ABSTRACT While the relationship between teacher attributes and the motivation and achievements of language learners has been extensively studied in the past decades, the relevant research that addresses the evolving educational context of China has been relatively limited. This study fills this knowledge gap by identifying distinctive attributes of English teachers shaped by China's traditional and modern educational context. These attributes are categorised into three main groups: teacher attitudes, teaching performance and teacher–student interaction. In this mixed‐methods study, a questionnaire on teacher attributes was designed to survey the perceptions of 417 students regarding what teacher attributes they found motivating. Qualitative data was obtained from semi‐structured interviews with 36 students. We explored the teacher attributes perceived as motivational by the students, considering the backdrop of cultural factors and educational policies in China. The findings revealed not only internationally recognised motivating attributes but also teacher attributes particular to the Chinese context. These perceptions can guide educators in providing both effective and enjoyable language learning experiences in the given cultural context, while also informing school authorities in designing teacher training programmes and evaluation systems. The findings are also valuable and enlightening in other Asian countries, where exam‐oriented education and Confucian heritage prevail.

There has recently been a pronounced global escalation in scholarly output concerning Artificial Intelligence (AI) within the context of higher education (HE). However, the precise locus of this growth remains ambiguous, thereby hindering the systematic integration of critical AI trends into HE practices. To address this opacity, the present study adopts a rigorous and impartial analytical approach by synthesizing datasets from the Web of Science (WoS) and Scopus through the Biblioshiny platform. In addition, independent examinations of WoS and Scopus data were conducted using co-occurrence network analyses in VOSviewer, which revealed comparable patterns of cluster strength across both datasets. Complementing these methods, Latent Dirichlet Allocation (LDA) was employed to extract and interpret thematic structures within locally cited references, thereby providing deeper insights into the extant research discourse. Findings revealed significant acceleration patterns from 2023 concerning publication trends, annual growth patterns, cited references, top authors, leading journals, and leading countries. Patterns of strengths from co-occurrence networks in VOSviewer revealed growing interest in generative AI tools, AI ethics, and concerns about AI integration into the curriculum in HE. The LDA analysis identified two dominant themes: the pedagogical integration of generative AI tools and broader academic discourse on AI ethics that correlated with the VOSviewer findings. This enhanced the credibility, reliability, and validity of the bibliometric techniques applied in the study. Recommendations and future directions offer valuable insights for policymakers and stakeholders to address pedagogical integration of generative AI tools in HE. The development of frameworks and ethical guidelines are important to address fair and transparent adoption of AI in HE. Further, global inequalities in adoption, aligning with UNESCO’s Sustainable Development Goals, are crucial to ensure equitable and responsible AI integration in HE.

Transformational leadership is believed to enhance motivation and performance; however, it is essential to evaluate the efficacy of the high school principal's leadership style in motivating teachers, particularly in the integration of technology and the resolution of digital learning challenges. This study analyzes and empirically tests the principal's transformational leadership style on teacher performance at High School 2 Takalar, especially in the digital age when technology adaptation and learning innovation are crucial. This study uses a quantitative approach with an associative explanatory survey design. The total number of teachers at High School 2 Takalar is 78, with 21 men and 57 women. The research sample was determined using the Slovin Formula with a tolerance level of error of 10% (e = 0.10), resulting in a minimum of 44 respondents. Data was collected through a closed questionnaire and analyzed using simple linear regression statistical techniques. The study found a positive and significant relationship between principal transformational leadership and teacher performance. Teacher performance in technology adaptation, learning innovation, and main task implementation improved significantly with increased transformational leadership dimensions like idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. This research endorses the transformational leadership model within the context of 21st-century education characterized by digital predominance. This case study offers practical advice for High School 2 Takalar's principal and other educators on how to use transformational leadership to boost teacher professionalism and performance in the digital age.

