < 0.05), working memory (ß = 0.220, p < 0.05), and short-term memory (ß = 0.213, p < 0.05). Correlations between the independent variables were also significant (p < 0.05). According to the results, cognitive variables should be included in remedial intervention programs.

Explanatory model of emotional-cognitive variables in school mathematics performance: a longitudinal study in primary school.

This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students' level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of 4 years as a variable. The sampled students were initially assessed by means of an Early Numeracy Test, and, subsequently, they were administered a Likert-type scale to measure their predisposition toward mathematics (EPMAT) and a basic test of logical intelligence. The results of these tests were used to analyse the interaction of all the aforementioned variables by means of a structural equations model. This combined interaction model was able to predict 64.3% of the variability of observed performance. Preschool students' performance in EMCs was a strong predictor for achievement in mathematics for students between 8 and 11 years of age. Therefore, this paper highlights the importance of EMCs and the modulating role of predisposition toward mathematics. Also, this paper discusses the educational role of these findings, as well as possible ways to improve negative predispositions toward mathematical tasks in the school domain.