This article aims to answer the research question: How do 5th grade students experience the use of artificial intelligence (AI) tools to create a comic strip describing the survival struggle between the Myna and the Lesser Kestrel? This study utilized a case-study approach to examine the advantages and challenges experienced by 5th grade students using AI tools to create a comic strip about the Lesser Kestrel's survival struggle. Data were collected through qualitative methods, including student reflections, drawings, and analyses of the comic strips they created. Additionally, a questionnaire was used to assess students' attitudes towards the four components of 21st century skills: Creativity, critical thinking, collaboration, and communication. The study indicates that the development of 21st century skills among students requires a collaborative effort involving both parents and teachers. It is not sufficient to rely solely on technological tools; there must be intermediary processes and support from teachers, who are obliged to adjust their teaching methods. Additionally, a teaching approach that supports the creation of a future citizen with a humanistic outlook and awareness of the complexity of life, is essential. This approach develops students' environmental citizenship, which is also an important 21st century skill. This involves integrating ethical, inclusive, and holistic perspectives to address complex problems, such as the survival struggle between the Lesser Kestrel and Myna.

This study analyzes trends, collaborations, and research developments on augmented reality (AR) in mathematics education using a bibliometric approach. Data were collected from the Scopus database on July 31, 2024, identifying 542 documents published between 2015 and 2024. After screening, 194 journal articles were selected for analysis. Using VOSviewer, the study produced visualizations related to document types, publication trends, journal sources, research subjects, institutions, countries, keywords, and author collaborations. The results show that 88.7% of the documents are journal articles, indicating that this topic is predominantly published in scholarly journals. Publication trends reveal significant growth since 2016, peaking in 2024, reflecting increasing global interest. Education Sciences and IEEE Access are among the top journal sources. Subject-wise, social sciences and computer science are the main disciplines exploring AR in mathematics education. Chitkara University (India) and Johannes Kepler University Linz (Austria) are leading institutions, while the United States, Malaysia, and Spain contribute the most publications. Keyword analysis shows rapid growth in research using terms such as "augmented reality" and "mathematics education," emphasizing the role of immersive technology in enhancing student engagement and conceptual understanding through visual and interactive learning. Influential authors like Lavicza, Mantri, and Haas highlight the importance of global collaboration. Based on a thematic analysis of the most-cited articles, this study proposes the AI Mathematical Education Impact and Outcome Framework. In conclusion, although research on AR in mathematics education has significantly advanced, further studies are needed to evaluate its effectiveness across varied educational contexts.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

The present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.

This study investigated the relationships between conflict management strategies and family functioning among university students from diverse ethnic backgrounds in the multicultural context of Kosovo. A cross-sectional design was used with 362 university students (183 female, 179 male) comprising Kosovo Turks (58.6%), Albanians (23.8%), and Bosnians (17.7%). Data were collected using the Conflict Management Strategy Scale and Family Assessment Device. Path analysis was used to examine relationships between conflict strategies and family functioning dimensions. Students preferred compromising strategies most (M = 3.68) and withdrawing least (M = 2.98). Family functioning was healthy in problem-solving, communication, roles, affective responsiveness, and general functioning (scores < 2.0), but unhealthy in affective involvement (M = 2.29) and behavioral control (M = 2.12). Significant ethnic differences emerged in communication (F(2,144) = 3.158, p = .045, η² = .020) and behavioral control (F(2,149) = 4.109, p = .018, η² = .018), but not in conflict strategies. Path analysis revealed that withdrawing strategies negatively affected family functioning (β = .113-.143), while smoothing strategies had positive effects (β = -.139 to -.220). However, conflict strategies explained only 1.6-4.3% of the variance in family functioning (R² = .016-.043), indicating small effect sizes. While statistically significant relationships exist between conflict management strategies and family functioning, effect sizes are modest. Ethnic variations in these relationships emphasize the importance of cultural considerations for family counseling practices. The findings suggest that conflict management training may have a limited direct impact on family functioning, highlighting the need for comprehensive, culturally sensitive intervention approaches.

The current study sought to evaluate the impact of programs used to enhance the self-regulation and social interaction for children with Autism Spectrum Disorders (ASD), as perceived by their families. The descriptive approach was used to collect and analyze data and derive conclusions after developing the study instruments. The study sample consisted of 150 families of children with ASD enrolled in special education centers in Amman, Jordan. The study participants were purposefully selected to respond to the two provided measurement scales. To measure the impact of the intervention programs, the researchers developed the Self-Regulation Behavior Scale and the Social Interaction Scale, ensuring the validity and reliability of both scales. The results of the study indicated that from the families’ perspective, programs for children with ASD had a moderate impact on enhancing self-regulation and a high impact on social interaction. Additionally, the findings of the study revealed statistically significant differences in the degree of improvement in self-regulation and social interaction behaviors related to the child’s gender and the severity of their disorder. However, no statistically significant differences were found related to the child’s age and gender in their level of improvement in self-regulation and social interaction behaviors.

This preliminary study examines how three generative AI tools, ChatGPT-4, Google Gemini, and Microsoft Copilot, support B+ level English as a Foreign Language (EFL) students in opinion essay writing. Conducted at a preparatory school in Türkiye, the study explored student use of the tools for brainstorming, outlining, and feedback across three essay tasks. A mixed methods design combined rubric-based evaluations, surveys, and reflections. Quantitative results showed no significant differences between tools for most criteria, indicating comparable performance in idea generation, essay structuring, and feedback. The only significant effect was in the feedback stage, where ChatGPT-4 scored higher than both Gemini and Copilot for actionability. In the brainstorming stage, a difference in argument relevance was observed across tools, but this was not statistically significant after post-hoc analysis. Qualitative findings revealed task-specific preferences: Gemini was favored for clarity and variety in brainstorming and outlining, ChatGPT-4 for detailed, clear, and actionable feedback, and Copilot for certain organizational strengths. While the tools performed similarly overall, perceptions varied by task and tool, highlighting the value of allowing flexible tool choice in EFL writing instruction.