Search Results (3,256)

The proliferation of generative AI (GenAI) in higher education necessitates a shift towards more authentic assessment methods that can genuinely measure student understanding. Student-created screencasts are a potentially valuable yet underexamined assessment format in higher education. A screencast is a screen capture video, which records all the activities on a computer screen. This study examines the efficacy of student-created screencasts as an authentic assessment. Using data from 84 undergraduate students, Elastic Net regression and Shapley Additive Explanations (SHAP) analysis were applied to examine predictive relationships across assessment types: screencasts with audio narration (SWAs), screencasts without audio (SNAs), written assignments, and group project presentations. The findings reveal that SWAs have a moderate-to-strong positive association with test performance, acting as a significantly stronger predictor than both traditional written work and SNAs. The results suggest that narrated screencasts may serve as a useful assessment format for gauging student understanding, supporting the early identification of at-risk students, and providing a platform for developing crucial communication skills. This assessment strategy holds promise for enhancing academic integrity and learning in the GenAI era. This study contributes to assessment research by demonstrating the predictive value of narrated screencasts in identifying at-risk students in AI-supported learning environments. Future research should extend this work through multi-institutional designs, longitudinal analysis, and qualitative investigation of student perceptions in various courses other than artificial intelligence. Full article

Introduction: Sleep is essential for cognitive performance and psychological well-being. Medical students are particularly vulnerable to sleep disturbances due to academic stress and irregular schedules. Beta-blockers are increasingly used to alleviate anxiety and performance stress, with lipophilic agents such as propranolol affecting sleep. Evidence on the association of beta-blocker use with sleep disturbances among medical students in Jordan is limited. Objective: The aim of this study was to describe self-reported sleep characteristics among medical students in Jordan and report patterns related to beta-blocker use. Methods: A quantitative cross-sectional study was conducted among 697 undergraduate students from six public medical schools in Jordan over a one-month period. Data were collected using an anonymous online questionnaire on beta-blocker use and sleep characteristics. Associations were analyzed using chi-square tests, with a p < 0.05 considered significant. Results: Of 697 students, 23 (3.3%) were current and 11 (1.6%) were previous users of beta-blockers; 663 (95.1%) had never used them. Beta-blocker use was significantly associated with smoking status (p = 0.013) but not with academic level or caffeine consumption. In multivariable analysis, males had lower odds (OR = 0.4) of beta-blocker use compared with females. More than half of current users (56.5%) reported non-prescribed use, with propranolol (78.3%) being the most commonly used beta-blocker. Sleep-related disturbances were frequently reported among current users, including nocturnal awakenings (73.9%), nightmares or disturbing dreams (69.6%), morning fatigue (65.2%), difficulty waking (52.2%), and sleep-onset insomnia (39.1%), with about one-third reporting a decline in sleep quality. Conclusions: Beta-blocker use among medical students in Jordan is mostly non-prescribed and primarily for anxiety or exam stress. Users frequently reported sleep disturbances, highlighting the need for medical guidance to prevent adverse effects. These findings can inform local guidelines and raise awareness about the risks of unsupervised beta-blocker use among medical students, supporting safer practices and better overall well-being. Full article

Digital technologies are central to student life, but evidence is limited on whether digital-use scales can provide useful thresholds for identifying psychological distress among medical students. This single-center cross-sectional study analyzed complete data from 600 undergraduates at a medical university in southern Vietnam. Stress, depression, and anxiety symptoms were classified using the DASS-21, while problematic smartphone use, social media use, and gaming-related problems were assessed using the SABAS, BSMAS, and a six-item GAS adaptation, respectively. Receiver operating characteristic analyses and the Youden index were used to estimate discrimination and candidate cut-offs. Non-normal DASS-21 scores were observed for stress (30.4%), depression (37.8%), and anxiety (39.0%), predominantly within the mild range. For stress, the AUCs and cut-offs were 0.75 (95% CI 0.70–0.80; ≥23.5) for SABAS, 0.67 (0.62–0.71; ≥17.5) for BSMAS, and 0.64 (0.60–0.70; ≥15.5) for GAS. For depression, the corresponding values were 0.62 (0.57–0.66; ≥21.5), 0.68 (0.63–0.73; ≥18.5), and 0.60 (0.55–0.65; ≥14.5). For anxiety, they were 0.60 (0.55–0.64; ≥20.5), 0.62 (0.57–0.67; ≥17.5) and 0.55 (0.51–0.60; ≥15.5). Sensitivity was low across thresholds (35.0–59.0%). These candidate cut-offs showed modest discrimination and should be considered only as preliminary behavioral flags prompting validated mental health assessment, not as stand-alone screening or diagnostic criteria. Full article