BackgroundArtificial intelligence (AI) is reshaping the landscape of medical education with unprecedented depth and breadth. As technologies like large language models and natural language processing advance, AI agents with multimodal interaction capabilities—such as intelligent teaching assistants and virtual simulation labs—are demonstrating immense potential. Concurrently, medical students face challenges including a disconnect between theoretical knowledge and clinical practice, excessive cognitive load, and a lack of personalized practical opportunities. Medical education AI agents are poised to address these issues, but their successful integration hinges on student acceptance and adoption. This study aims to fill a gap in the current empirical research by investigating the key psychological mechanisms and behavioral factors that influence medical students’ adoption of AI educational agents.MethodsThis study constructed an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model by integrating four key variables tailored to the medical education context: AI Trust, Perceived Risk, Hedonic Motivation, and Trialability. A cross-sectional survey was conducted with an initial sample of 200 clinical medicine students following their interaction with a custom-developed interactive medical education AI agent. After excluding invalid responses, a final valid sample of 155 participants was retained. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to validate the theoretical model and test the research hypotheses.ResultsThe constructed model demonstrated strong explanatory power, successfully accounting for 85.3% of the variance in students’ behavioral intention (R² = 0.853). Effort Expectancy (β = 0.362, p < 0.001) and Performance Expectancy (β = 0.297, p < 0.001) were the strongest direct positive predictors of behavioral intention, with Facilitating Conditions (β = 0.258, p = 0.002) also showing a significant impact. A noteworthy finding was that Social Influence had no significant effect on behavioral intention (β = 0.038, p = 0.633). Furthermore, Hedonic Motivation had a significant positive influence on both Effort Expectancy (β = 0.818, p < 0.001) and Performance Expectancy (β = 0.237, p < 0.001). AI Trust, Trialability, and lower Perceived Risk also significantly enhanced students’ Performance Expectancy.ConclusionsThe findings indicate that for medical students, who are highly autonomous professional learners, the intrinsic value of an AI educational tool (i.e., its utility and ease of use) is the dominant factor in their adoption decisions, far outweighing the social influence of peers or authorities. Therefore, the key to successfully promoting such technologies lies in building users’ intrinsic trust, reducing their perceived risks, and providing an engaging, immersive learning experience. These findings provide a solid empirical basis for the optimal design of medical AI educational agents and for strategies to effectively integrate them into the curriculum.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12909-025-08234-z.

Human-AI interaction, particularly in educational contexts, is a dynamic and cognitively demanding process that holds promise for enhancing goal-directed learning. Yet, there remains a scarcity of empirical studies that examine how learners’ interaction with generative AI (GenAI) varies in structure and how these patterns influence distinct learning outcomes. This study investigates the relationship between human-AI interaction processes and outcomes such as AI literacy, problem-solving skills, metacognitive strategies, and task performance. We conducted an experimental study with 45 secondary school physics student teachers engaged in a GenAI-supported lesson plan assessment task. Using questionnaire responses, trace data, and prompt logs, we coded human-AI interaction behaviours based on self-regulation and cognitive processing levels. Through sequence clustering analysis, we identified two distinct interaction patterns. Both clusters showed significant improvement in task performance, but with divergent benefits. Cluster 1 exhibited diverse regulation processes characterized by exploratory, divergent prompting and low-level cognitive engagement in the early stages. This group showed significant gains in problem-solving skills through active idea generation and broad reflection. Cluster 2 demonstrated structured regulation behaviours, initiating interaction with deep-level cognitive processing and convergent prompting. These learners made more deliberate modifications and completed full self-regulated learning (SRL) cycles—planning, monitoring, and reflecting—which led to enhanced AI literacy and metacognitive strategy use. Our findings suggest that effective human-AI collaboration goes beyond prompt diversity; structured regulation behaviours serve as a key mediator between prompting and learning gains. GenAI served as both cognitive and metacognitive scaffolding, facilitating critical assessment and productive delegation. These results contribute to SRL theory in AI contexts and emphasize the importance of process-level analysis. Limitations include a small sample and limited prompt feature analysis. Future research should explore emotion-aware AI systems, multimodal interaction data, and the impact of task complexity on interaction dynamics. This study provides practical insights for educators and designers of AI-integrated learning systems. Specifically, it highlights the importance of tailoring AI scaffolds to different learner regulation styles: for exploratory learners, scaffolds can encourage broad idea generation and reflection, while for structured learners, scaffolds should support iterative planning and monitoring. These findings underline both opportunities and limitations of current GenAI use in classrooms, suggesting concrete directions for teacher practice and instructional design.

