İzmir Democracy University

This study aimed to develop and validate the Text-Based Generative AI Literacy Scale (T-GASE)—a multidimensional instrument designed to assess individuals’ competencies in interacting with, evaluating, and ethically engaging with text-based Generative AI (GenAI) tools. The scale development followed Hinkin’s five-step framework, including item generation, expert validation, pilot testing, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). A total of 645 undergraduate students participated in the study, with 332 students in the EFA phase and 313 in the CFA phase, all from diverse academic disciplines such as engineering, education, architecture, economics, and social sciences. Grounded in four well-established theoretical frameworks—the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), Expectancy-Value Theory (EVT), and Diffusion of Innovations Theory (DIT)—the final 23-item scale revealed a robust four-factor structure: Application, Expectations, Ethics, and Evaluation. The scale demonstrated strong psychometric properties, with high internal consistency and excellent model fit indices. Results showed that students had high expectations for the future of GenAI and were actively using it but exhibited lower confidence in critically evaluating AI-generated content. Moreover, students from STEM-oriented disciplines outperformed those from non-STEM fields, suggesting disciplinary differences in GenAI literacy levels. Unlike existing AI literacy scales that broadly assess technical knowledge or general attitudes, the T-GASE uniquely addresses the practical, ethical, and evaluative skills specific to text-based GenAI tools, including prompt crafting, misinformation detection, and adaptive usage. These findings highlight the T-GASE as a pioneering and theoretically grounded instrument for assessing GenAI literacy, with significant implications for curriculum design and digital competence development across higher education contexts.

This study investigates the influence of external alkaline immersion curing on the strength development and microstructural evolution of Class F fly ash-based geopolymers. In this approach, specimens are exposed to alkaline solutions after initial activation, unlike conventional systems where the activator is directly incorporated into the mix. A total of 43 mixtures were subjected to air, water, oven, and alkaline immersion curing at 20 degrees C and 80 degrees C using NaOH solutions (0.33-3 M) for up to 7 days. Compressive strength was interpreted alongside SEM/EDX, FTIR, and XRD analyses. At 20 degrees C, water and alkaline immersion curing showed no improvement over ambient curing, whereas alkaline immersion at 80 degrees C significantly enhanced strength. The highest compressive strength (75 MPa at 7 days) was achieved at moderate alkalinity (0.33-0.67 M), about 20% higher than oven curing. Excessive alkalinity (2-3 M) caused microcracking and reduced performance. Results show that curing temperature and external alkalinity govern geopolymerization and matrix densification.

Geotechnical engineering frequently encounters soils exhibiting insufficient mechanical strength or undesirable hydraulic properties, necessitating the implementation of soil improvement techniques. In the contemporary context of escalating global energy demands and rapid population growth, the selection of stabilization materials must rigorously prioritize sustainability, environmental compatibility, and cost-effectiveness. Furthermore, the expansion of energy infrastructure, often involving near-surface heat transfer mechanisms, requires a comprehensive understanding of soil behavior under elevated thermal regimes. This study investigates the potential of dried Zostera marina (seaweed) biomass as a novel, sustainable, and low-cost alternative additive for soil stabilization. Historically recognized for its thermal insulation capabilities in cold climates, Zostera marina represents a readily available waste product of marine origin. The research focused on evaluating the thermo-hydraulic conductivity performance of mixtures formulated by incorporating Zostera marina into a base matrix of zeolite and bentonite. Hydraulic conductivity tests were systematically conducted under two distinct thermal conditions: ambient laboratory temperature (RT) and an elevated temperature of 40 degrees C, allowing for the isolation of additive and thermal influences on permeability. The experimental results demonstrate a critical dual behavior. At ambient temperature, the inclusion of Zostera marina effectively reduced the hydraulic conductivity of the mixtures. However, under the 40 degrees C thermal regime, a discernible increase in permeability was recorded, a finding consistent with established literature concerning the temperature-dependent hydro-mechanical response of organic-rich or clay-based matrices. These findings highlight the ne-cessity of considering service temperature when developing sustainable stabilization techniques utilizing marine biomass additives.

Objective:This cross-sectional study aimed to identify significant child-related, parent-related, and social predictors of parental stress among parents of children diagnosed with autism spectrum disorder (ASD) or intellectual disability (ID). Method:A total of 100 parents were recruited from a child and adolescent psychiatry outpatient clinic (56 parents of children diagnosed with ASD and 44 parents of children with ID). Participants completed the Strengths and Difficulties Questionnaire (SDQ), the Multidimensional Scale of Perceived Social Support (MSPSS), the Parental Attitude Scale (PAS), the Impact on Family Scale (IFS), and the Parental Stress Scale (PSS). Descriptive statistics and multivariate regression analyses were conducted to determine which variables best predicted parental stress. Results:Multivariate linear regression analysis indicated that the overall model significantly predicted parental stress, F(9, 90)=6.877, p<0.001, explaining 34.8% of the variance. Parental self-efficacy (β=-0.285, p=0.003) and perceived family support (β=-0.213, p=0.024) emerged as significant independent predictors of stress. In contrast, children's emotional and behavioral difficulties (SDQ scores) and family impact (IFS scores) were not significantly associated with parental stress in the final model. Conclusion:The findings highlight parental self-efficacy and family support as key predictors of parental stress in families of children with neurodevelopmental disabilities (NDD). These results underscore the importance of strengthening parental competence and enhancing family-based support resources to alleviate parental stress.

Despite extensive research on the impacts of flooding on urban transportation, few studies have systematically assessed neighborhood-scale flood resilience. This study focuses on the Mavis,ehir neighborhood in I(center dot)zmir, Turkey, to evaluate the vulnerability and resilience of its road transportation network under flood conditions. Using GIS-based network modeling and quasi-real-time traffic data, the analysis measures accessibility disruptions, increased travel times, and the network's capacity to support emergency operations during inundation. Three research questions guide the study: (1) Which areas become inaccessible, and how are local populations and infrastructure affected? (2) How do network disruptions influence travel times and emergency accessibility? (3) What do these patterns reveal about overall network resilience? A total of 282 residential buildings and 11,876 housing units were identified within the inundated zone. Using an average household size of 3, the affected population is estimated at 35,628 people. During the flood scenario, total travel times increased by 20-25 %, with the most severe impacts observed between 14:00 and 17:00. Such delays present critical challenges for emergency response, evacuation, healthcare access, and essential services. Overall, the findings provide actionable insights for urban planners and decision-makers, underscoring the need for climate change adaptation strategies that enhance urban transportation resilience, reduce social and economic losses, and strengthen neighborhood-scale disaster preparedness.