Ibn Haldun University

As Tufan al-Aqsa marks its second anniversary, the devastation in Gaza remains immense. Thousands have been killed in relentless Israeli bombardments, and countless children, the sick, and the elderly face starvation under a blockade that has systematically denied access to food, medicine, and humanitarian aid. Relief efforts to reach Gaza’s besieged population have been deliberately obstructed, while global protests from India to the United States have been criminalized and severely repressed. Diplomatic initiatives and peace negotiations have yielded no lasting results. In a striking display of hypocrisy, several Western states complicit in the genocide against Palestinians have now moved to recognize Palestine as a state.

This study aims to identify and prioritize the key factors influencing export performance among Turkish exporters, based on the resource-based view (RBV) and industrial organization theory (IO), categorizing the factors as internal and external, and employing the Stepwise Weight Assessment Ratio Analysis (SWARA). Twenty-five factors across Internal (IF) and External (EF) categories were evaluated through expert assessments. Results reveal that Internal Factors (58.0%) significantly dominate External Factors (42.0%), indicating that Turkish exporters possess substantial control over their export competitiveness. The top five critical factors are Management and Leadership (9.6%), Strategy (6.2%), Technological Change (5.3%), Industry and Sector Activity (5.0%), and Competitors (5.0%). Surprisingly, traditional factors such as firm size, international experience, and digitalization ranked much lower, challenging conventional assumptions about export success. A leave-one-out (LOO) sensitivity analysis further validated the robustness of these rankings, with Management and Leadership, and Strategy emerging as the most stable and dominant factors across all scenarios. The predominance of management and strategic factors over structural characteristics suggests that even smaller, less experienced companies can achieve export success through effective leadership and strategic planning. These findings contribute theoretically by supporting the notion that the resource-based view has a greater impact on export performance than the industrial organization theory, and they provide practical guidance for companies to focus on managerial and leadership skills, organizational capabilities, and strategic approaches to enhance export investments. The study presents the first comprehensive SWARA-based ranking of export performance factors in the Turkish context, providing empirical evidence to support the internal-external factor debate in the international business literature.

Abstract Purpose This study examines the extent to which artificial intelligence (AI) applications predict psychological flourishing and sustainable development among Fayoum University students. It further explores gender differences in AI usage, flourishing levels, and sustainability orientations, as well as the interrelationships among the three variables. Methods A quantitative correlational design was employed using validated scales measuring AI application use, psychological flourishing, and sustainable development. The sample consisted of 190 university students from Fayoum University (Egypt) there ages were between 20 and 25 years. The mean age was 22.54 years, with a standard deviation of 3.22 years. Data were analyzed using t-tests, Pearson’s correlation coefficients, and simple linear regression to test the study hypotheses. Results Findings revealed no significant gender differences in AI application use, while significant differences were found in psychological flourishing and sustainable development in favor of male students. Significant positive correlations emerged among AI use, flourishing, and sustainability. Regression analyses showed that AI application use moderately predicted psychological flourishing (R 2 = 0.098) but strongly predicted sustainable development (R 2 = 0.604), indicating that AI plays a substantial role in shaping students’ sustainability-related behaviors. Conclusions The study demonstrates that AI applications contribute meaningfully to enhancing students’ well-being and sustainability practices, with a stronger influence on sustainability outcomes. These findings underscore the growing relevance of AI-driven learning environments in promoting sustainable education and student development. Implications The results highlight the need for integrating AI-based tools into higher education policies, fostering responsible AI use, and developing institutional initiatives that enhance students’ well-being and sustainability competencies.

This study aimed to evaluate an eight-week Understanding by Design-based climate change program implemented in 153 elementary schools across Türkiye (65 cities) with a total of 1350 teachers and 35000 students. 402 teachers from 77 schools in 35 cities filled out the teacher opinion form to evaluate the program. Additionally, three focus group interviews with a total number of 26 teachers were conducted in the three biggest cities in Türkiye. In focus group interviews and teacher opinion forms, teachers were asked to evaluate the curriculum in terms of context, input, process, and product. The transcriptions obtained from the focus group interviews and teacher opinion forms were analyzed with content analysis. According to the findings of the study, the curriculum effectively addressed the teachers' needs for climate change education, and the activities helped students to understand and transfer knowledge to their daily lives. However, due to physical limitations and a lack of time, sometimes the activities could not be completed as desired. As a result, this research found that climate change education developed using Understanding by Design is effective for students to comprehend and apply knowledge in their daily lives, which are the ultimate goals of climate change education.