This mixed study explores the impact from reflective journal writing upon students' interpreting anxiety. It draws on data sources from students' reflective journals written during the semester as well as two questionnaires of Anxiety Scale for Chinese Interpreting Learners. The study focuses on three dimensions of interpreting anxiety, namely task anxiety, error anxiety and confidence anxiety. Task anxiety has been significantly alleviated over the course, while the other two have not. The cognitive–affective–behavioral intervention mechanism identified in students' reflective journals, functions effectively in mitigating interpreting anxiety. The study also reveals how instructed reflective journals enable students to perceive themselves as self-motivated and sustainable learners. This study holds important pedagogical implications for educators in language teaching and other educational context.

This study explores university lecturers’ perceptions and experiences in implementing the Critical Literacy Approach (CLA) in teaching Critical Reading within the context of Indonesian higher education. In contrast to most previous research that focused on students’ learning outcomes or curriculum design, this investigation centers on lecturers’ pedagogical agency and their contextual adaptations of CLA. Using a descriptive qualitative case study design, three lecturers from different universities participated in in-depth interviews and semester-long classroom observations. Thematic analysis revealed that lecturers’ entry into critical literacy emerged through distinct pathways: self-directed study, reflective classroom practice, and formal graduate education. These trajectories informed how each lecturer interpreted and modified CLA that ranging from integrating discourse analysis and media literacy to using literature for social critique. Despite methodological variations, all lecturers shared a strong commitment to cultivating students’ critical thinking and sociopolitical awareness. However, the implementation was not without challenges: emotional discomfort around sensitive topics, student disengagement, and limited instructional time frequently emerged. Even so, the lecturers employed adaptive strategies to sustain dialogue and scaffold critical reflection. These findings highlight that effective CLA practice depends not only on theoretical understanding but also on emotional intelligence, contextual sensitivity, and institutional support. By foregrounding lecturers’ voices, this study contributes a practice-oriented perspective on critical literacy, urging a reorientation of research and policy to recognize educators as key agents of critical pedagogy in Indonesian higher education.

Background Anxiety and depression are highly prevalent among pre-university students, often intensified by the academic stress associated with entrance exams. Linguistic analysis of written texts offers a promising, non-invasive approach for early detection and prevention. Study design: Cross-sectional study. Objectives To examine the association between linguistic features in essays and levels of anxiety and depression, identifying specific language patterns linked to these conditions. Setting Pre-university preparatory courses in São Paulo, Brazil, in 2023. Methods Participants were 62 pre-university students (51 females, 11 males; M = 20.3 years, SD = 2.65) who completed a self-report form shared via WhatsApp or in-person at preparatory schools. The form included sociodemographic questions, the GAD-7 and PHQ-9 scales, and the upload of an argumentative essay written within the previous month as part of their regular coursework. Essays were analyzed using LIWC software, and multivariate regression models identified linguistic features associated with anxiety and depression scores. Results Higher anxiety levels correlated with increased use of words related to affiliation and home, and decreased use of leisure and money-related terms. Depression was associated with higher frequency of drives and number-related words, and fewer motion-related terms. Conclusion Linguistic analysis can assist in identifying emotional distress among pre-university students, offering a potential tool for early screening and intervention in educational and mental health contexts.

Abstract In India’s multilingual higher education system, language use reflects complex negotiations between institutional policies, social hierarchies, and identity practices. Within this context, translanguaging, understood as the strategic use of a multilingual speaker’s full linguistic repertoire offers a valuable framework for examining how individuals navigate these linguistic and social dynamics. However, limited research has examined how institutional structure and gender shape such translanguaging behaviours within Indian universities. This study investigates how institutional type and gender affect translanguaging among 522 university students across India. Drawing on data from both public and private institutions, it analyses language use across three domains: home, social and public, and academic and professional environments. The analysis employs Chi-square tests of independence to examine associations between institutional type, gender, and language use. The findings reveal that students from private institutions engage more frequently in English-dominant translanguaging, particularly in social and academic-professional environments, whereas female students demonstrate stronger maintenance of heritage languages within the home domain. These patterns highlight how institutional language policies and gendered expectations mediate multilingual behaviour in higher education. The study positions translanguaging as both an index of sociocultural identity and an adaptive communicative practice. It contributes to ongoing discussions on linguistic repertoires, social positioning, and multilingual agency in Indian educational contexts.

