Abstract: Artificial intelligence and generative models are rapidly reshaping academic research methodologies, yet cohesive citation standards remain underdeveloped. Without reliable, transparent, and standardized practices accepted by the scholarly community, AI-supported research risks being either underreported or deemed methodologically untrustworthy. The citation of AI use raises foundational challenges, particularly because AI outputs are neither fully replicable nor verifiable—two core tenets of traditional citation practice. Outputs from large language models are non-deterministic, ephemeral, and context-sensitive, necessitating renewed engagement with debates on model variability, training data, hosting environments, prompting practices, authorship, licensing, ethics, and archival responsibility. This paper presents findings from a CLARIAH-AT–funded initiative to develop citation standards for six categories of new media, with a focused examination of AI outputs. Drawing on interdisciplinary workshops, teaching practice, and scholarly discussion, the project proposes flexible citation frameworks and use-based variations that align emerging technologies with established principles of historical source criticism. These efforts demonstrate that while the citation of AI and new media remains complex and contested, transparent methodological standards can serve as an ethical and practical roadmap for scholarship in the age of AI.

Abstract: The discussion surrounding early childhood technology continues to concentrate predominantly on the duration of screen time, overlooking a critical examination of how particular digital tools qualitatively affect cognitive development. This study asked 74 early childhood teachers and administrators from different types of schools (public, private, Montessori, Reggio, and Head Start) about how they use technology with kids ages 3 to 5 and what effects it has on their thinking. Data indicates a transition from passive consumption to active creation. The study strongly links tablet-based creation apps and digital cameras to the observed 31% increase in creativity and self-expression. There is a strong correlation between educational robotics and coding kits and the growth of problem-solving and critical thinking skills 28%. Interactive e-books and audio resources help people learn languages 22%, especially if they speak more than one language. Success is not determined by duration but by purposeful integration that employs technology as a medium for documentation, collaboration, and targeted skill development within play-based teaching. It is important to move beyond the "screen time" model to a "tech-quality" model. The cognitive advantage is contingent upon the tool's function, the child's position as a creator, and its smooth integration into comprehensive early learning experiences.

Abstract: The COVID-19 pandemic intensified faculty emotional labor as instructors were expected to sustain learning while responding to students’ grief, isolation, and uncertainty. Educational leadership educators occupy a distinctive role as mentors and models for current and aspiring PK–12 and higher education leaders. Using a secondary phenomenological analysis, we reanalyzed de-identified Zoom interview transcripts (2022) from nine U.S. educational leadership educators (seven women; four educators of color) originally collected to examine caring pedagogies. Guided by Hochschild’s emotional labor theory and feminist care ethics, with particular attention to Tronto’s political theory of care, we conducted a theoretically informed thematic analysis focused on caring expectations, role boundaries, and well-being. Findings highlight five interrelated themes: serving as an “anchor” during crisis; blurred instructional–counseling roles and invisible care work; gendered and racialized expectations of availability; competing care obligations across work and home; and boundary-setting as resistance and sustainability. Participants described deep relational commitments to students alongside exhaustion, role strain, and frustration with institutional cultures that assumed limitless capacity to care without reciprocal support. Emotional labor in leadership education should be recognized as central leadership work, and sustainable cultures of care require systemic policies that redistribute and resource care labor.

Abstract: Generative AI challenges traditional technology integration frameworks by introducing agentic systems that actively participate in meaning-making and representation. Existing TPACK-based extensions have identified new knowledge domains required for AI integration, yet they offer insufficient explanations of how such knowledge is dynamically activated during human–AI collaboration. This study proposes the MTA–TPACK Dynamic Collaboration Spiral, a theoretical framework that integrates Meta-Task Awareness (MTA) with TPACK to explain how static knowledge resources are transformed into visible pedagogical reasoning through iterative human–AI interaction. Within this framework, MTA functions as a dynamic navigation engine that guides experts along a Generate–Evaluate–Refine trajectory, enabling principled orchestration of AI participation while maintaining epistemic responsibility. The framework is illustrated through a two-phase scientific visualization task on typhoon–terrain interactions, using Midjourney and GPT-4o. The results show how disciplinary knowledge must be reformulated as AI-interpretable constraints and how evaluation practices evolve when AI systems participate in closed-loop feedback. The resulting visual artifacts embody what is termed Visible Pedagogical Thinking—externalized cognitive constructs that make expert reasoning inspectable. By foregrounding evaluation-centered task design, this study provides a transferable account of how human–AI collaboration can remain pedagogically meaningful by rendering expert reasoning observable and reusable across iterative generative workflows. In doing so, the model contributes to sustainable pedagogical innovation by strengthening teachers’ long-term epistemic agency in AI-mediated design environments.

