Reinforced by the Russian war, an even stronger economic, social, and political orientation towards the values of the European Union and thus also Western economic paradigms is taking place in Ukraine. This article investigates financial literacy (FL) as the knowledge and understanding of personal finance among university students in Ukraine. Individual financial decision-making will be central to the reconstruction of Ukraine and the long-term economic growth of the country. We use the principles developed by the U.S. Council for Economic Education in modelling FL. In doing so, we examine the feasibility of using a version of the U.S. American Test of Financial Literacy translated and adapted into Ukrainian. The translation and adaptation process of the 50-item test instrument is presented in the article. Significant differences in the content of FL between Ukraine and the U.S. test instrument are highlighted. At the beginning of the winter semester 2022, the Ukrainian version was administered to 68 students at three East-Ukrainian universities (Donetsk, Sumy, Kharkiv). In the article, we present findings from the initial validation of the test instrument and show from a content perspective which hurdles need to be overcome in the future for some concepts of FL.

It is known that the COVID-19 pandemic led to learning losses among students both domestically and internationally. Therefore, situational and casual factors were examined to discover and understand them so that learning loss could be reduced or recovered from. This research aimed to: (a) study learning loss situation; and (b) develop and examine the causal model of learning loss among lower secondary school students affected by the pandemic. The sample included 650 Grade 7-9 students selected by multi-stage random sampling. The data was collected using a self-developing questionnaire as a research instrument. The data was analyzed using descriptive statistics, independent samples t-test, ANOVA, and structural equation modeling (SEM) through the LISREL program. The findings were: (a) Lower secondary school students had an average academic achievement learning loss at the moderate level with the highest mean of learning loss in mathematics (M=3.012, SD=1.074), and an average learning characteristics learning loss at the medium level (M=2.824, SD=0.842). Several situational factors had a different effect depending on the school size with a statistical significance of .05.; and (b) the causal model showed the learning loss of grade 7-9 students was consistent with the empirical data (χ2=46.885, df=34, p= .069, GFI=0.991, AGFI=0.964, CFI=0.999, RMSEA=0.024, SRMR=0.014).

This study aimed to assess the geometric knowledge of student teachers from a university in the Eastern Cape province of South Africa. The study used a sample of 225 first-year student teachers who completed school mathematics baseline assessments on a computer- aided mathematics instruction (CAMI) software. The study adopted a descriptive cross-sectional research design, using quantitative data to measure student teachers’ geometry achievement level, and qualitative data to explain the challenges encountered. The results show that student teachers exhibited a low level of understanding of school-level geometry. The low achievement levels were linked to various factors, such as insufficient grasp of geometry concepts in their secondary school education, difficulty in remembering what was done years ago, low self-confidence, and lack of Information and Communications Technology (ICT) skills along with the limited time for the baseline tests. These results suggest that appropriate measures should be taken to ensure that student teachers acquire the necessary subject-matter knowledge to teach effectively in their future classrooms.

Students’ mastery goal orientation tends to decline over the course of compulsory school, especially after the transition to lower secondary school. According to stage-environment fit theory, secondary school is less accommodating to students' needs, interests, and abilities than primary school. In consequence, the perceived person-environment fit declines as well. It is assumed that a strong sense of classroom community in primary school can counteract a potential decline in both of these important individual aspects. Using data from the Swiss longitudinal research project WiSel (“Wirkungen der Selektion”; “Effects of Tracking”), we conducted a latent growth curve model (LGCM) to examine the correlation between the development of students' mastery goal orientation and the development of their person-environment fit during the transition from primary school to lower secondary school. Perceived classroom community was assumed to benefit from these developments. The results show that both mastery goal orientation and person-environment fit decrease during the transition to lower secondary school. A strong sense of classroom community in fifth grade leads to a smaller decline in both constructs. Implications for educational practice are discussed.

Digital competence entails the healthy, safe, and responsible use of digital technologies to take engage in society, to learn, work and to interact with. However, the use of digital devices is not exempt of risks. The objectives of this study were to analyze the mediating effect of fear of missing out (FoMO) on phubbing and nomophobia, and to explore the perception of the use of Internet-connected devices among 522 Spanish university students, with an average age of 27.11 years. The 80.8% are women and 68.2% study degrees related with Educational Sciences. A mixed-methods approach was used, combining bivariate correlation with structural equation modelling (SEM), and qualitative content analysis. SEM analysis revealed that FoMO had a significant effect on nomophobia and phubbing. Qualitative content analysis underlined that the time spent, problematic use, and sense of dependence were the main concerns for participants. It is emphasized that the plethora of ICT opportunities exposes individuals to risk contexts, necessitating media education to mitigate psychological and social consequences stemming from Internet risks.

One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.

Emotional empathy, mindfulness, and subjective well-being are essential to understanding human behavior and mental health among students. However, more research is needed to investigate how these constructs interplay within academic contexts. This study explored the hierarchical relationships between emotional empathy, mindfulness, and subjective well-being. The Multidimensional Emotional Empathy Scale (MDEES), The Kentucky Inventory of Mindfulness Skills (KIMS), and the Subjective Well-Being Scale (WeBs) were administered with a sample of postgraduate professional diplomas in teaching students attending Al Ain University in Abu Dhabi campus and Al Ain campus (n = 1545). The results showed that emotional empathy (positive sharing, suffering, feeling for others, and emotional contagion) positively affects physical and eudaimonic well-being. A negative correlation was found between financial and social well-being and other components of emotional empathy, such as emotional attention and responsive crying. Mindfulness significantly improves emotional empathy in components like describing, accepting without judgment, and observing. This study revealed that some components of mindfulness, such as observing and acting with awareness, decrease emotional empathy, such as suffering and feeling for others. Acting with the awareness component in mindfulness decreases positive sharing, responsive crying, and emotional contagion. Future research could explore these relationships further and examine potential cultural differences.

