Search Results (230)

Drawing on Self-Determination Theory, this study examines how perceived learning support, smartphone addiction, and user resistance jointly shape online learning outcomes among Chinese pre-service teachers. Data from 1134 participants enrolled in China’s government-funded targeted teacher education program-primarily oriented toward strengthening the supply of teachers for basic education, especially in central and western China, were analyzed using Mplus 8.3. The results showed that perceived learning support was positively associated with learning outcomes, whereas smartphone addiction was negatively associated with them. The role of user resistance was more complex in the full structural model and should therefore be interpreted with caution. Self-regulated learning (SRL) strategies served as a key mediator: perceived learning support improved learning outcomes partly by fostering SRL, while smartphone addiction hindered learning outcomes by weakening SRL. By examining a distinctive cohort of pre-service teachers, this study highlights the importance of supportive learning conditions and institutional context in online learning, and identifies SRL as a key learning process through which learning support and digital constraints are associated with learning outcomes. Full article

Generative artificial intelligence (GenAI) has been rapidly integrated into higher education, yet current studies largely rely on quantitative frameworks that capture initial adoption, leaving university EFL teachers’ motivational evolution for continued use of GenAI underexplored. To address this gap, this longitudinal qualitative study explores the motivational evolution and psychological need experience of 15 university EFL teachers’continued use of GenAI grounded in Self-Determination Theory (SDT). Data were collected through two rounds of semi-structured interviews over one year and analyzed in NVivo 11 PLUS. Our findings reveal a dynamic evolution of motivation from external regulation to value identification and professional identity integration. Crucially, need satisfaction and need frustration provide important psychological foundations for teachers’ motivation internalization. Notably, while need satisfaction directly facilitates university EFL teachers’ continued use of GenAI, need frustration can actually act as a potential catalyst that facilitates EFL teachers to form long-term continued use of GenAI through iterative reflection and instructional adjustment. This study extends the application of SDT within the GenAI education context, indicating that university EFL teachers’ continued use of GenAI is not merely a process of technology adoption, but also a process of professional growth and professional identity integration. The results provided preliminary implications for teacher professional development, GenAI design and education policy. Full article

As artificial intelligence (AI) becomes deeply integrated into teacher education, pre-service teachers’ innovative competence has become a cornerstone for fostering human–AI collaborative innovation and enabling intelligent educational transformation. This study used empirical data from 3003 pre-service teachers across 12 provinces in China. It employed difference tests, quantile regression, and structural equation modeling to examine the associations of AI technological support and school-based intelligent environment support with pre-service teachers’ innovative competence. Results showed that pre-service teachers’ innovative competence was at a medium-to-high level, with significant heterogeneity across individual, family, and school background variables. Both supports were positively associated with innovative competence. However, the patterns of association differed. The association between AI technological support and innovative competence generally increased across the middle-to-upper quantiles, whereas the association between school-based intelligent environment support and innovative competence was stronger at the lower-to-middle quantiles and subsequently declined. AI self-efficacy and self-regulated learning both showed significant model-based indirect associations linking the two supports with innovative competence. Specifically, under AI technological support, AI self-efficacy had a larger mediating association than self-regulated learning; under intelligent environment support, the opposite pattern emerged. This study systematically examined the associations and mediating paths of AI technological support and intelligent environment support with pre-service teachers’ innovative competence. These findings identify correlational patterns consistent with the proposed framework and provide empirical evidence for optimizing AI-empowered teacher innovation cultivation. Full article

Interdisciplinary dialogue between religion and psychoanalysis has long been regarded as an important approach to addressing modern psychological suffering. Erich Fromm sought to integrate Zen Buddhist practice with psychoanalytic reflections on integration of the unconscious, self-awareness, and personality, proposing a framework that links spiritual cultivation with psychological growth. However, this framework’s explanatory power and limitations in the contemporary Chinese context remain insufficiently explored through empirical research. Drawing on semi-structured interviews with 14 Chinese Zen practitioners in China, this study employs thematic analysis to examine their practices, psychological changes, and understandings of the relationship between Zen and mental health. Most participants regarded Zen practice as a long-term process involving cognitive reorientation, emotional regulation, and behavioral transformation, broadly resonant with Fromm’s integrative framework. However, the framework should not be treated as a directly applicable model of psychological intervention, as its practical relevance depends on sustained cultivation, community support, situated understanding, and clear professional and ethical boundaries. These qualitative findings underline potential risks when Zen cultural resources are introduced into contemporary mental health services, including decontextualization, instrumentalization, and an orientation toward immediate results. Therefore, within clearly defined ethical boundaries, a limited and responsible form of collaboration between Zen teachers and mental health professionals may be worth further exploration. Full article