Abstract: With the deep integration of artificial intelligence (AI) into education, AI literacy has emerged as a core competency indispensable for pre-service teachers. However, the formation mechanisms and sustainable cultivation pathways remain underexplored. This study integrates the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT) to construct a theoretical model where Individual Innovations (II) and Self-Efficacy (SE) serve as antecedents, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) as mediators, Behavior Intention (BI) as a proximal variable, and AI literacy (AIL) as the outcome variable. Through a questionnaire survey of 778 pre-service teachers, mixed empirical tests were conducted using Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). SEM results indicate that II and SE significantly and positively influence AIL through a chain mediation involving PE, PEOU, and BI. fsQCA further identifies four convergent high-AIL configurational pathways: "High-efficacy-practice-oriented" "High-adoption-intention-oriented" "High-innovative-qualities-oriented" and "Balanced-development-oriented". The study reveals that enhancing pre-service teachers' AIL involves diverse yet equivalent mechanisms, necessitating a shift beyond singular training paradigms. Based on these findings, the research proposes differentiated cultivation pathways, providing both theoretical foundations and practical references for teacher-training institutions to implement precise and sustainable AIL development.

Abstract: Universities operate in an environment characterized by complexity, unpredictable challenges, rapid change and stakeholder demands. University employees are a key resource to achieve the strategic goals of the institution, linked to this complexity. Therefore, a conducive environment that fosters employee engagement in the university is critical. Employee engagement as a concept encompasses employees’ positive attitude towards the organization and its values, whereby employees continuously improve how they perform their work to improve organizational effectiveness. Organizational effectiveness is the ability of the organization to proactively adapt and adopt new ideas to continuously improve its operations. The purpose of the study was to explore the application of Systems Thinking as a strategic approach to foster employee engagement across functional boundaries in Universities of Technology. Employee engagement is central to achieving the strategic goals of Universities of Technology. To achieve the objectives of this study, a qualitative research methodology was used. The study was underpinned by a constructivism philosophical worldview. A total of 15 participants were purposively selected from the employees of two universities of technology. Semi-structured face- to-face interviews were used to collect data. Thematic Analysis was applied to analyze data. The findings revealed that Systems Thinking would create a conducive environment to foster Employee Engagement across functional boundaries in universities of technology. In addition, the findings revealed the prevalence of silo practices in the universities of technology. Without Systems Thinking in the institution, departments generally operate in silos and there is no institutionalized philosophy to foster employee engagement, collaboration and knowledge sharing within and beyond functional boundaries.

Abstract: Universities are fundamental to transitions towards sustainability, but academic pres-tige is still primarily shaped by overall rankings. This study assesses whether sustaina-bility leadership is becoming associated with academic prestige and, for this assess-ment, analyzes the UI GreenMetric World University Rankings (2010–2025) and its overlap with the QS World University Rankings (QS WUR) and Times Higher Educa-tion World University Rankings (THE WUR) Top 100; triangulation utilizes THE Im-pact (2019–2025) and QS Sustainability (2023–2025). A longitudinal institution-year panel was constructed and analyzed based on Top 100/Top 10 participation, Borda points, Jaccard stability, and conditional access risk (RR) indices. Participation in-creased from 95 institutions (2010) to 1,745 (2025), with the Global South representing 90% of participants in 2025. Although the South occupied more positions in the Top 100 in 2025 (63 vs. 37), conditional access to the Top 100 remained unequal (21.1% North vs. 4% South; RR = 5.27), and the Top 10 was dominated by the North (9 vs. 1). The stability of the Top 100 increased (Jaccard 0.33 in 2010–2011 to 0.86 in 2023–2024), while overlap with the overall Top 100 remained minimal in 2025 (three institutions with QS WUR ranking and three with THE WUR ranking). Overall, sustainability ap-pears institutionalized in GreenMetric participation and elite stability, but remains weakly associated with conventional academic prestige, suggesting a limited align-ment of incentives in higher education.

