Search Results (592)

This study investigates the evolving pedagogical strategies and professional identity development of two novice college English teachers in China through a semester-long classroom-based inquiry. Drawing on Norris’s Multimodal (Inter)action Analysis (MIA), it analyzes 270 min of video-recorded lessons across three instructional stages, supported by visual transcripts and pitch-intensity spectrograms. The analysis reveals each teacher’s transformation from textbook-reliant instruction to student-centered pedagogy, facilitated by multimodal strategies such as gaze, vocal pitch, gesture, and head movement. These shifts unfold across the following three evolving identity configurations: compliance, experimentation, and dialogic enactment. Rather than following a linear path, identity development is shown as a negotiated process shaped by institutional demands and classroom interactional realities. By foregrounding the multimodal enactment of self in a non-Western educational context, this study offers insights into how novice EFL teachers navigate tensions between traditional discourse norms and reform-driven pedagogical expectations, contributing to broader understandings of identity formation in global higher education. Full article

In distance learning environments, learner engagement directly impacts attention, motivation, and academic performance. Signs of fatigue, negative affect, or critical remarks can warn of growing disengagement and potential dropout. However, most existing approaches rely on a single modality, visual or text-based, without providing a general view of learners’ cognitive and affective states. We propose a multimodal system that integrates three complementary analyzes: (1) a CNN-LSTM model augmented with warning signs such as PERCLOS and yawning frequency for fatigue detection, (2) facial emotion recognition by EmoNet and an LSTM to handle temporal dynamics, and (3) sentiment analysis of feedback by a fine-tuned BERT model. It was evaluated on three public benchmarks: DAiSEE for fatigue, AffectNet for emotion, and MOOC Review (Coursera) for sentiment analysis. The results show a precision of 88.5% for fatigue detection, 70% for emotion detection, and 91.5% for sentiment analysis. Aggregating these cues enables an accurate identification of disengagement periods and triggers individualized pedagogical interventions. These results, although based on independently sourced datasets, demonstrate the feasibility of an integrated approach to detecting disengagement and open the door to emotionally intelligent learning systems with potential for future work in real-time content personalization and adaptive learning assistance. Full article

In the era of generative artificial intelligence, writing has evolved into a programmable practice capable of generating sustainable narratives and preserving cultural heritage through poetic prompts. This study proposes “Writing Is Coding ” as a paradigm for sustainability education, exploring how students engage with AI-mediated multimodal creation to address environmental challenges. Using grounded theory methodology with 57 twelfth-grade students from technology-integrated high schools, we analyzed their experiences creating environmental stories and digital cultural artifacts using MidJourney, Kling, and Sora. Data collection involved classroom observations, semi-structured interviews, and reflective journals, analyzed through systematic coding procedures (κ = 0.82). Five central themes emerged: writing as algorithmic design for sustainability (89.5%), emotional scaffolding for environmental awareness (78.9%), aesthetics of imperfection in cultural preservation (71.9%), collaborative dynamics in sustainable creativity (84.2%), and pedagogical value of prompt literacy (91.2%). Findings indicate that AI deepens environmental consciousness and reframes writing as a computational process for addressing global issues. This research contributes a theoretical framework integrating expressive writing with algorithmic thinking in AI-assisted sustainability education, aligned with SDGs 4, 11, and 13. Full article

Background/Objectives: Legislative changes in educational systems have influenced how student learning is understood and promoted. In physical education (PE), there has been a shift from behaviorist models to more holistic approaches. In this context, physical literacy (PL) is presented as an emerging pedagogical model in school PE, aimed at fostering students’ motor competence in a safe, efficient, and meaningful way. The aim of this study is to analyze the origins, foundations, methodological elements, and educational value of PL, highlighting its potential to promote holistic and inclusive learning as the basis for an emerging PL model. Methods: A narrative review was conducted through a literature search in the Web of Science, PubMed, Scopus, and SportDiscus databases up to June 2025, focusing on scientific literature related to PL and PE. The analysis included its historical background, philosophical and theoretical foundations, and the key methodological elements and interventions that support its use as a pedagogical model. Results/Discussion: The findings indicate that the PL model can be grounded in key principles, such as student autonomy, teacher training, connection with the environment, inclusion, and collaboration. Additionally, motivation, enjoyment, creativity, and continuous assessment are identified as essential components for effective implementation. Moreover, this model not only guides and supports teachers in the field of PL but also promotes comprehensive benefits for students at the physical, cognitive, affective, and social levels, while encouraging increased levels of physical activity (PA). Conclusions: PL is understood as a dynamic and lifelong process that should be cultivated from early childhood to encourage sustained and active participation in PA. As a pedagogical model, PL represents an effective tool to enhance student learning and well-being in PE classes. Full article