While most research on biographical narratives has concentrated on the analysis of the final textual product as a means of understanding the narrative, the present study explores the underlying processes of narrative construction and presentation within peer groups in a teacher education college, drawing on the narrators’ own reflections and accounts. Employing on a qualitative grounded theory design, semi-structured interviews were conducted with 15 current and former special education college students. Participants reflected on the deliberative and interpretive processes, shaping both disclosure decisions and modes of self-presentation. Findings indicate that peer groups constitute a significant force in narrative co-construction. Boundaries of disclosure and degrees of vulnerability were continuously negotiated, through engagement with others’ narratives. Participants employed various narrative strategies, including redemption and normalization frameworks, in order to sustain a coherent and resilient professional self-concept. A key theoretical contribution of the study is the conceptualization of emotional regulation, as an integral component of narrative construction. Participants actively modulated the emotional intensity of their storytelling. Overall, the study suggests that Biographical Narrative practices function as a collaborative and meaning-making process that supports reflective capacity, peer-based scaffolding and resilience, thereby contributing to teacher well-being and professional identity development, in preservice education contexts. Full article

This conceptual paper revisits the learning styles debate in the context of generative and adaptive artificial intelligence in higher education. It does not seek to rehabilitate classical learning style taxonomies, whose prescriptive claims have been widely challenged as a neuromyth. Instead, it argues that AI-mediated learning creates new conditions under which patterns of regulation, delegation, verification, iteration, epistemic control, and ethical responsibility may become more observable and pedagogically relevant. Drawing on research on learning styles, neuromyths, AI literacy, adaptive learning, assessment, self-regulated learning, metacognition, and epistemic agency, the paper proposes a conceptual framework for regulation and agency styles in AI-mediated learning. In this framework, style is not treated as a fixed psychological trait or as a category into which learners should be sorted, but as a situated and modifiable profile of decisions and actions distributed across learners, tasks, and intelligent systems. Three analytical dimensions are proposed: epistemic control and metacognitive orchestration, adaptive regulation and generative iteration, and socio-algorithmic agency and ethical governance. The paper concludes with implications for task design, assessment, teacher education, and equitable AI integration. Full article

As generative AI technologies become increasingly embedded in educational cloud platforms, understanding their impact on teacher professional development is essential. Grounded in the stimulus–organism–response (S–O–R) framework, this study investigates how AI-driven stimuli—hedonicity, interactivity, and immersion—influence teachers’ self-regulation and resilience. Using structural equation modeling, data were collected from in-service teachers in Taiwan who actively utilize educational cloud platforms. The results reveal that all three AI-driven stimuli significantly enhance teachers’ self-regulation and resilience, which in turn are significantly associated with perceived value co-creation intentions. Specifically, self-regulation enables teachers to manage goals effectively, while resilience supports their recovery from technical setbacks. The findings indicate that self-regulation positively influences resilience, and both appear to mediate the relationship between perceived AI-driven stimuli and teachers’ value co-creation intentions. This study highlights the potential role of teachers’ psychological adaptability in AI-enhanced environments. Practical implications suggest that platform developers and administrators should prioritize AI features that foster self-directed learning and emotional engagement to promote collaborative willingness and professional alignment within modern educational ecosystems rather than implying proven macro-level transformation. Full article

Empirical evidence for AI formative assessment combined with gamification remains scarce in subjective aesthetic disciplines. This study examined whether such integration enhances metacognitive regulation in undergraduate color education and whether the effect is conditional on learners’ prior AI credibility belief. A four-arm, four-wave cluster-randomized controlled trial (N = 540, 24 classes, eight cross-allocated teachers) compared gamification with AI feedback, gamification with dose-matched human feedback, gamification only, and traditional instruction; the primary outcome was metacognitive regulation measured 4 weeks post-intervention. Gamification produced a small-to-medium effect over traditional instruction (d = 0.34, p_Holm = 0.015). AI and human feedback did not differ on average (d = 0.07; underpowered). Autoregressive mediation confirmed metacognitive regulation as a longitudinal mediator of intervention effects on motivation and achievement. On an exploratory basis, prior AI credibility belief moderated the AI-versus-human indirect effect on motivation (p_Holm = 0.034) but not achievement (p_Holm = 0.054), with higher-belief learners benefiting; given the limited power of the AI-versus-human comparison, this conditional pattern is reported as a tentative finding rather than as confirmatory evidence. These findings extend self-determination theory and the self-regulated learning framework to aesthetic education and provide preliminary support for the deployment of prior-trust-aware AI feedback, pending replication. Full article

