Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors. The Picture Exchange Communication System (PECS) has been widely utilized to support communication in children with ASD by using picture cards to convey needs and responses. However, traditional PECS can be limited by its static nature and lack of immediate feedback. Recent technological advances, particularly Augmented Reality (AR), offer new avenues for enhancing these communication strategies. This study explores the integration of AR into PECS and its impact on improving basic communication skills, specifically answering questions and commenting, in children with ASD. The research involved a multiple baseline design with four participants aged 7-12 years, recruited from autism centers in Melaka, Malaysia. Results showed significant improvements in both the frequency and accuracy of responses and relevant commenting skills after the AR-based intervention. Answering skills improved by 83%, and commenting skills increased by 122%, with the average number of relevant comments rising from 3 (SD = 0.89) to 6.67 (SD = 2.25). Statistical analysis (paired t-test) revealed a significant effect (p = 0.00272). Compared to traditional methods, AR-based PECS accelerated the achievement of target communication skills. Future research should focus on larger sample sizes and explore long-term impacts to solidify these promising outcomes.

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.