Background/Objectives: Canagliflozin (CFZ) is the first sodium glucose co-transporter 2 (SGLT-2) inhibitor and is characterized by poor water solubility and permeability, resulting in low oral bioavailability. In this study, a CFZ nanosuspension (CFZ-NS) was converted into a solid form to improve the physical stability of CFZ nanocrystals (CFZ-NCs) and to enable formulation as a tablet dosage form. Methods: To achieve adequate redispersibility of dried CFZ-NCs, fluid bed granulation and spray-drying methods were employed, and the effects of critical process parameters were investigated. The stability of spray-dried nanocrystal tablets (NCs-SD-TAB) was evaluated over a three-month period under storage conditions of 25 ± 2 °C with 60 ± 5% relative humidity (RH) and 40 ± 2 °C with 75 ± 5% RH. Results: The highest redispersibility index (94%) was obtained using the spray-drying method. Tablets prepared with spray-dried NCs-SD-TAB exhibited a significantly higher in vitro dissolution rate under non-sink conditions compared with control tablets prepared using unprocessed CFZ with the same excipients, as well as the marketed product. NCs-SD-TAB showed an approximately three-fold increase in drug release at 15 min in 0.1 N HCl, with a pH 4.5 acetate buffer and pH 6.8 phosphate buffer, which simulate gastrointestinal pH conditions, relative to the marketed product. Conclusions: Overall, these results indicate that nanocrystal technology represents a promising approach for CFZ as an improved oral drug-delivery system, primarily due to its solubility enhancement capabilities.

This study examines how artificial intelligence (AI)-mediated instruction shapes novice language teachers' identity by highlighting both reinforcing and disrupting forces. Seven novice English as a Foreign Language (EFL) teachers at a private language school participated in a three-phase qualitative design: (a) demographic interviews to contextualize backgrounds and expectations; (b) observations of three lessons per teacher from an 18-session course in which AI tools were implemented; and (c) stimulated-recall interviews anchored to recorded AI episodes. Transcripts from all phases were analyzed through iterative open, axial, and selective coding, with reflexive memoing and member checking to enhance credibility. Findings reveal AI as a double-edged driver of identity. Reinforcing factors included enhanced classroom dynamism and efficiency, increased creativity, boosted self-confidence, and the emergence of a tech-savvy teacher identity. Disrupting factors involved challenged pedagogical knowledge, a perceived lack of AI expertise, limited recognition and appreciation within the institution, and moments of professional authenticity crisis. Overall, AI-mediated episodes prompted oscillations rather than linear change in identity, positioning novices alternately as empowered innovators and uncertain practitioners; targeted AI literacy, mentored experimentation, and recognition structures are recommended to stabilize preferable positions.

ABSTRACT Artificial Intelligence (AI) is increasingly embedded in secondary education, yet its impact on high school students and teachers remains underexplored. This study employed a sequential explanatory mixed-methods design to investigate AI adoption, attitudes, and concerns among 545 students and 24 teachers in Kashmir, India. Quantitative results, grounded in the Technology Acceptance Model and Sociocultural Learning Theory, showed that sociocultural and self-perceived learning emerged as the strongest predictors of positive attitudes, followed by ease of use and usefulness, while ethical concerns had a minor negative influence. Qualitative interviews revealed optimism about AI’s potential but highlighted risks related to plagiarism, over-reliance, and assessment authenticity. Findings point to the need for AI literacy, ethical training, and clear institutional policies to guide responsible integration. This study contributes one of the first comprehensive accounts of adolescent and teacher perspectives on AI in high school learning, offering evidence-based recommendations for pedagogy and policy.

Language teacher immunity (LTI), i.e., the ability to confront professional challenges, has recently gained momentum in applied linguistics research. However, the impact of technology integration on its development across diverse educational contexts has not yet received the attention it deserves. The present study aims to fill this gap by exploring the immunity of 10 language teachers from public and private institutions with respect to the integration of technological instruments in their actual practices. Data were collected through narrative frames and semi-structured interviews drawing on Activity Theory (AT). The data analysis revealed that both groups of teachers experienced maladaptive immunity due to insufficient infrastructure, inequitable assessment standards, lack of technological support, administrative greed, and inadequate TPACK in their educational environments. To address these triggers, public sector teachers endeavored to adapt external resources while private sector teachers practiced autonomy and engaged in professional development courses. The participating teachers found self-reliant strategies more beneficial and reported that engaging in these processes led to a range of self-perceptions, from feeling highly autonomous to feeling demotivated. This study provides implications for language teachers, policymakers, and teacher educators.