Abstract: The STEAM-CT approach integrates Science, Technology, Engineering, Arts, and Mathematics with Computational Thinking (CT) to help students learn how to think, design, and solve problems. It gives students hands-on, interdisciplinary experiences where they apply logic and creativity through real-world applications. The purpose of this study is to foster the development of computational thinking among Deaf students by embedding Artificial Intelligence (AI) learning within a STEAM-CT approach. This learning program consisted of three main phases: (1) exploring AI processes and tools, (2) constructing an AI system, and (3) designing AI-driven innovations. Thirty-six Deaf students from seven Deaf schools participated in this program, which aims to enhance their CT abilities and cultivate their capacity to create AI-based solutions. Students’ progress was measured using a CT framework encompassing knowledge of concepts, applied practices and perspectives. Assessments included multiple-choice tests for CT concepts, task-based rubrics for CT practices, and interviews for CT perspectives. The results showed that Deaf students gained a better understanding of CT concepts, demonstrated advanced CT practices, and exhibited strong CT perspectives. These findings suggest that AI learning through a STEAM-CT approach can effectively promote Deaf students’ computational thinking abilities.

Abstract: Graffiti and mural painting, as essential forms of public visual art, require not only aesthetic planning but also high-precision implementation and control. This study constructs a structured teaching model based on a four-phase framework—"theme design—wall planning—process control—outcome evaluation"—integrated with computational support. Key techniques include image vector mapping, RGB-based color deviation analysis, and 3D wall surface modeling through point cloud reconstruction. Teaching effectiveness was verified via data collected from public wall implementations, using quantitative metrics computed through computer vision modules and spatial analysis algorithms. Results demonstrate significant improvements: 93.8% task completion rate, 16.5% gain in compositional consistency, 21.7% reduction in boundary color error, and a 0.76-point increase in public acceptance score (p<0.05), confirming the feasibility and technical reliability of this computationally augmented art education mode.This study demonstrates that integrating graffiti mural instruction into a structured teaching framework and employing quantitative assessment methods enhances the controllability and replicability of public art education, providing methodological insights for public space art education practices.

Abstract: This study investigates and explores teachers' trust in their colleagues while implementing a PLC in chosen rural primary schools, which has previously been neglected. This study included 310 randomly selected teachers from 57 rural primary schools. The findings demonstrated that primary teachers chose openness, competence, and reliability as three important trust aspects to nurture in their rural primary schools while engaging in PLC activities. Teachers, on the other hand, claimed that compassion and honesty were not well-cultivated in their schools. Additionally, a poor correlation was found between trusting relationships and PLC practice in rural primary schools. Nonetheless, competence, reliability, and openness remained the most important determinants of teachers' PLC practices in the rural primary schools examined. The practical applications and limitations of these findings are discussed.