Background/Objectives: School violence represents a significant concern for educational communities worldwide, affecting student well-being and academic development. While prior research has documented prevalence rates and risk factors, limited studies have examined social–cognitive factors associated with antisocial behavior specifically within vocational education contexts using integrated analytical approaches. This exploratory cross-sectional study examined social–cognitive factors—specifically self-reported attitudes about aggression norms, prosocial attitudes, and school climate perceptions—associated with violence-supportive attitudes among Greek vocational students. Methods: A cross-sectional design employed validated self-report instruments and traditional statistical methods. The sample comprised 76 vocational high school students (38.2% male; ages 14–18; response rate 75.2%) from one school in Patras, Greece. Validated instruments assessed attitudes toward interpersonal peer violence (α = 0.87), peer aggression norms across four subscales (α = 0.83–0.90), and school climate dimensions (α = 0.70–0.75). Analyses included descriptive statistics, Pearson correlations with bootstrapped confidence intervals, MANOVA for multivariate group comparisons, independent samples t-tests, propensity score matching for urban–rural comparisons, polynomial regression for developmental patterns, and path analysis for theoretical model testing. Results: Strong associations emerged between perceived school-level and individual-level aggression norms (r = 0.80, p &lt; 0.001, 95% CI [0.71, 0.87]), representing one of the strongest relationships documented in school violence research. Violence-supportive attitudes demonstrated inverse associations with prosocial alternative norms (r = −0.37, p &lt; 0.001, 95% CI [−0.55, −0.16]). Significant gender differences emerged for teacher–student relationships (d = −0.78, p = 0.002), with females reporting substantially more positive perceptions. Propensity-matched urban students demonstrated higher aggression norm endorsement compared to rural students across multiple indicators (d = 0.61–0.78, all p &lt; 0.020). Polynomial regression revealed curvilinear developmental patterns with optimal teacher relationship quality during mid-adolescence (ages 15–16). Path analysis supported a sequential association model wherein school-level norms related to individual attitudes through prosocial alternative beliefs (indirect effect β = −0.22, p = 0.002, 95% CI [−0.34, −0.11]). Conclusions: This preliminary investigation identified social–cognitive factors—particularly normative beliefs about aggression at both individual and environmental levels—as strongly associated with violence-supportive attitudes in Greek vocational education. The exceptionally strong alignment between school-level and individual-level aggression norms (r = 0.80) suggests that environmental normative contexts may play a more substantial role in attitude formation than previously recognized in this educational setting. Gender and urban–rural differences indicate meaningful heterogeneity requiring differentiated approaches. Future research should employ longitudinal designs with multi-informant assessment and larger multi-site samples to establish temporal precedence, reduce method variance, and test causal hypotheses regarding relationships between normative beliefs and behavioral outcomes.

This study examined predictors of work task motivation among secondary-school teachers in Bengaluru, India—a rapidly urbanizing education context marked by diversity and workload challenges. Survey data from 756 teachers were analyzed using multiple regression models. Instructional design explained the largest variance in motivation ( R 2 = 25.1%), followed by affirming school environments ( R 2 = 23.2%) and teachers’ social–emotional competence ( R 2 = 15.2%). Key predictors included social–emotional instruction (β = .312), cooperative learning (β = .170), warmth and support (β = .299), and social awareness (β = .198). Female teachers showed stronger motivation in collaborative settings, and experienced educators benefited more from supportive climates. Findings align with OECD and UNESCO evidence emphasizing that supportive environments and structured pedagogy are central to sustaining teacher motivation and retention.