This paper presents the development, implementation, and outcomes of the ELEVATE-US-UP (Engaging Learners through Exploration of Visionary Academic Thought and Empowerment in UnderServed and UnderPrivileged communities) teaching methodology, an equity-centered, culturally responsive pedagogical framework designed to enhance student engagement, academic performance, and science identity among underrepresented learners. This framework was piloted at Northern New Mexico College (NNMC), a Hispanic- and minority-serving rural institution. ELEVATE-US-UP reimagines science education as a dynamic, inquiry-driven, and contextually grounded process that embeds visionary scientific themes, community relevance, trauma-informed mentoring, and authentic assessment into everyday instruction. Drawing from culturally sustaining pedagogy, experiential learning, and action teaching, the methodology positions students not as passive recipients of content but as knowledge-holders and civic actors. Implemented across upper-level environmental science courses, the method produced measurable gains: class attendance rose from 67% to 93%, average final grades improved significantly, and over two-thirds of students reported a stronger science identity and a newfound confidence in their academic potential. Qualitative feedback highlighted increased perceptions of classroom inclusivity, community relevance, and instructor support. By centering on cultural context, student voice, and place-based application, the ELEVATE-US-UP framework offers a replicable and scalable model for educational transformation in underserved regions. Full article

As digital transformation progresses, schools are increasingly confronted with psychosocial challenges such as technostress, digital overload, and unequal participation in digital (learning) environments. This article investigates the conceptual relevance of digital well-being for school development, particularly in relation to social inequality. Despite growing attention, the term remains theoretically underdefined in educational research—a gap addressed through a theory-driven review. Drawing on a systematic search, 25 key studies were analyzed for their conceptual understanding and refinement of digital well-being, with a focus on educational relevance. Findings suggest that digital well-being constitutes a multidimensional state shaped by individual, media-related, and socio-structural factors. It emerges when individuals are able to successfully manage the demands of digital environments and is closely linked to digital inequality—particularly in terms of access, usage practices, and the resulting opportunities for participation and health promotion. Since the institutional role of schools has thus far received limited attention, this article shifts the focus toward schools as key arenas for negotiating digital norms and practices and calls for an equity-sensitive and health-conscious perspective on school development in the context of digitalization. In doing so, digital well-being is repositioned as a pedagogical cross-cutting issue that requires coordinated efforts across all levels of the education system, highlighting that equitable digital transformation in schools depends on a critical reflection of power asymmetries within society and educational institutions. The article concludes by advocating for the systematic integration of digital well-being into school development processes as a way to support inclusive digital participation and to foster a health-oriented digital school culture. Full article

The accelerated transformations in the education system marked by volatility, uncertainty, complexity, and ambiguity (VUCA) require a rethinking of pedagogical approaches. The VUCA environment requires a new educational management system in line with new technological trends in order to respond effectively to all the internal and external factors that may affect the quality of teaching. A particularly important course of action is updating teaching methods by combining traditional teaching methods with new interactive methods that promote the introduction of certain digital applications during the teaching of new topics. In this sense, the quantitative research carried out in the present study among second-year students from the psycho-pedagogical program organized by the Bucharest University of Economic Studies, Romania, has highlighted the fact that innovative teaching methods are more effective, contributing to the development of personality and communication skills among pupils and students. Also, the results obtained after applying the Mann–Whitney test showed that there is a significant difference between students involved in different educational activities and those who do not have contact with the educational environment in terms of perceiving the volatility, uncertainty, complexity and ambiguity of the educational environment. At the same time, in the context of the VUCA world, in order to ensure the effectiveness of the teaching–learning process, teachers need to develop new skills such as stress management, adaptability, creativity, technological skills, and time management. Addressing the specific competencies that teachers need to acquire in order to improve their teaching and to respond effectively to the volatility, uncertainty, complexity and ambiguity in education, this study contributes to the creation of a sustainable education system, which is able to cope with all transformations (technological, legislative, socio-economic, etc.). The article is based on the results obtained in the postdoctoral research conducted at the end of 2024. Full article