Abstract: Computational thinking (CT) has become a cross-curriculum priority in many educational jurisdictions, yet research consistently reports uneven integration in initial teacher education (ITE), limited preservice teacher confidence, and persistent misconceptions that equate CT with coding. Concurrently, generative artificial intelligence (GenAI) has rapidly entered university programmes, offering new possibilities for modelling problem solving, generating multiple representations, and supporting iterative design. However, the psychological dimensions of engagement with CT and emerging technologies, including self-efficacy beliefs, affective responses such as anxiety and curiosity, cognitive load management, and the formation of professional identity, remain under-theorised in the teacher education literature. This thematic literature review synthesises 54 sources across three intersecting domains: CT frameworks and their pedagogical implications, CT integration in preservice teacher preparation, and GenAI in teacher education and learning design. Drawing on Bandura's social cognitive theory, cognitive load theory, and research on technology-related affect, the review foregrounds the affective, cognitive, and cultural dimensions of preservice teachers' engagement with CT and GenAI. The review proposes the GenAI-Enabled Computational Thinking for Preservice Teachers (GECT-P) model, which integrates CT dimensions with GenAI-supported learning cycles, psychological mediators, and teacher education outcomes. The model positions prompting as an epistemic and pedagogical practice that can make CT visible, supports cycles of decomposition, abstraction, pattern recognition, and algorithmic design, and embeds critical AI literacy, ethics, affective scaffolding, and classroom enactment. Design principles and practical pathways are offered for teacher educators seeking to prepare graduates who can develop CT with and beyond GenAI across diverse curriculum areas.

Abstract: Background: It is essential that the training of young water polo players aligns with didactic principles and the characteristics of growth and development. Despite this crucial fact, there is a lack of appropriate research. The aim of this article is to determine and explain the appropriate age to begin learning technical elements for defensive field players and goalkeepers in water polo, according to the opinions of water polo coaches. Methods: Twenty-seven water polo experts completed a questionnaire constructed specifically for this study. Test-retest reliability showed acceptable results (r between 0.85 and 1.00, with p < 0.05 for all variables). Results: Exploratory factor analysis using the Guttman-Kaiser criterion for selecting the number of factors and Varimax rotation indicated the existence of two distinct factors for the defensive technique of field players: (1) explosive and perceptive defensive activities; (2) static-repetitive defensive activities. Two distinct factors were also identified for goalkeeping technique: (1) basic goalkeeping technique; (2) advanced goalkeeping technique. Manifest space variability explained 41% and 31% of the variance for defensive technique of field players, and 45% and 44% for goalkeeping technique, respectively. Conclusions: The findings provide improved insight into water polo coaches’ perspectives on learning simple and complex technical elements in water polo and offer crucial guidelines for all training participants.

Abstract: To address inefficiencies caused by fragmented content delivery, inconsistent instructional pacing, and subjective evaluation in foundational art education, this study proposes a computer-assisted modular teaching system based on a unified training pathway. The system incorporates a digital platform structured on a browser–server (B/S) architecture, featuring modules for content scheduling, demonstration standardization, progress tracking, and evaluation automation. The five instructional stages—Imitation Reinforcement, Geometric Structure, Basic Still Life, Complex Composition, and Figure Drawing—are encoded as structured task units. A lightweight image analysis algorithm based on OpenCV extracts visual features (e.g., contour continuity, spatial alignment) from student work, generating quantitative indicators that support semi-automated evaluation and reinforce instructional decision-making. A 16-week teaching experiment involving 86 foundational-level students was conducted using this platform. Four metrics—teaching progress consistency, module achievement rate, modeling accuracy, and teaching effectiveness dispersion—were used to assess outcomes. Compared to traditional instruction, the system achieved a 24.8% reduction in progression deviation, a 14.6% increase in achievement rate, and a 43.3% reduction in inter-class variance (p < 0.05). This research demonstrates the viability of integrating computational control mechanisms and visual analysis tools into art instruction, enhancing the process stability and reproducibility of modular teaching in exam-oriented contexts.