Formal undergraduate research training programs are typically two years in length to support student development over time. However, some evidence suggests that many benefits of research participation can be achieved in a shorter duration, raising the question of whether shorter models can be as effective. This prospective study compared outcomes for two concurrent cohort-based research training models: a two-year Scholars Program and an accelerated one-year Fellows Program. The Fellows Program was designed for advanced students who joined the training program later than their peers for a variety of reasons. Both programs provided students with financial support, faculty-mentored research, a Learning Community, and other resources for professional development. The longer duration allowed Scholars to report significantly higher levels of research skills and produce more publications and professional presentations than Fellows by the end of their respective training programs. In contrast, the programs did not differ on graduation GPA, number of awards, or graduate school enrollment. Fellows also did not significantly differ from Scholars on psychosocial measures, including science/researcher identity, belongingness, cultural compatibility, family support, or time management. Findings suggest that a high-intensity, one-year model can deliver many broad academic and social benefits associated with the two-year model, while a longer two-year model provides students with more time and additional research opportunities to be more productive. We conclude that both types of programs should be available to best meet students’ needs and to make the most effective use of program resources. Full article

Interactions with people who are highly engaged in sustainability (e.g., zookeepers, environmental educators) can have a significant impact on motivating less-engaged individuals to adopt more pro-environmental beliefs and to act on them. The current work examined two groups, graduate students mainly in conservation careers (n = 35) and an undergraduate comparison group (n = 237), to observe how they differed on sustainability beliefs (e.g., reports of willingness to sacrifice for the environment, anthropogenic global warming beliefs), reports of emotional experiences, reflections on nature, and nature–self–humanity cognitive representations. In comparison to undergraduate students, a frequently studied population in sustainability research, the graduate students reported greater willingness to sacrifice for the environment, stronger belief in anthropogenic global warming, and weaker self-interested emotions. When spontaneously reflecting on nature, the graduate students expressed greater connection with nature and stronger negative feelings about how humanity treats the environment. Finally, the graduate students showed more sustainable nature–self representations (e.g., greater inclusion of nature in self, viewing nature as larger than the self). We discuss the implications of these findings for understanding groups that may vary in environmental engagement, for developing measures to assess qualitative and quantitative assessments of nature–self–humanity knowledge, and for providing observations that may spur future work on encouraging people to care more strongly about nature and for supporting people engaged in sustainability fields. Full article

This exploratory mixed-methods study investigated the relationships among students’ engagement with L2 tasks, extramural English, and their self-assessed L2 proficiency. Participants were undergraduate students at a public university in Myanmar. First, qualitative data were elicited from eight students; then, quantitative data were collected from 336 participants. The thematic analysis revealed how students engaged with L2 tasks and extramural English cognitively, behaviourally, emotionally and socially. The quantitative results underpinned with evidence of students’ high to moderate levels of engagement with tasks in their English classes and beyond them. Correlation analysis documented that their engagement with L2 tasks in and beyond their classes were positively and significantly related to their self-reported L2 competency. SEM results evidenced a positive and significant direct pathway of task engagement to participants’ English proficiency (β = 0.367, p < 0.001); whereas, a direct prediction of extramural English engagement on self-reported L2 proficiency was statistically not significant (β = 0.059, p > 0.05). Task engagement significantly mediated the relationship between extramural English and participants’ L2 outcomes (β = 0.161, p < 0.001). These findings highlight the pivotal role of task engagement both in and outside English classes. L2 educators should recommend and integrate extramural English activities to enhance their students’ proficiency in English. Full article

The rapid integration of artificial intelligence (AI) into higher education has renewed concern that technology-related strain may erode students’ higher-order thinking. Drawing on a social–cognitive framework, this study tested whether AI self-efficacy and technostress predict critical thinking in 340 Peruvian undergraduates, who completed three validated scales (Yoon’s Critical Thinking Disposition Inventory; the brief General Self-Efficacy Scale for AI, GSE-6AI; and the RED-Technostress scale). Data were modeled with PLS-SEM, with significance from 5000 bootstrap resamples and an out-of-sample predictive assessment (PLSpredict, CVPAT). AI self-efficacy was a robust positive predictor of critical thinking (β = 0.42, p < 0.001), whereas technostress had no direct effect (β = −0.06, p = 0.50); AI self-efficacy was associated with higher technostress (β = 0.24, p < 0.001), but that path did not carry over to critical thinking (no mediation). A hypothesized moderation (AI self-efficacy mattering more at higher technostress) was not confirmed: it reached significance under the two-stage method but not under a stricter bootstrap, and the hypothesis was therefore not supported. The model explained a modest share of variance in critical thinking (R² = 0.17) and was invariant across public and private universities. These findings reposition technostress as, at most, a distal correlate and identify confident, literate engagement with AI, rather than the absence of strain, as the more promising lever for cultivating critical thinking. Full article

