Search Results (1,022)

Sustainable education requires addressing the challenges posed by digital transformation, including technostress among university students. This study evaluates technostress levels in higher education through the validation of the TS4US scale and its implications for sustainable learning environments. A cross-sectional study was conducted with 328 university students from four districts in Lima, Peru, using an online survey to measure technostress. Confirmatory factor analysis (CFA) was performed to assess the psychometric properties of the TS4US scale, resulting in a refined model with two latent factors and thirteen validated items. Findings indicate that 28% of students experience high technostress levels, while 5% report very high levels, though no significant associations were found between technostress and sociodemographic variables such as campus location, employment status, gender, and academic level. The TS4US instrument had been previously validated in Chile; this study confirms its structure in a new sociocultural context, reinforcing its cross-cultural applicability. These results highlight the need for sustainable strategies to mitigate technostress in higher education, including institutional support, digital literacy programs, and policies fostering a balanced technological environment. Addressing technostress is essential for promoting sustainable education (SDG4) and enhancing student well-being (SDG3). This study directly contributes to the achievement of Sustainable Development Goals 3 (Good Health and Well-being) and 4 (Quality Education) by providing validated tools and evidence-based recommendations to promote mental health and equitable access to digital education in Latin America. Future research should explore cross-country comparisons and targeted interventions, including digital well-being initiatives and adaptive learning strategies, to ensure a resilient and sustainable academic ecosystem. Full article

The role of emotional intelligence (EI) in the academic context has been steadily established, together with its impact on students’ academic achievement, well-being, and professional success. Therefore, this study examined the development of a key EI ability—emotional understanding—throughout secondary school and explored its impact on students’ academic achievement (maternal language and mathematics) at the end of this cycle, using the Vocabulary of Emotions Test. A total of 222 students were followed over the entire 3-year secondary cycle, using a three-wave longitudinal design spanning from 10th to 12th grade. At the first wave, participants were aged between 14 and 18 years (M = 15.4; SD = 0.63), with 58.6% being female. Overall, the results of Latent Growth Curve modeling indicated that students’ emotional understanding increased over the secondary school cycle. While student’s gender predicted the emotional understanding change patterns throughout secondary school, student’s GPA in 10th grade did not. Moreover, the initial levels of ability-based emotional understanding predicted students’ achievement in maternal language at the end of the cycle. Our findings offer valuable insights into how EI skills can contribute to academic endeavors in late adolescence and will explore their impact on educational settings. Full article

Background/Objectives: Effective teamwork is crucial for minimizing human error in healthcare settings. Medical teams, typically composed of physicians and nurses, supported by auxiliary professionals, achieve better outcomes when they possess strong collaborative competencies. High-quality teamwork is associated with fewer adverse events and complications and lower mortality rates. Based on this background, the objective of this study is to analyze the perception of non-technical skills and immediate learning outcomes in interprofessional simulation settings based on E-CRM items. Methods: A cross-sectional observational study was conducted involving participants from the official postgraduate Medicine and Nursing programs at the Catholic University of Murcia (UCAM) during the 2024–2025 academic year. Four interprofessional E-CRM simulation sessions were planned, involving randomly assigned groups with proportional representation of medical and nursing students. Teams worked consistently throughout the training and participated in clinical scenarios observed via video transmission by their peers. Post-scenario debriefings followed INACSL guidelines and employed the PEARLS method. Results: Findings indicate that 48.3% of participants had no difficulty identifying the team leader, while 51.7% reported minor difficulty. Role assignment posed moderate-to-high difficulty for 24.1% of respondents. Communication, situation awareness, and early help-seeking were generally managed with ease, though mobilizing resources remained a challenge for 27.5% of participants. Conclusions: This study supports the value of interprofessional education in developing essential competencies for handling urgent, emergency, and high-complexity clinical situations. Strengthening interdisciplinary collaboration contributes to safer, more effective patient care. Full article