Abstract: This mixed-methods study explores the emotional and relational dimensions of dyadic dialogue between early childhood educators - specifically between kindergarten teachers and assistants. Grounded in theoretical perspectives from dialogic pedagogy and developmental and organizational psychology, the study conceptualizes emotional dialogue as a reflective, co-constructed process through which educators express, respond to, and make meaning of emotional experiences in their daily professional lives.The sample included 60 early childhood teachers (30) and assistants (30) from Israeli kindergartens. The qualitative component included thematic analysis of authentic professional conversations, conducted in a structured setting designed to simulate naturally occurring dialogue. This analysis identified five key dimensions of emotional dialogue: (1) emotional awareness and expression, (2) Fostering acceptance, (3) emotional containment and resolution of negative emotions, (4) positive affect, appreciation and respect, and (5) negative affect - hostility or emotional distance. The quantitative analysis explored associations between emotional dialogue and a range of psychological, interpersonal, and environmental variables, using the CLASS framework (Pianta et al., 2008).Findings revealed that emotionally attuned dialogue is positively associated with educators’ cognitive empathy, attachment orientations, and psychological control, as well as their subjective and interpersonal professional experiences - such as professional self-efficacy, job satisfaction, sense of coherence, evaluation of the assistant’s professional performance, quality of team functioning, and observed quality of classroom climate. These results highlight the potential value of fostering emotional dialogue within early childhood teams as a pathway to enhancing educational quality and professional well-being.

Abstract: Central Asian countries share a common Soviet educational heritage, yet their higher education systems have diverged considerably since independence in 1991. Efforts to construct a unified educational space through Bologna-style reforms have yielded limited results owing to institutional barriers, linguistic diversity, data sovereignty concerns, and administrative inefficiency in credential recognition. This paper proposes a technology-enabled framework for educational integration in Central Asia, leveraging three emerging technologies: blockchain for credential verification and credit transfer, federated learning for privacy-preserving cross-border data collaboration, and neural machine translation for overcoming language barriers. Unlike conventional approaches that demand institutional harmonization, the proposed framework prioritizes functional interoperability while respecting national sovereignty. From a Chinese perspective, the framework embodies principles of South–South cooperation and technological enablement through the Belt and Road Initiative. We describe the architecture of each technological layer, propose a phased implementation strategy with concrete pilot projects, and validate the framework through semi-structured interviews with eight educational administrators and IT specialists across three Central Asian countries. The expert validation confirms the framework's practical relevance while highlighting infrastructure readiness and regulatory adaptation as critical preconditions. This study contributes to debates on alternative models of educational regionalization beyond Western-centric frameworks and offers practical guidance for policymakers, educational institutions, and technology developers.

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Digital serious games are increasingly recognised as valuable tools for fostering student engagement and supporting active learning processes in formal educational contexts. Within the field of heritage education, however, empirical evidence concerning teacher-created games and their pedagogical effects remains limited. This study examines the educational impact of a digital serious game designed by teachers using RPG Maker MV to support the teaching of Social Sciences and local cultural heritage. The game, Misterios de Olivenza, integrates historical, geographical, and cultural content related to the municipality of Olivenza (Extremadura, Spain) through exploratory gameplay and problem-based activities. The research involved 86 primary education students aged 10–13 and employed a validated questionnaire to analyse gameplay experience, motivation, and self-perceived learning, with attention to age and gender differences. Results indicate high levels of enjoyment, motivation, and perceived learning, with no statistically significant differences by gender and limited age-related variation. A moderate positive correlation was identified between motivation and self-perception of learning, suggesting that engagement plays a key role in students’ educational experience. The findings highlight the pedagogical potential of teacher-created serious games for heritage education, while underscoring the importance of careful curricular integration and adequate scaffolding to maximise educational effectiveness.

Abstract: This paper proposes a structural and philosophical synthesis between Edgar R. Eslit’s Narrative Language Ecology (NLE) method and the Law of the Trio—a recursive ontological framework developed by the author. While NLE critiques the ethical void and performative nature of mainstream English Language Teaching (ELT), the Law of the Trio offers a semantic geometry that models language, thought, and reality as structurally equivalent modalities. Together, these frameworks form a pedagogical alliance that restores learner agency, ethical presence, and cognitive resonance. Through comparative mapping, curriculum design, and teacher training implications, the paper argues for a paradigm shift in ELT—one that treats language not as performance, but as presence; not as output, but as invocation. The synthesis invites educators, scholars, and institutions to reimagine language learning as a recursive, ethical, and narrative act. This synthesis responds to calls for humanizing pedagogy (TESOL Quarterly, 2024) and ecological approaches to applied linguistics (Applied Linguistics, 2023), situating the Law of the Trio within current discussions of ethical and narrative presence in ELT.