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

Considering the importance of the results of national and international standardized tests, which are a benchmark for measuring educational quality, the objective of this research was to model strategies to improve the results of the evaluations, specifically the Saber 11 standardized tests. These tests are applied to students who finish their Vocational Education and Training (VET) in Bogotá, Colombia. To achieve this objective, we employed the Systems Dynamics methodology for a comprehensive analysis, which is a tool that allows for the analysis and projecting of the behavior of different systems, in which anticipation by means of modeling results over time is required. The modeling was conducted in two stages: First, a causal loop diagram and a stock-and-flow diagram that linked 45 variables were designed, showing the underlying physical structure of the system. Then, five groups of alternative simulations were conducted over a time frame of six years: Reference mode, student self-efficacy rate, management rate, teaching competencies rate, and educational policy. An increase in results was observed in each scenario. The combined activity of educational stakeholders is a notably effective strategy to achieve significant improvements. The data used for these simulations came from a six-year period of standardized test results in Bogotá. This period was selected to capture both recent trends and long-term outcomes, ensuring that the model reflects current educational conditions while allowing for meaningful trend analysis.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

Integrated learning has emerged as an approach to developing critical thinking and creativity skills. This meta-analysis synthesizes the effects of integrated learning on critical thinking and creativity, drawing from experimental studies published over the past decade. This study addresses the research question: What are the impacts and factors influencing integrated learning on students' critical thinking skills and creativity compared to conventional learning over the past decade? In the database, 403 articles were obtained, which were then supplemented by seven articles from manual searches, so that there were a total of 410 articles. After a strict inclusion process, 8 articles were selected for analysis. The inter-rater reliability test using Cohen's Kappa coefficient produced a value of 0.78, which indicates a substantial level of agreement. The analysis includes data from 497 participants for critical thinking and 266 for creativity. Heterogeneity in critical thinking skill data was 96%, and in creative skills, it was 86%; then, a subgroup analysis of education level was carried out to find out where the high heterogeneity was. The results show a significant positive effect of integrated learning, with an SMD of 1.48 (p = .004) for critical thinking and 1.60 (p = .0001) for creativity. Funnel plots and Egger's regression tests indicate no risk of publication bias. In addition, this study also synthesized the causal factors of how integrated learning affects critical thinking skills and creativity. Further research is recommended to explore its long-term impact and implementation strategies in various educational settings.  

This study analyzes trends, collaborations, and research developments on augmented reality (AR) in mathematics education using a bibliometric approach. Data were collected from the Scopus database on July 31, 2024, identifying 542 documents published between 2015 and 2024. After screening, 194 journal articles were selected for analysis. Using VOSviewer, the study produced visualizations related to document types, publication trends, journal sources, research subjects, institutions, countries, keywords, and author collaborations. The results show that 88.7% of the documents are journal articles, indicating that this topic is predominantly published in scholarly journals. Publication trends reveal significant growth since 2016, peaking in 2024, reflecting increasing global interest. Education Sciences and IEEE Access are among the top journal sources. Subject-wise, social sciences and computer science are the main disciplines exploring AR in mathematics education. Chitkara University (India) and Johannes Kepler University Linz (Austria) are leading institutions, while the United States, Malaysia, and Spain contribute the most publications. Keyword analysis shows rapid growth in research using terms such as "augmented reality" and "mathematics education," emphasizing the role of immersive technology in enhancing student engagement and conceptual understanding through visual and interactive learning. Influential authors like Lavicza, Mantri, and Haas highlight the importance of global collaboration. Based on a thematic analysis of the most-cited articles, this study proposes the AI Mathematical Education Impact and Outcome Framework. In conclusion, although research on AR in mathematics education has significantly advanced, further studies are needed to evaluate its effectiveness across varied educational contexts.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

Research in mathematics education and interdisciplinarity is varied and extensive, covering multiple approaches that reflect a growing interest in this type of perspective. The objective of this study is to systematize the findings of research on interdisciplinary mathematics education published between 2019 and 2024. The review was carried out following the guidelines of the PRISMA statement, allowing us to identify 49 articles published in journals indexed in the Web of Science (WOS) and Scopus databases. Subsequently, a content analysis was carried out to identify methodological and theoretical aspects present in the studies reviewed, such as methodology employed, education level of participants, disciplines integrated with mathematics, and types of interdisciplinary tasks proposed. Additionally, four main research themes were identified: (a) understanding of interdisciplinarity; (b) pedagogical strategies for interdisciplinary development in mathematics education; (c) interdisciplinarity for the development of mathematical skills; and (d) professional development of mathematics teachers. The results reveal a sustained increase in the number of publications, which reflects a growing interest in the interdisciplinary approach in mathematics education. Finally, several challenges and opportunities are highlighted for future research, including the need to develop an interdisciplinary teacher training model, the creation of pedagogical strategies that promote greater interconnection between disciplines, and the need to carry out more studies focused on early childhood and primary education in this area.

This study presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.