The paper presents the CNC manufacturing technology of the ”Double fixing fork” part as a module with educational purpose, being designed as a training support for students and other parties, facilitating the practical learning of CNC processing technology. Its technological manufacturing process involved a careful analysis of the geometry, material, tolerances, as well as functional requirements to ensure precision and reliability in operation. The material from which the part was made is a polymer material (PEHD 1000) selected both for its mechanical characteristics and for its compatibility with processing technologies. The results demonstrated high precision and adaptability, reduced execution times and the possibility of achieving complex geometries in a relatively short time. The developed module supports skill development in CNC programming and operation and is suitable for replication in other academic environments. Programming allowed for more precise control of the cutting tool trajectory and processing parameters. The paper represents an important contribution to the training of future specialists, paying special attention to the growing interdisciplinarity in manufacturing technology and the development of technical skills necessary for future engineers in the numerically controlled machinery sector. Full article

This study addresses fairness in machine learning for student academic performance prediction using the UCI Student Performance dataset. We comparatively evaluate logistic regression, Random Forest, and XGBoost, integrating the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance and 5-fold cross-validation for robust model training. A comprehensive fairness analysis is conducted, considering sensitive attributes such as gender, school type, and socioeconomic factors, including parental education (Medu and Fedu), cohabitation status (Pstatus), and family size (famsize). Using the AIF360 library, we compute the demographic parity difference (DP) and Equalized Odds Difference (EO) to assess model biases across diverse subgroups. Our results demonstrate that XGBoost achieves high predictive performance (accuracy: 0.789; F1 score: 0.803) while maintaining low bias for socioeconomic attributes, offering a balanced approach to fairness and performance. A sensitivity analysis of bias mitigation strategies further enhances the study, advancing equitable artificial intelligence in education by incorporating socially relevant factors. Full article

This paper shows that artificial intelligence is fundamentally transforming college curricula by enabling data-driven personalization, which enhances student outcomes and better aligns educational programs with evolving workforce demands. Specifically, predictive analytics, machine learning algorithms, and natural language processing were applied here, grounded in constructivist learning theory and Human–Computer Interaction principles, to evaluate student performance and identify at-risk students to propose personalized learning pathways. Results indicated that the AI-based curriculum achieved much higher course completion rates (89.72%) as well as retention (91.44%) and dropout rates (4.98%) compared to the traditional model. Sentiment analysis of learner feedback showed a more positive learning experience, while regression and ANOVA analyses proved the impact of AI on enhancing academic performance to be real. Therefore, the learning content delivery for each student was continuously improved based on individual learner characteristics and industry trends by AI-enabled recommender systems and adaptive learning models. Its advantages notwithstanding, the study emphasizes the need to address ethical concerns, ensure data privacy safeguards, and mitigate algorithmic bias before an equitable outcome can be claimed. These findings can inform institutions aspiring to adopt AI-driven models for curriculum innovation to build a more dynamic, responsive, and learner-centered educational ecosystem. Full article

Currently, the role of a university in promoting the development of rural areas has been emphasized. However, an increase in academic training can lead to a growth in rural migration due to the lack of job opportunities for university graduates. Given the scarcity of studies on the impact of higher education institutions in areas at risk of depopulation, a research study has been conducted with university students residing in Castilla y León (Spain) in order to understand their insights on the benefits that university education can bring to rural areas, as well as to comprehend the reasons that would motivate the migration of university students or even the interest of institutions in addressing the issue of depopulation. The results achieved suggest that an increase in education could help slow down this process, with the proximity of the university being a decisive factor for population settlement. Additionally, while the shortage of job opportunities would be the main cause of migration, there would also be other factors contributing to depopulation, such as lack of leisure or services, despite a will to stay. Finally, the survey respondents expressed skepticism about the institutions’ interest in addressing this problem. Full article

