Search Results (1,127)

Background/Objectives: Cognitive dysfunction, or “brain fog”, following COVID-19 viral infection is strongly associated with diminished work capacity which disproportionality affects working-age adults. This study examined an existing method of cognitive rehabilitation training applied to adults struggling with workplace functioning and self-efficacy due to post-COVID-19 brain fog. Methods: Nine adults with post-COVID-19 cognitive dysfunction participated in this single arm pilot trial of a severity-adaptive cognitive training program. The participants completed 45–90 h of clinician-delivered cognitive training exercises delivered remotely in 60- to 90-min sessions, two or three times per week. The primary outcome measure was overall workplace self-efficacy with subskills of perceived workplace functioning, perception of cognitive functioning, and perception of home functioning assessed through pre and post surveys and qualitative interviews. The secondary outcome was cognitive function operationalized by an IQ score administered before and after the intervention. Results: The participants achieved significant improvements in workplace self-efficacy and cognition following cognitive training. The main qualitative themes of self-reported improvements were in executive function, health and energy, daily living activities, productivity, and socioemotional functioning. A cross-case synthesis of pre-intervention struggles, and post-intervention improvements revealed subthemes at work or school in cognitive processing and comprehension, memory, executive function, fatigue, emotional distress, confidence in work or academics, and work/academic performance impairment. As a group, the mean gain in IQ score was 10.5 points. Conclusions: This study adds to the growing body of literature examining the possibility of using cognitive rehabilitation for post-COVID-19 cognitive dysfunction impacting workplace self-efficacy and work functioning. Full article

In social science degree programs, where Statistics is not a core subject, students often experience anxiety and negative attitudes that influence their engagement and may hinder academic performance. This study examines the role of positive emotions in the teaching of Probability Calculus and Inferential Statistics in Business Administration and Management studies, analyzing their relationship with students’ engagement in Problem-Based Learning (PBL). The research is framed as an exploratory single-campus case study conducted with a modestly sized sample of undergraduate students from a single Faculty. Moving beyond traditional approaches that view emotions merely as outcomes of learning, our model assumes that positive emotions, both prior to and following the PBL experience, shape students’ perceptions of its usefulness, their collaborative behaviors, and their communication with instructors. Using Structural Equation Modeling (SEM) and Cluster Analysis, the findings show that positive emotions are a key driver of students’ predisposition toward and engagement with PBL, indicating that cultivating a supportive emotional climate enhances participation and deepens the understanding of statistical concepts. These results suggest that fostering emotional engagement is essential not only for improving motivation and academic outcomes in Statistics but also for developing transversal and sustainability-related competencies such as critical thinking, collaboration, communication, and evidence-based decision-making. The study contributes to current discussions on sustainable and inclusive teaching practices by highlighting the importance of integrating socio-emotional dimensions into active learning methodologies in higher education. Full article

Academic anxiety is a negative emotional state experienced by learners of Chinese as a foreign language (CFL) during their Chinese language learning process. To explore the mediating mechanisms of positive and negative emotions and academic self-efficacy between teacher support and academic anxiety, a questionnaire survey was conducted among 1047 CFL learners, and a structural equation model was established to test the mediating effects. The study found that teacher support helps alleviate academic anxiety among CFL learners; teacher support exerts a certain inhibitory effect on learners’ academic anxiety. However, teacher support does not directly reduce academic anxiety but indirectly influences it through the independent mediating roles of self-efficacy and academic emotions, as well as through the chain mediating effect of both. Based on these findings, the paper provides recommendations for maintaining positive emotions, enhancing self-efficacy, implementing tailored teacher support, and constructing comprehensive motivational mechanisms for CFL learners. Full article

