Search Results (11)

This work reports and discusses the results of a secondary analysis on statistical data regarding the phenomenon of school dropout in Italy starting from primary school. The research was conducted as part of Next GenerationEU funded by the European Union. The aim is to highlight any territorial differences in the phenomenon at the European, national, and local level. The data were collected from reliable sources (Eurostat, National Institute of Statistics, Ministry of Education and Merit, Regional School Office of Campania) and are updated to the latest year available. In line with the goals of PRIN, the aim was to photograph the national situation starting from the results of the INVALSI tests recorded in primary and lower secondary schools. The results of the analysis show that the levels of school dropout in Italy are among the highest in EU countries and, within our country, the well-known gap between the North and South remains, with the latter in a worse position. An econometric model is presented that demonstrates a cause–effect relationship that goes from the results of the primary cycle to those of the secondary cycle. This outcome attests to the importance of strengthening and increasing the skills necessary to prevent the possible conditions of school dropout starting from primary school. Full article

Immigration processes and the possible marginalization of ethnic minorities in the receiving countries are essential issues in contemporary societies. Prejudice and discrimination can be critical obstacles to immigrants’ integration into the host country and can severely affect their well-being and mental health. This theoretical and conceptual overview aims to highlight the critical social–psychological processes underlying attitudes toward immigrants. First, it tackles the social psychological roots of social prejudice by focusing on the role of individual (ideological, motivational, and cultural) factors and categorization processes. Second, it examines how contextual factors such as intergroup perceptions and structural relations can lead to high levels of prejudice and discrimination towards immigrants. This review highlights how prejudice against immigrants can be driven by various factors at the individual and contextual level, suggesting that programs aimed at facilitating harmonious relations in contemporary multi-ethnic societies should consider such different determinants. Accordingly, the conclusion discusses possible interventions that can promote better relations between the majority and immigrant groups and counteract the negative impact of discrimination. Full article

The use of fuzzy logic to assess students’ knowledge is not a completely new concept. However, despite dealing with a large quantity of data, traditional statistical methods have typically been the preferred approach. Many studies have argued that machine learning methods could offer a viable alternative for analyzing big data. Therefore, this study presents findings from a Random Forest (RF) regression analysis to understand the influence of demographic factors on students’ achievements, i.e., teacher-given grades, students’ outcomes on the national assessment, and fuzzy grades, which were obtained as a combination of the two. RF analysis showed that demographic factors have limited predictive power for teacher-assigned grades, unlike INVALSI scores and fuzzy grades. School type, macroregion, and ESCS are influential predictors, whereas gender and origin have a lesser impact. The study highlights regional and socio-economic disparities, influencing both student outcomes and fuzzy grades, underscoring the need for equitable education. Unexpectedly, gender’s impact on achievements is minor, possibly due to gender-focused policies. Although the study acknowledges limitations, its integration of fuzzy logic and machine learning sets the foundation for future research and policy recommendations, advocating for diversified assessment approaches and data-driven policymaking. Full article

Several factors affect students’ mathematics grades and standardized test results. These include the gender of the students, their socio-economic status, the type of school they attend, and their geographic region. In this work, we analyze which of these factors affect assessments of students based on fuzzy logic, using a sample of 29,371 Italian high school students from the 2018/19 academic year. To combine grades assigned by teachers and the students’ results in the INVALSI standardized tests, a hybrid grade was created using fuzzy logic, since it is the most suitable method for analyzing qualitative data, such as teacher-given grades. These grades are analyzed with a hierarchical linear regression. The results show that (1) boys have higher hybrid grades than girls; (2) students with higher socio-economic status achieve higher grades; (3) students from scientific lyceums have the highest grades, whereas students from vocational schools have the lowest; and (4) students from Northern Italy have higher grades than students from Southern Italy. The findings suggest that legislators should investigate appropriate ways to reach equity in assessment and sustainable learning. Without proper interventions, disparities between students might lead to unfairness in students’ future career and study opportunities. Full article

Although the idea of evaluating students’ mathematical knowledge with fuzzy logic is not new in the literature, few studies have explored the possibility of assessing students’ mathematical knowledge by combining teacher-assigned grades (i.e., school grades) with students’ achievements on standardized tests (e.g., national assessments). Thus, the present study aims to investigate the use of fuzzy logic to generate a novel assessment model, which combines teacher-assigned mathematics grades with students’ results on the Italian National Assessment of Mathematical Knowledge (INVALSI). We expanded the findings from previous works by considering a larger sample, which included more than 90,000 students attending grades 8, 10, and 13. The results showed that the tested model led to a lower assessment score compared to the traditional grading method based on teacher’s evaluation. Additionally, the use of fuzzy logic across the examined school levels yielded similar results, suggesting that the model is adequate among different educational levels. Full article

Background: This study aimed to investigate differences in adolescents’ social relationships with classmates of diverse gender, socioeconomic status, immigrant background, and academic achievement. Methods: A population of 10th-grade students (N = 406,783; males = 50.3%; M_age = 15.57 years, SD_age = 0.75) completed the Classmates Social Isolation Questionnaire (CSIQ), an instrument specifically designed to measure two distinct but correlated types of peer relationships in class: peer acceptance and peer friendship. To obtain reliable comparisons across diverse adolescent characteristics, the measurement invariance of the CSIQ was established by means of CFAs and then latent mean differences tests were performed. Results: Immigrant background, academic achievement, and socioeconomic status all proved to be important factors influencing relationships with classmates, while being a male or a female was less relevant. Being a first-generation immigrant adolescent appears to be the foremost risk factor for being less accepted by classmates, while having a low academic achievement is the greatest hindrance for having friends in the group of classmates, a finding that diverges from previous studies. Conclusions: This population study suggests that adolescent characteristics (especially immigrant background, socioeconomic status, and academic achievement) seem to affect social relationships with classmates. Full article