Abstract: Artificial intelligence (AI) rapidly changes how educators and institutions view academic integrity. Tools like ChatGPT are raising concerns about plagiarism and ethical misuse. While some view these tools as helpful, others are concerned about academic dishonesty or overreliance. The difficulty in detecting AI-generated work makes enforcing ethical rules more challenging. Moreover, university policies vary across institutions, leading to inconsistencies in enforcement. This study used a narrative review following the SANRA scale to assess 24 scholarly articles for key themes regarding the use of AI in higher education. The results show that many students use tools like ChatGPT without understanding the ethical issues involved. Furthermore, faculty struggle to verify student-authored content as AI detection tools lack accuracy in differentiating between human and AI-generated content. University policies regarding AI usage are inconsistent, with some attempting to integrate AI ethically while others ban it outright. While AI tools have clear benefits, the challenges with their use highlight the need for stronger policies, AI literacy programs, better detection tools, and faculty training in the ethical integration of such technology. AI should support student-centered learning rather than replace critical thinking, and for that, universities must update their academic integrity policies to include the ethical use of AI.

Abstract: Germany's global competitiveness, historically rooted in its high-quality education system, is threatened by a severe investment backlog in its public-school infrastructure. While national estimates of this deficit are substantial, the literature lacks a granular empirical analysis at the municipal level, where fiscal responsibility for these assets primarily lies. This paper addresses this critical gap by providing the first municipal-level study of Germany's school investment crisis and exploring the necessity and viability of private capital as a solution. Using a mixed-methods approach, we conduct a cross-sectional analysis of 30 municipalities in North Rhine-Westphalia, integrating demographic, fiscal, and real estate data. We introduce a novel composite metric, the ‘Need Score,’ to offer a more nuanced tool for identifying high-need municipalities. Our findings reveal a profound structural underfunding, with planned municipal investments covering less than 10% of the estimated backlog. The backlog is weakly correlated with GDP growth but not significantly predicted by other common socio-economic indicators, highlighting the limitations of macro-level diagnostics. Conversely, a higher share of private school enrolment is significantly associated with a lower public investment backlog (r = -0.51, p &lt; 0.05). A detailed financial case study demonstrates that investments in educational real estate can deliver stable, positive returns (IRR of 4.5%–19.8%), positioning them as an attractive asset class for institutional investors. We conclude that private capital is not merely an alternative but a necessity for securing Germany’s educational future and propose a policy framework for fostering effective public-private partnerships (PPPs) to bridge this critical infrastructure gap.

Abstract: The rapid expansion of mobile technology has transformed language learning practices worldwide, including in English as a Foreign Language (EFL) contexts at the secondary school level. In Indonesia, where English exposure outside the classroom remains limited, mobile learning has emerged as a potential solution to support vocabulary development among junior high school students. This study aimed to explore how mobile learning was adopted for English vocabulary learning, to examine students’ perceptions of its use, and to identify contextual factors that influenced its effectiveness. Employing a qualitative research design, the study was conducted in a public junior high school in Indonesia. Data were collected through classroom observations, semi-structured interviews with students and English teachers, and analysis of learning-related documents. The data were analyzed thematically using an iterative coding process to identify recurring patterns and meanings. The findings revealed that mobile learning facilitated flexible access to vocabulary input, encouraged repeated practice, and increased students’ motivation and engagement. Students perceived mobile-assisted activities as enjoyable and supportive of independent learning, although challenges related to self-regulation, unequal digital skills, and inconsistent instructional guidance were also identified. The study further found that the effectiveness of mobile learning depended largely on pedagogical integration, teacher mediation, and infrastructural readiness rather than on technology alone. Overall, the study highlighted that mobile learning functioned most effectively when aligned with instructional goals and classroom practices. These findings contributed to a deeper understanding of mobile learning adoption in EFL vocabulary instruction and offered practical implications for teachers, schools, and policymakers seeking to implement sustainable and pedagogically grounded mobile learning initiatives at the junior secondary level.