As in other cultures, university students in Nepal struggle with significant academic pressure, which often leads to academic anxiety and depression. The current study aims to expand awareness of the presence, prevalence, and impact of student academic anxiety and depression among Nepalese university students as well as to test an emerging approach to universal screening to identify learners’ need profiles to promote targeted intervention supports. Participants included 547 Nepalese college students who completed the Academic Anxiety Scale (AAS) and the University Student Depression Inventory (USDI). Confirmatory factor analysis (CFA) was conducted to evaluate the validity of the Nepalese versions. Finally, comparative analyses using an archival dataset of students from the United States explored consistencies across cultural contexts. Nepalese translations of both scales demonstrated high reliability and validity and identified similarities in patterns of expressed academic anxiety and depression across cultures. Furthermore, four profiles of need were generated based on levels of anxiety, depression, and academic motivation. The results supported clear recommendations for tiered interventions in specific domains of emotion regulation. This initial large-scale study of academic anxiety and depression in a Nepalese university population provided confirmation that the models of anxiety and depression as well as incidence levels were consistent with existing research from other contexts. Moreover, the results provided strong confirmation that universal screening with simplified self-report measures can identify clear patterns of need among students, which can be aligned with targeted tiered interventions to support student thriving. Full article

The rapid development of intelligent learning guidance systems has created a favorable environment for personalized learning. By accurately predicting students’ future performance, education can be tailored and teaching strategies optimized. However, traditional prediction algorithms seldom account for highly imbalanced datasets in basic education, overlook temporal factors, and lack further interpretability of the prediction results. To address these shortcomings, we propose Temporal Variational Autoencoder-Generative Adversarial Network (TVAE-GAN), a temporal variational autoencoder-generative adversarial network model aimed at providing early warnings for high-risk students in basic education, with in-depth interpretability analysis of the prediction results to suit the unique context of basic education. TVAE-GAN extracts features from real samples and introduces a Long Short-Term Memory (LSTM) network to capture dynamic features in time series, helping the model better understand temporal dependencies in the data, remember the sequential causal information of students’ online learning, and achieve better data generation performance. Using these features, the generative model generates new samples, and the discriminator model evaluates their quality, producing outputs that closely resemble real samples through training. The effectiveness of the TVAE-GAN model is validated on a collected online basic education dataset while also advancing the timing of interventions in predictions. The performance differences between the proposed method and classic resampling methods, as well as their impact in the educational field, are analyzed, highlighting that misclassification increases teacher workload and affects students’ emotions. Key influencing factors are identified using a decision-tree surrogate model, providing teachers with multidimensional references for academic assessment. Full article

University students face sustained academic, employment, and social pressures. Campus pathways, as central linear spaces in daily routines, hold significant potential to influence well-being, yet existing research has largely overlooked how their environmental characteristics affect multidimensional health. Using Shenyang Jianzhu University as a case, this study identified frequently used pathways through GPS tracking and surveys, and quantitatively analyzed how environmental features affect walking willingness, emotional experience, and social interaction. By comparing high- and low-benefit groups, the key environmental thresholds were identified to inform health-oriented design. Beyond verifying some established understandings (e.g., daily commuting paths prioritize efficiency, while leisure paths focus on experiential quality), the study further revealed several mechanisms through quantitative analysis. For example, “road accessibility”—an indicator of convenience—showed a significant negative correlation with emotional experience. The study established quantifiable prediction models and identified design thresholds for campus pathways. A high aesthetic greenery was key to achieving high overall benefits, while low building enclosure and vegetation complexity promoted social interaction. This achievement transforms health-oriented campus pathway design from qualitative principles into a measurable and optimizable scientific practice, thus providing an empirical basis and practical guidance for the construction of health-supportive campus environments. Full article

