Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

Mindfulness, recognized as a protective factor against learning burnout in higher education, has garnered considerable attention, yet its underlying mechanisms remain underexplored. This study examined the relationship between mindfulness, regulatory emotional self-efficacy, and learning burnout. Data from 461 Chinese university students were collected using a correlational design and cluster sampling method, employing the Five Facet Mindfulness Questionnaire, University Student Learning Burnout Scale, and Regulatory Emotional Self-Efficacy Scale. Hypotheses were tested using partial least squares structural equation modeling. Results showed that Participants exhibited above-average mindfulness (M=3.090), learning burnout (M=3.278), and regulatory emotional self-efficacy (M=3.417). Results revealed that mindfulness is directly and negatively related to learning burnout (β=-0.679, t = 28.657, p < .001). Regulatory emotional self-efficacy (β = -0.357, t = 8.592, p < .001) was significantly and negatively related to learning burnout. Mindfulness was significantly and positively related to regulatory emotional self-efficacy (β = 0.638, t = 24.306, p < .001), and regulatory emotional self-efficacy (R2: from .461 to .537) partially mediated the relationship between mindfulness and learning burnout. Besides, the Importance-Performance Matrix Analysis revealed that managing negative emotions significantly contributes to learning burnout but performs poorly, whereas non-reacting demonstrates both the lowest contribution and performance. Findings suggest that mindfulness indirectly alleviates learning burnout through regulatory emotional self-efficacy, providing evidence-based insights for targeted mindfulness interventions in higher 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 presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by persistent challenges in language acquisition, particularly in the lexical and semantic domains. This study examined the effectiveness of an adapted Applied Behavior Analysis (ABA) intervention in improving lexical and semantic language skills among preschool-aged children with ASD. A total of 3- to 6-year-old children participated, divided into experimental and control groups across two specialized centers. The experimental group received an adapted ABA-based program emphasizing discrete trial teaching, functional communication strategies, visual supports, and targeted reinforcement techniques. Pre- and post-intervention assessments were conducted using a structured methodology that evaluated active and passive vocabulary, semantic categorization, and contextual language use. Results from paired t-tests showed statistically significant improvements in the experimental group compared to the control group (p < .05). Despite these gains, generalization of language skills across social contexts remained limited. These findings highlight the value of individualized behavioral interventions and support their inclusion in early childhood programs for children with ASD.

This study examines the emotional labor of early childhood educators and its relationship with interactions involving children and parents, with a focus on emotional regulation and demographic influences. This study aimed to investigate the impact of emotional regulation strategies and demographic variables on educators’ emotional well-being during professional interactions. A quantitative approach was adopted, with data collected through structured questionnaires. The analysis concentrated on emotion suppression and surface acting in relation to well-being. Results indicated that teachers experienced considerable emotional burden, with emotion suppression being more prevalent than surface acting, particularly in interactions with parents. Fifty-three percent of educators reported a high emotional burden in parent-related suppression, compared to 38% in interactions with children. Additionally, 38% reported high suppression in self-regulation, while 29% experienced no burden from surface acting. Emotion suppression in parent interactions had the most significant impact on well-being (standardized coefficient = 0.4044, p < .001), followed by education level (coefficient = 0.1646, p < .001). Factors such as generation, teaching experience, salary, and certification were not statistically significant. The model explained 18.7% of the variance in emotional well-being. These findings align with existing literature that highlights the emotional burden of teaching and the psychological toll of unaddressed regulation challenges. Therefore, culturally and contextually appropriate suppression-management training, together with enhanced institutional support, is essential to reduce the emotional burden on Indonesian early childhood educators.

The evaluation of Service-Learning (S-L) projects in online environments has become increasingly relevant in educational research, at the same time as the importance of using mixed methods has risen. However, there are few studies focusing on the evaluation of virtual Service-Learning, as most studies concentrate on face-to-face Service-Learning projects. In this regard, the aim of the present research is to assess three Virtual Service-Learning (vS-L) projects using a blended (quantitative-qualitative) evaluation method, also conducted online. The evaluation was conducted by students from the National University for Distance Learning, who completed a questionnaire asynchronously and participated in synchronous focus groups within their respective groups. Data were arranged in a mixed panel (questionnaire items and focus group verbatim opinions). The questionnaires demonstrated that Service-Learning is an excellent methodology to broaden students’ skills, abilities, and competencies to better face the professional world. The focus group verbatim interventions showed that the construction of indicators improves learning. Overall, the assessment results revealed a high level of student satisfaction. The implementation of our mixed-methods approach is innovative because it is conducted entirely online and utilizes computer technology for processing the gathered information.