The study evaluates whether and to what extent the Teaching at the Right Level (TaRL) intervention improves students’ learning in mathematics across cognitive, affective, and psychomotor domains. This study employed a pre-experimental one-group pre-test/post-test design, in which a single cohort of 35 Grade XI students at Senior High School I, Takalar, South Sulawesi, Indonesia, was assessed before and after the implementation of the TaRL approach. Data were gathered using pre- and post-tests to measure cognitive improvement. The cognitive, affective, and psychomotor domains were assessed with structured observation sheets using a five-point Likert scale, which were then transformed to a 0-100 scale for clarity of interpretation. The result showed a significant increase in students’ cognitive achievement, with the pre-test and post-test means of 83.42 and 93.22, respectively. Although the initial score was relatively high due to students’ prior exposure to similar mathematical content, the statistical results confirmed a meaningful improvement beyond the baseline understanding. Observations of the affective domain revealed notable positive shifts; students demonstrated higher motivation, increased confidence in problem-solving, and more active participation during class activities, as reflected in an average converted score of 95.31. In the psychomotor domain, the mean score of 93.21 demonstrated students’ enhanced ability to apply mathematical concepts in practical contexts through active engagement. These findings suggest that the Teaching at the Right Level (TaRL) approach effectively enhances students’ learning outcomes within the studied context by promoting active, differentiated, and student-centered learning experiences. Since the study was conducted at a single institution with a small sample, additional research with larger populations and diverse educational contexts is necessary to substantiate and generalize these findings. Keywords: affective, cognitive, mathematics, psychomotor, teaching at the right level (TaRL).

This study investigated the effectiveness of computer simulations on students’ academic performance in the topic of evolution in the Biology subject in secondary schools in Tanzania. A quasi-experimental research study design was employed, involving two schools with a sample of 191 students that were divided into experimental and control groups. The experimental groups received instructions using computer simulations while the control groups were taught using traditional teaching methods. Pretest and posttest scores were collected and analyzed using descriptive statistics, and paired samples t-test and independent samples t-test were used to measure performance variations. The results showed a significant gain in the posttest scores for both the control and experimental groups; however, the magnitude of the t-value (t = -32) for the experimental group was higher, reflecting a much stronger effect on students’ performance compared to the control group (t = -16), the gain in the experimental group is attributed to the additional advantage of the experimental group suggests that the computer simulations provided a unique learning benefit by fostering understanding through visualization of various topic phenomena. The gain in the control group may also be attributed for by teacher explanations, practice effects, increased familiarity with the test content, the use of various classroom activities, and individual teacher creativity. The study found no significant disparity in the performances based on gender. These findings show the potential of integrating computer-assisted instruction in science education, especially in areas with limited resources. The study recommends the adoption of Computer technologies in educational contexts to foster dynamic learning.

The rapid multimodal development of Generative AI (GenAI) tools has opened up possibilities for content creation in many fields. This paper presents a study that had a focus on image generation for educational contexts and professional development in a course on artificial intelligence for education and work life. In an assignment, participants used different GenAI tools for image generation. Moreover, course participants analysed and discussed their AI generated images in essays. In the wide variety of GenAI tools two different image generation software were suggested, one from a big established IT company and the other from a small independent software developer. Both these tools were chosen because they are free to use without any licence fees, and that there are not any complex login procedures before using them. This was seen as important criteria for a group of course participants with relatively low pre-knowledge of GenAI and image generation. On the other hand, course participants with earlier experience of were allowed to use other and more advanced tools. Images could be generated individually or in groups, but the final analysis essays had to be written individually without any AI assistance. Four portraits should be generated with each tool of two world-wide well-known persons, one locally known person and a portrait of the course participant that wrote the essay. 61 essays were thematically analysed with the use of open coding and axial coding. Results were divided into the categories of Age, Gender and Ethnicity, Language, Guardrails, and Training data, with Training data as the central or axial category. Findings show that the results to a certain degree are depending on prompting and the language, but that the found bias is depending on the training data.

Democratic management is a fundamental principle of Brazilian education, highlighting the importance of the participation of the entire school community in planning and decision-making. This study analyzes the process of elections for principals in municipal public schools in Ariquemes, Rondônia, with the aim of evaluating its contribution to the implementation of democratic management in the educational context. Direct elections for principals are one of the mechanisms that seek to ensure greater transparency, representation, and involvement of students, parents, teachers, and staff. The research uses a documentary and bibliographical analysis, based on legislation, official documents, and specialized literature such as books and articles that address democratic management and electoral processes in educational environments. Among the expected results are the identification of good practices and challenges in the electoral process, as well as proposals to strengthen the participation of the school community and improve democratic management in schools. It is concluded that, despite representing a significant advance in the democratization of educational management, direct elections have deactivated adjustments in criteria, procedures, and engagement policies to maximize their effectiveness as an instrument of inclusion and transparency in school decisions. These insights may contribute to the formulation of more effective educational management strategies in Ariquemes-RO.