The COVID-19 pandemic caused sudden changes in school routines, creating conditions that may have been relevant to students’ self-efficacy for self-regulated learning (SESRL). This research investigated high-school students’ SESRL during the initial lockdown (Study 1) and across three pandemic stages (Study 2). Using a cross-sectional retrospective design, Study 1 (N = 802, 32.5% males; M_age [Time1 (T1)] = 16.40, SD = 1.52) revealed a significant difference between retrospectively reported SESRL for the pre-pandemic period and SESRL perceived during the first lockdown. Also, higher perceived teacher support and effortful control were associated with higher SESRL during the lockdown. Latent Growth Curve Analyses in Study 2 [N (T1) = 455, 31.9% males; M_age (T1) = 15.37, SD = 1.10; 71% attrition rate] showed a declining trend for perceived SESRL over time, regardless of gender and school grade, whereas COVID-19-related life disruption showed a significant time-varying effect. Specifically, higher levels of COVID-19-related life disruption were associated with lower SESRL at each time point. These findings highlight the potential value of monitoring students’ SESRL and exploring educational initiatives that support self-regulatory skills and positive teacher–student relationships, particularly during periods of widespread educational disruption. However, the longitudinal findings should be interpreted cautiously given the substantial attrition across waves. Full article

Teachers’ socio-emotional competencies are increasingly recognized as essential for professional well-being, adaptive teaching, and effective participation in digitally transforming educational systems. However, valid and culturally appropriate instruments for assessing these competencies among teachers remain limited, particularly in multilingual and underrepresented educational contexts. This study aimed to adapt the Behavioral, Emotional, and Social Skills Inventory (BESSI) for teachers in Kazakhstan and to examine its preliminary psychometric properties and socio-emotional competency profiles. The instrument was translated and culturally adapted into Kazakh and Russian using a TRAPD-based (Translation, Review, Adjudication, Pretesting, and Documentation) procedure involving translation, review, adjudication, pretesting, and documentation. Data were collected from 1458 school teachers across Kazakhstan representing different subject areas and language groups. After data-quality screening, the final analytic sample included 918 valid observations. Reliability analyses demonstrated excellent total-scale internal consistency (Cronbach’s α = 0.92; McDonald’s ω = 0.94), while domain-level reliability ranged from moderate to acceptable (α = 0.60–0.76; ω = 0.73–0.81). Exploratory factor analysis suggested an empirical eight-factor structure rather than a direct replication of the original BESSI framework, indicating that socio-emotional competencies may be organized differently in teacher populations. Model-based clustering identified four exploratory teacher profiles reflecting different configurations of self-management, emotional regulation, interpersonal, and innovation-related competencies. The profiles differed not only in overall competency levels but also in specific patterns of strengths and developmental needs. The findings provide preliminary evidence supporting the use of the adapted BESSI as a promising research and diagnostic instrument for assessing teachers’ socio-emotional competencies in Kazakhstan. At the same time, the results indicate the need for further confirmatory validation, measurement invariance testing, and external validity evidence before broader application. Full article

There is a growing body of research examining the experiences of lesbian, gay, bisexual, trans, and queer (LGBTQ+) teachers in schools. However, limited empirical attention has been given to those in the early stages of their careers, particularly within the UK context, where historical and legislative dynamics continue to shape school cultures. This article addresses this gap by exploring how queer early-career teachers (QECTs) construct and navigate their personal and professional identities within heteronormative and cisnormative school environments. Drawing on a qualitative narrative inquiry with three UK-based QECTs, the study analyses written biographical narratives and semi-structured interviews using reflexive thematic analysis. The findings identify three interconnected processes shaping identity navigation: preventative barriers (including anticipated judgement, self-surveillance, and performative regulation), community as a site of affirmation and restoration, and a negotiated sense of freedom understood as context-dependent agency rather than full disclosure. The study argues that identity formation for QECTs is not a linear progression towards authenticity, but an ongoing negotiation shaped by power, precarity, and relational safety. In doing so, it extends existing research by foregrounding early-career status as a critical factor in queer teacher identity work and contributes a conceptual framing of “negotiated authenticity” within professional contexts. The article concludes by considering implications for professional sustainability, belonging, and inclusive school cultures. Full article