In the post-pandemic higher education context, multilingual students, particularly those from widening participation backgrounds, continue to face academic, linguistic, and socio-emotional challenges that can limit their participation and sense of belonging. This study examines the use of Reflective Video Diaries (RVDs) facilitated through Microsoft Flipgrid as an inclusive pedagogical approach to support reflective engagement, communication, and socio-emotional development among multilingual undergraduate students. Adopting a qualitative iterative action research approach, the study was conducted within a UK university module and involved three cycles of implementation, reflection, and pedagogical refinement, capturing students’ lived experiences rather than measuring causal effects. Multiple methods, including RVDs, end-of-module reflective reports, an anonymous survey, and lecturers’ field notes, were deliberately combined to provide complementary perspectives on students’ experiences, allowing triangulation of data and enhancing the validity and richness of findings. Thematic analysis of this longitudinal dataset collected across the three action-research cycles explored how students experienced RVDs as a space for reflection, peer support, and engagement with learning. Findings indicate that Flipgrid-mediated RVDs functioned as a low-anxiety, flexible, and dialogic learning environment that enabled students to articulate challenges, share progress, and develop reflective awareness, confidence, and a sense of connection with peers and lecturers. Improvements in participation and reflective depth were more evident in later cycles, suggesting that benefits emerged through iterative pedagogical adjustment rather than by video technology alone. Both positive experiences and challenges are reported, providing a balanced account of engagement with the RVDs. The study underscores the potential of inclusive digital pedagogies to inform curriculum planning and policy implementation, supporting equitable learning opportunities and socio-emotional development. By conceptualizing RVDs as relational and inclusive pedagogical practices rather than technological interventions, and by demonstrating how reflective engagement developed across successive action-research cycles, this research contributes to understanding how reflective digital practices can support multilingual learners’ academic and socio-emotional development within socially just higher education contexts. Practical implications for designing inclusive reflective learning environments are discussed. Full article

The integration of virtual museums into education has emerged as an innovative approach embraced by both teachers and learners, reflecting the broader impact of virtual reality (VR) applications in education. This study puts forward a pedagogical framework for utilizing virtual museums in teaching art history and investigating their impact on the art history curriculum. In this context, two free online museums are used as teaching materials, representing 3D interactive learning environments that enable immersive exploration of cultural heritage. Grounded in the Theory of Technology-Mediated Learning, this research adopts a hybrid methodological approach to track the art history courses of 75 Chinese undergraduates through experiments, questionnaires, and structured interviews over a four-week period. The findings demonstrate that virtual museum-integrated instruction significantly enhances learning effectiveness over sustained use, actively promotes learner engagement, and fosters greater autonomy. Importantly, learners prioritize educational value and authenticity in virtual museum features, while also expressing a strong preference for technologically mature platforms. This research contributes to understanding the impact of VR on digital transformation in the educational sector by providing a validated instructional model that integrates virtual museums into art history curricula, offering educators a replicable framework for implementation. Future studies should investigate the relationship between emotional engagement and academic performance within virtual museums to further refine both pedagogical strategies and educational virtual reality design. Full article

Introduction: University students are vulnerable to psychological distress due to the academic and social demands of this life stage. Mindfulness and self-compassion are effective and adaptable strategies in an academic environment that promote emotional regulation and psychological well-being. This study aims to conduct a systematic review and meta-analysis to evaluate the combined impact of mindfulness- and self-compassion-based interventions (MBSCIs) on psychological distress. It will also analyze their role as predictors of therapeutic change, as well as the moderating influence of sociodemographic and contextual factors. Method: We systematically searched PubMed, Scopus and Web of Science for randomized controlled trials (RCTs) and single-group pre-post trials investigating the effect of MBSCI on anxiety, depression and stress in college students. Studies were combined using the inverse variance method in a random effects model. Additional subgroup and meta-regression analyses were performed, and risk of bias was assessed. The review was pre-registered (PROSPERO registration number: CRD420251003822). Results: Our review included 49 studies with a total of 5043 participants (3721 in the intervention group, and 1322 in the control group). The results provide relevant evidence on the efficacy of MBSCI in the university population, especially in reducing symptoms of stress, anxiety, and depression. The effect sizes observed were moderate-to-large for stress and small-to-moderate for anxiety and depression, supporting their clinical usefulness in university educational settings. However, these findings should be interpreted with caution, as no included study achieved low risk of bias, and heterogeneity was moderate-to-high across most outcomes. Conclusions: The results suggest that MBSCI could alleviate psychological distress in university students. However, these results are limited by some methodological issues (risk of bias, heterogeneity, lack of follow-ups, poor standardization). It would be advisable to integrate these practices into the university curriculum as workshops or complementary activities. Further studies are needed to confirm their effectiveness and explore sustained effects and differences according to individual characteristics. Full article