The increasing prevalence of anxiety, depression, and stress has intensified the demand for scalable, evidence-based psychological interventions that can be delivered across traditional and digital modalities. University students represent a high-risk group due to academic demands and developmental transitions, making them a relevant population for evaluating flexible, technology-mediated interventions. Cognitive-behavioral therapy (CBT)-based psychoeducation offers a structured approach that may accommodate variability in accessibility, preferences, and delivery contexts. This quasi-experimental pre–post study evaluated a CBT-based psychoeducation protocol delivered in group settings in both online and in-person formats. A total of 104 undergraduate and graduate students participated and completed the intervention. Symptom severity was assessed using the Depression, Anxiety and Stress Scale (DASS-21), the Hamilton Anxiety Rating Scale (HAM-A), and the Beck Depression Inventory–II (BDI-II). Significant reductions in anxiety, depression, and stress symptoms were observed over the intervention period, with moderate to large effect sizes. DASS-21 scores decreased from moderate to mild severity levels, and reductions were also observed in BDI-II and HAM-A scores. No significant differences were found between delivery modalities. These findings support the potential of CBT-based group psychoeducation as a scalable intervention. Similar patterns of symptom change were observed across delivery formats, contributing to the expansion of accessible and digitally informed mental health care. Full article

Creative thinking has become an increasingly important competence in education, yet less is known about how it may be supported in human–AI collaboration as large language models (LLMs) are increasingly employed as partners in learning and problem solving. This study examined whether and how cognitive support and social interaction in AI-assisted collaboration were associated with divergent and convergent thinking. A total of 92 undergraduate students completed creative problem-solving tasks with GPT-4.0. Data were collected from task outputs and self-report measures, and the hypothesized associations were tested using structural equation modeling, with indirect effects examined as supplementary analyses. Results showed that in human–AI collaboration, social interaction rather than cognitive support was associated with more positive affective experiences, and this affective pathway was linked specifically to convergent thinking rather than divergent thinking. These findings suggest that associations between AI-assisted collaboration and creative thinking may depend less on perceived cognitive support alone than on the extent to which collaboration is experienced as socially engaging and affectively positive, particularly for convergent thinking. Full article

Generative artificial intelligence (AI) is rapidly transforming higher education, yet comparative evidence from diverse international settings remains limited. This cross-national study examined undergraduate students’ adoption and perceived academic impact of generative AI tools at institutions in Indonesia, Tajikistan, and the United States. A harmonized online survey was administered to 584 undergraduates during Spring 2026 (Indonesia n = 235; Tajikistan n = 226; United States n = 123). The survey assessed AI familiarity, adoption patterns, frequency and purpose of use, perceived academic impact, and factors encouraging AI engagement. AI adoption differed significantly across sites, with the highest adoption observed in Indonesia (84.3%), followed by Tajikistan (67.7%) and the United States (47.2%). These differences remained significant after adjustment for demographic and educational variables. Self-rated AI familiarity was the strongest predictor of both adoption and perceived academic benefit across all three settings. Differences across sites persisted even after accounting for participants’ academic discipline. The perceived-impact scale demonstrated excellent internal consistency (Cronbach’s α = 0.907). Brainstorming, writing assistance, and broader task diversification were associated with higher perceived benefit. Exploratory analyses found limited evidence linking learning-style preferences to AI use patterns. The findings highlight the importance of institutional context, self-rated AI familiarity, and curriculum integration in shaping student engagement with generative AI. Full article

This qualitative study, grounded in a phenomenological-interpretive design, aimed to explore university students’ experiences regarding digital hyperconnectivity, emotional well-being, and the balance between academic and personal life at a private university in Viña del Mar, Chile. The sample consisted of 18 Occupational Therapy students (mean age: 22.4 years; 61.1% female, 27.8% male, 5.6% non-binary; representing a diverse range of undergraduate academic years from second to fifth). Data were collected through individual semi-structured interviews and analyzed using open, axial, and selective coding following grounded theory guidelines, with the assistance of Atlas.ti v25 software, to identify emerging categories and establish conceptual relationships. Findings were organized into two analytical categories. The first, Experiences and perceptions of digital hyperconnectivity, portrays hyperconnectivity as a taken-for-granted everyday condition shaped by intensive device use and the predominance of social media, streaming platforms, and artificial intelligence tools; within this category, a tension emerges between recognized practical/pedagogical usefulness and distracting or compulsive patterns of use. The second, Emotional well-being and balance in academic life, highlights the impact on emotions, time management, sleep, and relationships, as well as disconnection strategies to restore balance (time limits, mental breaks, and offline activities). In conclusion, digital hyperconnectivity is significantly associated with emotional well-being and the academic-personal life balance. Students’ narratives suggest that technology can enrich learning when accompanied by regulation, media literacy, and deliberate disconnection practices. Therefore, context-sensitive institutional interventions are needed to promote conscious disconnection, digital identity education, and a pedagogical design that integrates digital tools through a critical and ethical approach. Full article

