Teacher flourishing and burnout have often been viewed as opposing work experiences, implying that higher levels of one should be accompanied by lower levels of the other. However, recent research suggests that these experiences can coexist within the same individual. We extend this line of research by using latent profile analysis to examine how multiple dimensions of flourishing and burnout combine in different ways among 5694 primary and secondary school teachers in China. Five profiles were identified: Broadly Adaptive (61.19%), Struggling (19.41%), Engaged–Strained (8.96%), Unfulfilled (6.29%), and Depleted–Disconnected (4.16%). Broadly Adaptive and Struggling teachers followed the expected inverse pattern between flourishing and burnout. In contrast, Engaged–Strained teachers maintained moderate levels of flourishing and relatively high personal accomplishment despite substantial emotional exhaustion and depersonalization; Unfulfilled teachers showed favorable flourishing and low exhaustion and depersonalization but extremely low personal accomplishment; and Depleted–Disconnected teachers showed particularly poor emotional and social well-being alongside elevated exhaustion. These findings advance our understanding of teacher flourishing and burnout beyond a single-continuum model, although sensitivity analyses indicated that the retained profile solution was sensitive to the composition of the personal accomplishment measure, particularly for the Struggling and Unfulfilled profiles. Rather than asking simply whether teachers are flourishing or struggling with burnout, schools may benefit from asking in what areas teachers are feeling or functioning well and in what areas they are struggling.

Understanding learners’ conceptions of artificial intelligence (AI)-supported learning can inform the sustainable integration of AI into education. This study examined primary school students’ conceptions of large language model-based (LLM-based) chatbots-supported learning and explored differences associated with learning motivation. Seventy-two students participated in learning activities designed around the CLEAR prompt-engineering framework. A mixed-methods approach combined the draw-and-write technique with questionnaires assessing learning motivation, self-efficacy, and critical thinking tendencies. Students represented LLM-based chatbots as resources supporting a range of learning activities. Exploratory comparisons indicated motivation-related differences in the representation of learning content, usage times, and locations. Students with lower learning motivation more frequently depicted specific learning content and home-based use, whereas those with higher learning motivation more frequently depicted classroom-based use. Students with higher learning motivation also reported significantly higher self-efficacy, while no statistically significant between-group difference was found in critical thinking tendencies. By integrating young learners’ draw-and-write representations with questionnaire data and motivation-based comparisons, this study extends existing research by providing learner-centered evidence on how primary school students conceptualize LLM-based chatbot-supported learning and how these conceptions vary according to learning motivation. The findings may inform differentiated instructional guidance and learner-responsive task design that support purposeful and responsible AI use, contributing a learner-centered perspective to the development of inclusive and sustainable AI-enhanced learning environments.

Attention plays a central role in intellectual development and social interaction. Attention may differ between deaf and hearing youth, but it remains unclear whether such differences reflect hearing status, language experience, age-related factors, or some combination of these factors. In this cross-sectional study, we combined the Attention Network Test with comparisons of alternative age functions, age-stratified analyses, and EZ-diffusion modeling using data from 525 participants aged 6–19 years (200 deaf and 325 hearing). Both groups performed similarly during childhood, and alerting showed no reliable cross-sectional association with age, with no reliable difference between groups. In both groups, executive-control costs were smaller at older ages. The Bayesian information criterion (BIC) favored a linear age function for deaf participants and a logarithmic function for hearing participants. Crucially, however, the formal Group × Age interaction was not significant; the difference in functional form should therefore be treated as descriptive. By contrast, orienting was linearly related to age among deaf participants but followed a decelerating quadratic pattern among hearing participants; the Group × Age interaction was significant. Deaf participants also showed smaller benefits from spatial cues during early and middle adolescence. EZ-diffusion modeling further indicated that conflict produced a larger reduction in drift rate and a larger increase in non-decision time among deaf than among hearing participants, whereas conflict-related boundary adjustments were comparable between groups. Together, these findings suggest that deaf and hearing youth differ in visual attention in a network-specific, age-related manner rather than exhibiting either a generalized deficit or a generalized compensatory advantage. Because hearing status, language experience, and educational context were intertwined in this sample, the observed group differences cannot be interpreted as causal effects of deafness or auditory deprivation.

Severe occupational burnout among inclusive teachers poses a significant threat to building resilient and sustainable inclusive education systems. In the context of educational digital transformation, digital literacy emerges as a vital resource with the potential to reduce excessive job demands. However, the underlying pathways of this protective role remain underexplored. Addressing whether technological empowerment can effectively sustain inclusive educators, this study examined the serial mediating roles of time poverty and inclusive teaching efficacy in the relationship between digital literacy and teacher burnout. Based on a cross-sectional sample of 492 Chinese inclusive teachers, observed-variable path analysis was used to test the theoretical model across three core dimensions of occupational burnout. The results confirmed a full serial mediation model: digital literacy yielded no significant direct association with burnout; instead, its negative relationship with burnout was fully accounted for by lower time poverty and higher inclusive teaching efficacy. Furthermore, heterogeneous indirect pathways emerged across the burnout core dimensions: the indirect link to emotional exhaustion operated exclusively through perceived time poverty, whereas depersonalization and personal accomplishment were associated with both time poverty and teaching efficacy via independent and serial indirect paths. Although this cross-sectional design precludes inferring strict temporal sequences among the variables, these findings indicate that mere technical proficiency is insufficient to sustain teachers’ professional well-being. To effectively alleviate burnout among inclusive educators, digital literacy development must translate into tangible time savings and rebuild their confidence in inclusive teaching practices, thereby sustaining a healthy and effective inclusive teaching workforce.