Background: Adolescence is a sensitive developmental period marked by heightened emotional reactivity and increasing demands on emotion recognition and regulation. Although alexithymia has been associated with less adaptive and avoidant coping tendencies in adolescents, most prior research has relied on descriptive or bivariate approaches, leaving the underlying processes and model-based pathways insufficiently clarified. In particular, the explanatory role of difficulties in emotion regulation in the association between alexithymia and coping strategies remains underexplored. This study aimed to address this gap by examining whether difficulties in emotion regulation mediate the relationship between alexithymia and coping strategies in adolescents. Methods: In this cross-sectional study, 1415 adolescents (13–17 years) from public high schools in Central Anatolia, Türkiye, completed the Toronto Alexithymia Scale (TAS-20), the Difficulties in Emotion Regulation Scale (DERS-16), and the Coping Strategies Indicator (CSI). Pearson correlations were calculated. Mediation analyses were conducted using PROCESS Macro (Model 4) with 5000 bootstrap samples, adjusting for age, gender, academic achievement, and family type. Results: Alexithymia was moderately associated with emotion regulation difficulties (r = 0.49, p < 0.001). Mediation analyses revealed significant indirect effects for seeking social support (B = −0.068, 95% CI [−0.087, −0.051]) and problem solving (B = −0.067, 95% CI [−0.086, −0.049]), with direct effects remaining significant, indicating inconsistent (competitive) mediation patterns. For avoidance coping, the indirect effect was significant (B = −0.072, 95% CI [−0.090, −0.055]), whereas the direct effect became non-significant, consistent with an indirect-only mediation pattern. Correlations involving coping outcomes were small in magnitude. According to Cohen’s criteria, the association between alexithymia and emotion regulation difficulties was moderate in magnitude, whereas correlations involving coping outcomes were small. Conclusions: Difficulties in emotion regulation emerged as a statistical mediator within the proposed model, demonstrating systematic associations between alexithymia and distinct coping patterns in adolescents. These findings underscore the relevance of emotion regulation–focused prevention and intervention efforts in school settings. By examining multiple coping outcomes simultaneously within a covariate-adjusted mediation framework in a large community adolescent sample, this study offers an integrative, model-based perspective on how alexithymic traits are linked to coping through regulatory difficulties. Full article

Confidence in mathematics is a key factor for academic success, being influenced by emotional, behavioral, and technological aspects. The integration of digital tools, such as GeoGebra, has shown potential to promote engagement and develop mathematical skills. This study investigates how affective and behavioral engagement, confidence in the use of technology, and the perception of GeoGebra use relate to and contribute to explaining the confidence in mathematics of future teachers. The sample comprised 54 undergraduate students in Basic Education from a higher polytechnic institution. Participants engaged in learning activities involving real functions of a real variable using both traditional methods and GeoGebra. Data were analyzed using partial least squares structural equation modeling. The results indicate that behavioral engagement positively influences affective engagement, which, in turn, enhances confidence in mathematics. Confidence in the use of technology also has a positive effect on confidence in mathematics. The perception of GeoGebra use significantly influences behavioral engagement and confidence in the use of technology, but not affective engagement. These findings highlight the importance of the critical integration of digital technologies in mathematics education and emphasize the need to design pedagogical strategies that promote active participation and strengthen future teachers’ confidence in using technological tools. Full article

Academic functioning in university students emerges from the interplay of motivational, self-regulatory, emotional, and contextual processes. The present study examined the network structure linking academic motivation, self-regulated learning, academic engagement, academic burnout, generalized anxiety, self-esteem, and students’ ratings of instruction. Participants were 530 university students from Western Romania (Mage = 28.86, SD = 9.75; 87.5% women). Data were collected through an online cross-sectional survey using validated self-report instruments. A Gaussian Graphical Model was estimated using the EBICglasso procedure to examine the unique associations among the study variables and their relative structural importance within the network. The results indicated a moderately dense psychological network, with academic burnout emerging as the most structurally central node. Intrinsic motivation toward achievement, identified regulation, and performance control were positioned within the adaptive core of the network, whereas burnout, anxiety, amotivation, and low self-esteem clustered within the maladaptive region. Academic engagement occupied an intermediary position linking motivational and self-regulatory processes. Overall, the findings support a systems-oriented interpretation of academic functioning, suggesting that burnout represents a key convergence point in students’ psychological functioning, while self-determined motivation and self-regulated learning may serve as protective processes. These results highlight the value of network analysis for identifying psychologically meaningful intervention targets in higher education. Full article