This study presents a laboratory module designed to introduce undergraduate students to fundamental concepts of photolysis through the degradation of sulfamethoxazole (SMX), a widely used antibiotic and an emerging environmental contaminant. The module comprises three interconnected 4 h practical sessions. Participants investigate SMX decomposition under four illumination conditions (UVC, UVB, UVA, and visible light), comparing direct photolysis with commercial TiO₂ (P25)-mediated photocatalysis. Core activities include constructing kinetic profiles, performing pseudo-first-order regression analyses, interpreting UV-Vis absorbance spectra, and elucidating degradation mechanisms through radical quenching tests and electron paramagnetic resonance spectroscopy. Representative results demonstrate significant direct photolysis of SMX under UVC as well as UVB, and negligible photocatalytic degradation under visible light. The above results, corresponding to the light absorption spectrum of SMX and the UV-Vis diffuse reflectance spectrum of TiO₂, facilitate the understanding of the photolysis process. Hydroxyl radicals (•OH) were identified as the primary reactive species during the SMX degradation under UVA/TiO₂. The experimental framework relies exclusively on conventional instrumentation (photoreactor, HPLC, UV-Vis spectrophotometer) and commercially available reagents, ensuring broad accessibility. This laboratory module contributes to sustainability-oriented education by offering a cost-effective, reproducible, and adaptable platform for introducing advanced oxidation processes in water remediation. Full article

Background/Objective: Social media platforms have become increasingly integrated into nursing students’ academic and daily lives, influencing how health-related information is accessed, evaluated, and shared. At the same time, eHealth literacy has emerged as an important competency for nursing students within contemporary digital healthcare environments. This study aimed to examine the relationship between multidimensional social networking engagement and perceived eHealth literacy among undergraduate nursing students. Methods: A cross-sectional descriptive correlational design was used among undergraduate nursing students (N = 146). Data were collected using an electronic survey that included demographic characteristics, the Social Networking Usage Questionnaire, and the Revised eHealth Literacy Scale. Descriptive statistics, Pearson’s correlation, and linear regression analyses were performed using SPSS version 26. Results: Participants reported moderate-to-high social networking engagement and generally favorable perceived eHealth literacy. A strong positive correlation was identified between SNUQ and eHEALS-R scores (r = 0.75, p < 0.001), with academic use showing the strongest dimension-level association with perceived eHealth literacy. In the adjusted regression model, social networking engagement remained independently associated with perceived eHealth literacy, whereas demographic variables and daily social media use showed no significant associations. Conclusions: The findings suggest that how nursing students engage with digital platforms is associated with their confidence in accessing, evaluating, and applying online health information. Strengthening purposeful and critical digital engagement within nursing education may help prepare students for contemporary digital healthcare environments. Full article

Background/Objectives: The assessment of clinical competencies in nursing education requires valid and reliable instruments, especially for essential procedures such as the placement of a cervical collar in the care of polytrauma patients. The objective of this study was to analyse the psychometric properties of a rubric designed to assess the placement of cervical collars in nursing students in a low-fidelity clinical simulation environment. Methods: A quasi-experimental, cross-sectional study was conducted with 186 undergraduate nursing students, organised into 61 groups, over three academic years (2021–2024). An eight-item rubric was applied, with a four-level Likert scale (1–4). Interrater reliability was analysed using Cohen’s Kappa index (0.418–0.796), internal consistency using Cronbach’s alpha (alpha = 0.753), and the internal structure of the instrument using exploratory factor analysis, applying Varimax orthogonal rotation. Results: Inter-rater reliability showed values ranging from moderate to substantial, with greater agreement observed in items related to the selection of the collar and the position of the medical team, and moderate agreement in those related to technical manoeuvres and immobilisation. The rubric showed adequate overall internal consistency (α = 0.76), with good to very good consistency values in six of the eight items. Exploratory factor analysis identified a two-dimensional structure with a dominant procedural factor (four items) and a second factor associated with clinical judgement (four items). Conclusions: The validated rubric has adequate levels of reliability and internal consistency for evaluating the placement of cervical collars by nursing students. Its application can promote more objective and structured evaluation processes in clinical simulation for nursing students, contributing to the development of essential skills in the care of polytrauma patients. Full article