Enhancing teachers’ performance and sense of fulfillment in their roles is essential for advancing educational quality and promoting their overall well-being. This study investigates the determinants of teachers’ self-efficacy within a supportive school culture, as well as the factors influencing their job satisfaction, focusing on both educational and personal contexts among public elementary school teachers within a supportive school culture, focusing on educational and personal contexts. Utilizing a sample of 97 teachers from 13 schools in the Philippines, the research employs a causal-comparative design and surveys to gather data. The Kruskal-Wallis test results indicate no significant differences in self-efficacy and job satisfaction across age groups. The Mann-Whitney U test reveals a significant difference in self-efficacy between male and female teachers, with the latter reporting higher levels, while no significant gender differences were observed in job satisfaction. Likewise, no significant differences were found across career stages in both efficacy and satisfaction. A multivariate analysis of variance reveals that a supportive school culture has a significant impact on teachers’ self-efficacy and also on their job satisfaction. These results emphasize the critical role of nurturing a supportive school environment to enhance teacher well-being and effectiveness. The study provides valuable insights and practical recommendations for improving educational quality and teacher satisfaction through targeted interventions in school culture and opportunities for career advancement.

A mixed-methods framework for assessing differentiated instruction implementation barriers in EFL secondary education contexts.

Introduction: Physical Education plays a fundamental role in the development of socio-emotional competences, contributing to the improvement of school coexistence within the educational context. These skills are essential to ensure the overall well-being of pupils, fostering their interpersonal development and enhancing academic performance. Objective: To analyse, through a systematic review, how Physical Education promotes socio-emotional development and strengthens school coexistence. Methodology: An exhaustive search was conducted in the databases Scopus, WoS, SciELO, and Dialnet, considering studies published between 2012 and 2025 in Spanish and English. The inclusion criteria focused on the relationship with the subject, socio-emotional skills, and school coexistence. After applying methodological and thematic filters, 10 scientific studies were selected. Results: The findings reveal significant improvements in competences such as emotional self-regulation, empathy, cooperation, and problem-solving. Furthermore, Physical Education programmes are consolidated as an effective pedagogical resource for promoting an inclusive, cooperative, and respectful school climate. Conclusion: Physical Education constitutes a key pedagogical tool to enhance pupils’ socio-emotional development and optimise school coexistence.

&lt;span lang="EN-US"&gt;The scarcity of reliable tools to measure attention control among Arabic speaking learners represents a key research problem. To address this gap, this study aimed to develop and evaluate the Arabic version of the attention control scale (ACS). The research was conducted on a sample of (N=210) Moroccan students in their second year of middle school (2023/2024), using precise translation methods, including “forward and backward translation”. The reliability of the scale was confirmed through Cronbach’s alpha (α=0.832), McDonald’s omega (Ʊ=0.820), and split-half reliability (ρ=0.870). The factor structure of the scale was verified using principal component analysis (PCA), while confirmatory factor analysis (CFA) confirmed the model’s goodness of fit (χ²=1689.398, df=66, *p&amp;lt;.001; Kaiser-Meyer-Olkin (KMO)=0.672). The results showed statistically significant correlations between the scale’s dimensions: general attention control (GA), attention focusing (AF), and attention shifting (AS) (*p&amp;lt;.001). The findings confirmed that the 12 item Arabic version of the ACS (short version) has strong psychometric properties with factor loadings ranging from 0.311 to 0.825. This study is considered an important step in developing attention assessment tools for learners in the Arab educational context. It provides a standardized scale to measure the attention process, which helps enable teachers to accurately diagnose attention difficulties and provide targeted educational interventions. These interventions contribute to improving learners’ focus and engagement, thereby enhancing the overall effectiveness of the educational process.&lt;/span&gt;

NEW & NOTEWORTHY The proposed metacurriculum tackles the persistent "bioscience problem" by teaching students how to learn. It embeds self-regulated learning (SRL) strategies across all phases of the physiology learning cycle and uses low-stakes assessment and retrieval practice to reinforce learning. This approach is designed to improve self-efficacy, engagement, and achievement in bioscience.