Chatbots have spurred keen academic interest in the last decade, with researchers focusing primarily on the factors impacting chatbot adoption by consumers. Based on a systematic literature review (SLR) of 202 selected peer-reviewed papers published from 2015 to 2025, this article aims to achieve the following objectives: (1) describe publication trends, including relevant journals and highly-cited papers; (2) analyze the methodological approaches and theoretical models employed in the field; (3) investigate the drivers and barriers to consumers’ adoption of chatbots; and (4) outline directions for future research. Among the findings, the review reveals that perceived usefulness, perceived ease of use, anthropomorphic characteristics, consumer trust in chatbot applications, and the ability of chatbots to emulate a human-like personality are key drivers of chatbot adoption, whereas perceived risks and anxiety are the most reported barriers. This study offers several future research avenues and highlights the importance of considering the role of emotions and personality traits. Full article

Background/Objectives: Nomophobia, the irrational fear of being without a mobile phone, is increasingly prevalent among university students and has emerged as a concerning form of digital dependence. Among nursing students, this condition is particularly relevant due to the emotional demands and cognitive challenges of healthcare education. Nomophobia has been linked with adverse psychological outcomes, sleep disturbances, and impaired academic and clinical performance. However, existing evidence remains fragmented and lacks an integrated conceptual synthesis. This review aimed to synthesize current evidence on the prevalence, correlates, and outcomes of nomophobia among nursing students. Methods: An integrative review was conducted following Whittemore and Knafl’s methodology and PRISMA guidelines. A systematic search was performed in PubMed, CINAHL, PsycINFO, PsycArticles, and Medline (between 2015 and 2025), supplemented by Google Scholar. Cross-sectional studies and literature focusing on nomophobia in nursing students were included. The primary studies and selected review articles were considered when no overlap with the included primary evidence was identified. Methodological quality appraisal was assessed using validated tools (QuADS and JBI). Results: Twenty-two studies were included (19 cross-sectional and 3 reviews). Four thematic areas emerged: prevalence and severity (50–90% moderate to severe); psychological correlates (anxiety, depression, stress, insomnia, alexithymia, fear of missing out); academic and cognitive outcomes (impaired performance, procrastination, reduced decision-making); and behavioural predictors (excessive smartphone use and emotional dysregulation). The Nomophobia Questionnaire (NMP-Q) was the most frequently used instrument. Conclusions: Nomophobia represents a relevant dimension of the mind–technology relationship in nursing education, with implications for students’ mental health, academic engagement, and clinical readiness. Addressing nomophobia may support healthier learning environments and contribute to the development of emotionally competent and safe future healthcare professionals. However, significant gaps remain, particularly regarding longitudinal evidence and intervention-based approaches. Full article

Artificial intelligence (AI)-mediated tools have rapidly penetrated student life and become a valuable resource for seeking help with academic assignments/tasks, psychological problems, and social interactions. This study aims to investigate the levels and associations of AI-help-seeking behavior (AI-HSB), anxiety, stress, and depression among university students in the United Arab Emirates (UAE). In addition, it examines the factors associated with AI-HSB based on the selected demographic (gender, marital status, age, academic year, employment status, major, and nationality), as well as anxiety, stress, and depression. This study employed a descriptive cross-sectional design among 433 university students, who were recruited via an online Google Form between 1 October 2025 and 10 December 2025. The study utilized validated Arabic versions of the AI-HSB scale and the anxiety, stress, and depression scale. Descriptive statistics, Pearson correlation, and predictive analyses were conducted using SPSS v 25. Results indicated that students reported moderate reliance on AI-HSB despite moderate to severe levels of psychological distress, with particular emphasis on anxiety. The AI-HSB was positively associated with anxiety, stress, and depression amongst the participants. Furthermore, both depression and the students’ academic year emerged as the only significant predictors of AI-HSB, explaining a modest but meaningful proportion of variance with an exact percentage of 18.1%. AI tools may partially circumvent stigma by offering privacy and anonymity; however, cultural expectations around interpersonal support, trust, and authority may simultaneously limit students’ willingness to rely on non-human agents for emotional care. Full article