Academic performance has become a consolidated indicator of a nation’s educational and social equity. Consequently, increasing attention has been paid to determining the factors associated with school performance, particularly in the case of students with extreme academic outcomes. The aim of this study is to identify and compare the factors related to the level of mathematical competence of Spanish students with low and high levels of achievement, based on data from the Spanish sample of PISA 2022 (n = 30,800). The results of the multilevel quantile regression analysis reveal that the social, economic, and cultural status of the students have a significant and positive effect on both groups. Other variables, such as gender, grade repetition, and length of pre-primary education, show differentiated effects depending on the level of competence. Moreover, school-related factors, such as school location and competition among centres, exhibit opposite effects. Finally, aspects such as school ownership, average class size, and the degree of curricular autonomy only have a significant impact on the mathematical competence of low-achieving students. These findings highlight the need for differentiated educational policies that address the specific needs of each group of students. Full article

(1) Background: The development of professional identity in future educators is a dynamic and multifaceted process, shaped by personal experiences, interpersonal relationships, role models, and the values internalized across diverse learning ecologies. This identity formation is closely intertwined with academic achievement, socio-educational integration, peer interactions, and the underlying motivations for choosing a particular educational and professional trajectory. This study explores the connections between students’ educational experiences and their motivation to pursue careers in pedagogy and social education. (2) Methods: Based on 138 autoethnographic narratives written by undergraduate students enrolled in Anthropology of Education courses at two [Spanish] universities. (3) Results: The analysis reveals how reflective engagement with personal educational histories enables students to reconstruct the relational foundations of their learning paths. These reflections inform their academic and career choices, which are understood not as static decisions, but as evolving trajectories shaped by a generational context characterized by uncertainty and change. (4) Conclusions: The findings highlight how students, through their narratives, articulate both their professional aspirations and a vision of the educator as an agent of change—one who emerges in response to, and often in critique of, the educational structures and practices. Full article

This research investigates higher education admission outcomes at Hungarian universities for ethnic Hungarian minority students residing in countries within the Carpathian Basin. The region is distinguished by a variety of national policies that impact minority education. By analyzing extensive data on the availability of mother tongue education, the status of minority rights, advanced level examination performance, and types of settlement using a wide range of statistical methods, our study reveals significant cross-national differences in the distribution of admission scores and central tendencies. Compared to lower and more varied scores for students from Ukraine and Romania, ethnic Hungarian students from Serbia and Slovakia achieved high average admission scores. Performance was notably more consistent among students from EU member states compared to non-EU regions, strongly linking outcomes to the more robust implementation of minority rights and better access to mother-tongue education within the EU framework. A critical finding is the strong positive correlation (Pearson r = 0.837) between admission scores and advanced level examination results, highlighting the pivotal role of these exams for the academic progression of these minority students. The Jonckheere-Terpstra test (p < 0.05) further confirmed significant performance differences between ranked country groups, with Serbian and Slovak students generally outperforming their Ukrainian and Romanian counterparts. Counterintuitively, settlement type (urban vs. rural) exhibited a negligible relationship with admission scores (r = 0.150), explaining only 2% of score variability. This challenges common assumptions and suggests other factors specific to the Hungarian minority context are more influential. This study provides crucial insights into the complex dynamics influencing Hungarian minority students’ access to higher education, underscoring cross-country educational inequalities, and informing the development of equitable minority rights and mother-tongue education policies in Central Europe for these often-marginalized communities. Full article

In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic shortages, uneven distribution of qualified educators, and limited demographic diversity within the profession. Rather than supplanting conventional ITE models, these alternative pathways serve as complementary options, broadening access and enhancing system responsiveness to evolving societal and educational needs. The rise in non-traditional routes represents a deliberate response to the well-documented global teacher shortage, frequently examined in comparative educational research. Central to their design is a restructuring of traditional program elements, particularly duration and delivery methods, to facilitate more flexible and context-sensitive forms of teacher preparation. Such approaches often create opportunities for individuals who may be excluded from conventional pathways due to socioeconomic constraints, geographic isolation, or non-linear career trajectories. Significantly, the diversity introduced by alternative entry candidates has the potential to enrich school learning environments. These educators often bring a wide range of prior experiences, disciplinary knowledge, and cultural perspectives, contributing to more inclusive and representative teaching practices. The implications for student learning are substantial, particularly in disadvantaged communities where culturally and professionally diverse teachers may enhance engagement and academic outcomes. From a policy perspective, the development of flexible, multifaceted teacher education pathways constitutes a critical component of a sustainable workforce strategy. As demand for qualified teachers intensifies, especially in STEM disciplines and in rural, regional and remote areas, the role of alternative pathways is likely to become increasingly pivotal in achieving broader goals of equity, quality and innovation in teacher preparation. Full article