The analysis of what human capital (HC) is has a long history and culminates in the acknowledgment that HC and its growth are very important for both cognitive education (cognitive skills (CSs)) and personal life (noncognitive skills (NCSs)) and that CSs and NCSs have a strong reciprocal relationship, as studies by Heckman demonstrated. The present contribution (following Heckman’s approach) analyzed the relationship between CSs and NCSs in a sample of middle school students in the Autonomous Province of Trento. The second goal of the research was to verify whether educational teaching behaviors improved students’ personalities. Aside from the use of administrative data (INVALSI data, 2015 and 2018), one survey was administered in the 2018–2019 schooling year to verify the relationship between NCSs and CSs. Moreover, we sought to determine whether education teaching behavior improved the students’ personalities (1522 students in 25 schools) and whether programs could enhance NCSs. Methodological tools for the analysis involved the generalized least squares approach to answer the first question and a difference-in-differences model for the second. The main results showed that the levels of NCSs affected the ability to learn and improve CSs; a challenging teaching approach, especially if accompanied by programs improving its quality, had positive results. Finally, the research suggested that a wider, national-based survey following students from primary to secondary school would allow for a greater understanding of the dynamics of CSs and NCSs. Full article

Assessing student mathematical knowledge is an important factor in the mathematics learning process because students obtain important feedback to improve their knowledge and learning. Despite the importance of student assessment, several researchers have shown that student grades comprise noncognitive and metacognitive factors and teachers’ prejudices and beliefs. One method to obtain a more objective view of student mathematical knowledge is through standardized assessments. In this paper, we analyze two methods of assessing student mathematical knowledge by considering their written and oral grades and achievements on the Italian National Assessment of Knowledge (INVALSI). The final grade was produced using the fuzzy logic inference system. It was tested on a sample of 2279 Grade 13 Italian high school students, who had both an oral and written grade in mathematics and who took the INVALSI assessment in the school year 2020–2021. Both tested fuzzy-logic-based assessment methods lowered the mean grades. Full article

Background: Motivation to engage in physical activity plays a central role in ensuring the health of the population. The present study investigated the psychometric properties and validity in Italy of the Behavioral Regulation in Exercise Questionnaire (BREQ-3), a widely used instrument for assessing individuals’ motivation to exercise based on self-determination theory (SDT). Methods: A large sample (N = 2222; females = 55.4%; M_age = 36.4 years, SD_age = 13.9, min = 20, max = 69) of young people, and middle aged and older adults completed the Italian translation of the BREQ-3, also indicating their intentions to exercise in the following weeks. Results: Confirmatory factor analyses showed that the posited six-factor structure of the BREQ-3 fitted the data well (CFI = 0.96; RMSEA = 0.05; SRMR = 0.04) and provided evidence for full measurement invariance across gender and different age groups. The construct validity of the BREQ-3 was supported by the latent correlations among the subscales, which were consistent with the quasi-simplex pattern theorized by SDT. The overall level of self-determination and the intention to exercise were positively correlated, providing evidence for the criterion validity of the scale. Conclusions: The Italian version of the BREQ-3 has proved to be a reliable and valid instrument for measuring the behavioral regulation of exercise in individuals with different demographic characteristics. Full article

This study builds on a research-practitioner partnership embedded within an education for sustainable development (ESD) project and aims to explore the major potential challenges (i.e., disciplinary boundaries set by subject specialization, especially in secondary education) and success factors (i.e., teacher co-learning experiences in ESD) associated with differences in teachers’ professional action competence (PACesd) in a sample of 557 in-service teachers in primary and secondary schools in Flanders, Belgium. The study employed a recently validated PACesd measurement instrument and involved quantitative data analysis in a structural equation modelling framework. The results show that primary education teachers tend to report higher PACesd levels compared to their peers in secondary education. Moreover, regardless of educational level, gender and teaching experience, all teachers participating in a working group or a learning community in ESD are more likely to show higher levels of PACesd. Implications of the findings, limitations and directions for future research are discussed. Full article

In testing situations, automated test assembly (ATA) is used to assemble single or multiple test forms that share the same psychometric characteristics, given a set of specific constraints, by means of specific solvers. However, in complex situations, which are typical of large-scale assessments, ATA models may be infeasible due to the large number of decision variables and constraints involved in the problem. The purpose of this paper is to formalize a standard procedure and two different strategies—namely, additive and subtractive—for overcoming practical ATA concerns with large-scale assessments and to show their effectiveness in two case studies. The MAXIMIN and MINIMAX ATA methods are used to assemble multiple test forms based on item response theory models for binary data. The main results show that the additive strategy is able to identify the specific constraints that make the model infeasible, while the subtractive strategy is a faster but less accurate process, which may not always be optimal. Overall, the procedures are able to produce parallel test forms with similar measurement precision and contents, and they minimize the number of items shared among the test forms. Further research could be done to investigate the properties of the proposed approaches under more complex testing conditions, such as multi-stage testing, and to blend the proposed approaches in order to obtain the solution that satisfies the largest set of constraints. Full article