Rapidly expanding use of Generative Artificial Intelligence (GenAI) in higher education creates both opportunities and challenges for learning assessment. While GenAI can provide adaptive feedback and personalization, its pedagogical integration remains underdeveloped and often disconnected from established theories of learning and participatory design processes. This paper addresses this gap by proposing an integrative conceptual model of Hybrid Intelligent Assessment Systems (HIAS), which combines AI capabilities with human oversight to enable transparent, ethical, and pedagogically aligned assessment. HIAS is structured through three interdependent layers of adoption: a pedagogical layer, aligning AI-supported assessment with self-regulated learning and the development of knowledge, skills, and attitudes; a governance layer, ensuring transparency, fairness, and human-in-the-loop validation; and a technological layer, enabling scalable integration within digital learning environments. The study is situated in Estonia, a digitally advanced context with system-level AI integration through the national AI Leap initiative. To complement the conceptual model, an empirical study was conducted across three major Estonian universities, involving 66 professors and researchers and 153 students. In addition, a small-scale pilot implementation was conducted in a design thinking course to explore the practical feasibility of a course-specific HIAS-based AI assistant. The findings reveal a consistent pattern: while both groups demonstrate a broadly positive orientation toward AI, students approach AI primarily as an efficiency-driven learning tool, whereas academic staff emphasize pedagogical control, ethical considerations, and responsible use. Across both groups, AI literacy remains uneven, particularly in critical evaluation and structured application. These findings expose a critical gap between rapid AI adoption and insufficient pedagogical integration. In response, HIAS is proposed as a structured, human-centered framework that supports teachers in designing AI-enhanced learning environments and students in developing critical, self-regulated, and responsible use of AI. Full article

Although GenAI has been increasingly applied in pre-service teacher education, limited evidence is available on how permitted but unscaffolded GenAI use affects pre-service teachers’ learning and professional development in authentic course contexts. Grounded in cognitive load theory and the zone of proximal development, this quasi-experimental study examined the effects of unscaffolded GenAI use in an 11-week instructional design course. Two intact sophomore classes at a normal university participated, with one class permitted to use GenAI without prompt templates or instructional guidance and the other not permitted to use GenAI. Data were analyzed using paired-samples t-tests and a one-way analysis of covariance (ANCOVA). After controlling for pretest scores, no significant group differences were found in AI readiness, self-regulated learning, or critical thinking, whereas the control group showed stronger instructional design performance. Within-group comparisons showed that both groups improved in AI readiness and instructional design performance, but not in self-regulated learning or critical thinking. These findings suggest that, in this course context, unscaffolded GenAI access alone may be insufficient to support pre-service teachers’ professional learning and may be less favorable for their instructional design performance. Full article

Drawing on research on self-regulated learning, metacognition, and cognitive aspects of writing, this study examines whether structured free writing can function as a scaffold for developing writing self-regulation, affective engagement, and genre-based performance. While free writing has traditionally been conceptualized as a creativity-enhancing or pre-writing activity, its role in fostering self-regulatory and metacognitive processes associated with intelligent performance remains underexplored. A convergent parallel mixed-methods design was employed with preservice teachers enrolled in a seven-week writing workshop in higher education. Quantitative data included validated measures of writing self-regulatory efficacy and attitudes toward free writing, along with analytic assessments of informative and narrative writing performance. Qualitative data were obtained through semi-structured interviews examining participants’ regulation of their writing processes. Findings indicate significant improvements in self-regulatory efficacy, more adaptive attitudes toward writing, and gains in genre-specific performance. Qualitative results further suggest that structured free writing supports metacognitive awareness, reduces writing-related anxiety, and enhances sustained cognitive engagement. By conceptualizing free writing as a mechanism for developing self-regulatory capacities underlying intelligent behavior, this study contributes to research on individual differences in learning and highlights the integration of cognitive and affective processes in academic performance. Full article

Academic motivation and achievement are central to student success in applied STEM, engineering, and technical and vocational education and training (TVET); however, despite extensive research, the evidence remains fragmented across theoretical traditions, educational levels, and disciplinary settings. This structured narrative review synthesizes research on the factors shaping academic motivation, achievement, and career readiness in these contexts. A literature search was conducted in Web of Science, Scopus, ScienceDirect, PubMed, and PsycINFO for studies published between 2010 and 2025. A total of 58 studies met the inclusion criteria from an initial pool of 2184 records. Guided by self-determination theory, achievement goal theory, social cognitive career theory, and expectancy–value theory, this review identifies self-efficacy, perceived competence, task value, intrinsic/extrinsic motivation, goal orientation, metacognitive skills, teacher and peer support, curriculum relevance, and industry-aligned learning opportunities as key factors associated with student engagement, achievement, and career-related development. The synthesis shows that these factors operate through an integrated motivational core linking motivational regulation, self-belief, task value, and goal orientation. The findings suggest that student success is shaped by the interaction between individual beliefs, social support, instructional conditions, and perceived links between learning and future professional pathways. Practical implications are discussed for designing student-centered, career-relevant, and motivation-supportive learning environments in engineering and TVET. Full article