Background: University academics are often the first points of contact for students experiencing mental health problems (MHPs) because of the pre-existing relationship between academics and students. Aim: The aim of this review is to explore the experience of university academics who have supported students with MHPs. Methods: This systematic review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidance. Searches were conducted using six databases and were limited to peer-reviewed studies published in the English language between 2013 and 2023. Results: Thematic analyses identified three major themes: academics’ perceptions of mental health problems among students, the role of academics in supporting students and the academics’ perceived barriers to supporting students. Conclusions: Universities need to acknowledge the vulnerability of students’ mental health and prepare to respond appropriately. Improving the mental health literacy of university academics, and providing clarity about roles and mechanisms to support the mental health of university students will be crucial to achieve this. Full article

Effective studying is important to learn better and increase academic achievement in postsecondary education, which also holds true for the challenging content of science, technology, engineering, and mathematics (STEM). Informed by previous research, this study mainly aimed to investigate first-year STEM college students’ study habits and perceptions of the effectiveness of different study strategies, and the frequency of use of these strategies. To this end, this study employed a cross-sectional survey using the Prolific platform. The results revealed that participants use various study strategies, including more and less effective ones, generally do not study in a planned way nor believe that learning takes hard work, and also prioritize approaching deadlines. The results also showed that the participants (a) frequently use the study strategies that they think are effective, suggesting that perceived effectiveness can have an important role in students’ strategy choice, and (b) mostly use study strategies for studying only or for both studying and while learning for fun. However, the frequency of the use of strategies partially aligned with the perceived effectiveness of the strategies. Overall, these results suggest the need to further investigate the conditions under which college students find study strategies effective, which can affect their choices. Full article

This work presents the development of NOVA, an educational virtual assistant designed for the Parallel Computing course, built using a Retrieval-Augmented Generation (RAG) architecture combined with Large Language Models (LLMs). The assistant operates entirely in Spanish, supporting native-language learning and increasing accessibility for students in Latin American academic settings. It integrates vector and relational databases to provide an interactive, personalized learning experience that supports the understanding of complex technical concepts. Its core functionalities include the automatic generation of questions and answers, quizzes, and practical guides, all tailored to promote autonomous learning. NOVA was deployed in an academic setting at Universidad Politécnica Salesiana. Its modular architecture includes five components: a relational database for logging, a vector database for semantic retrieval, a FastAPI backend for managing logic, a Next.js frontend for user interaction, and an integration server for workflow automation. The system uses the GPT-4o mini model to generate context-aware, pedagogically aligned responses. To evaluate its effectiveness, a test suite of 100 academic tasks was executed—55 question-and-answer prompts, 25 practical guides, and 20 quizzes. NOVA achieved a 92% excellence rating, a 21-second average response time, and 72% retrieval coverage, confirming its potential as a reliable AI-driven tool for enhancing technical education. Full article

Considerable amounts of research have discussed “No Excuses” charter schools preparing traditionally disadvantaged students for higher education. Yet, no scholarly work has identified or investigated U.S. academically intensive charter schools (AICS) that were founded to enable students to excel academically as much as their abilities and efforts allow. Here, we offer an exploratory study of AICS, defining them, describing the lived experience of an AICS principal, presenting the first national data comparing AICS campus and student characteristics to those of other charter schools, and assessing whether, nationally, AICS succeed on their own terms, with relatively high academic achievements. The data indicate that AICS resemble other charter schools in terms of measurable campus and student characteristics. Standardized, NAEP-adjusted Z-scores reveal that AICS consistently outperform other charter and district schools in literacy and mathematics across demographic groups, with differences expanding after the COVID-19 pandemic. We end with limitations and suggestions for future research. Full article