Teachers’ 21st century technological pedagogical content knowledge affects their performance self-evaluations, and it is considered that their attitudes towards sustainable education disposition and their digital competencies may also have an impact on their performance self-evaluations and thus may significantly affect these relationships. In this study, it was aimed to examine the effect of teachers’ 21st century technological pedagogical content knowledge on their performance self-evaluations, and the moderating role of digital competencies mediated by sustainable educational disposition in the model established for this purpose was examined. The research sample consisted of 478 teachers (305 female (63.8) and 173 (36.2) male teachers) working in various fields in schools in Türkiye. Within the scope of the research, data analyses were carried out in SPSS 21 and PROCESS Macro package programs using Model 4 and Model 58 developed by Hayes (2022). As a result of the analyses, it was seen that sustainable education tendencies had a mediating role in the relationship between teachers’ 21st-century technological pedagogical content knowledge and their performance self-evaluations. In addition to this, it was seen that 21st-century technological pedagogical content knowledge, sustainable educational dispositions and performance self-evaluations depend on the level of digital competencies. Full article

In this post-digital age, writing assessment has been markedly influenced by advancements in artificial intelligence (AI), emphasizing the role of automated formative feedback in supporting second language (L2) writing. This study investigates how Norwegian teachers use an AI-driven automated feedback tool, the Essay Assessment Technology (EAT), in process writing for the first time. Framed by the second and third-order barriers framework, we looked at teachers’ beliefs and the design level changes that they made in their teaching. Data were collected in Autumn 2022, during the testing of EAT’s first prototype. Teachers were first introduced to EAT in a workshop. A total of 3 English as a second language teachers from different schools were informants in this study. Teachers then used EAT in the classroom with their 9th-grade students (13 years old). Through individual teacher interviews, this descriptive qualitative study explores teachers’ perceptions, user experiences, and pedagogical decisions when incorporating EAT into their practices. The findings indicate that teachers’ beliefs about technology and its role in student learning, as well as their views on students’ responsibilities in task completion, significantly influence their instructional choices. Additionally, teachers not only adopt AI-driven tools but are also able to reflect and solve complex teaching and learning activities in the classroom, which demonstrates that these teachers have applied design thinking processes in integrating technology in their teaching. Based on the results in this study, we suggest the need for targeted professional development to support effective technology integration. Full article

As generative AI tools become increasingly embedded in education, their role in supporting student learning remains both promising and contested. These cross-continental multiple case studies explore how integrating AI into classroom-based creative projects can move students from intimidation to meaningful engagement, comprehension, and retention of course content. Drawing on data from four international university classrooms—in the USA, UK, Canada, and Australia—this mixed-methods study examines students’ experiences as they collaboratively created comic books using generative AI. Each instructor embedded the assignment within their own pedagogical context, enabling cross-institutional comparison of AI’s educational potential. Findings highlight a shared trajectory: students initially approached AI with uncertainty or overconfidence, but developed nuanced understandings of its capabilities through experimentation, reflection, and collaboration. The process of creating narrative-driven visual outputs required students to synthesize theoretical material, communicate effectively in teams, and creatively solve problems—fostering both cognitive and interpersonal learning. Students reported deeper comprehension of academic content and greater confidence using AI tools critically and ethically. This study concludes that when framed as a collaborative partner rather than a replacement for human thinking, AI can support deeper learning experiences. It also suggests that creative, team-based projects can demystify AI and build essential future-facing skills. Full article

Digital transformation has profoundly impacted engineering education, demanding new pedagogical approaches that ensure effective and sustainable learning. Educational psychology plays a fundamental role in strategically integrating educational technologies, fostering more inclusive, interactive, and efficient learning environments. This article explores the intersection of technological innovation, engineering education, and educational psychology, analyzing how digital tools such as Artificial Intelligence, virtual reality, gamification, and remote laboratories can optimize the teaching–learning process. It also examines the psychopedagogical impact of these technologies, addressing challenges like cognitive load, student motivation, digital accessibility, and emotional well-being. Finally, the article presents guidelines for sustainable implementation aligned with the Sustainable Development Goals (SDGs), promoting efficient, equitable, and student-centered education. As a theoretical and exploratory study, it also points to directions for future empirical investigations and practical applications. The insights provided offer strategic guidance for academic managers and educational policymakers seeking to implement sustainable, inclusive, and pedagogically effective digital innovation in engineering education. Full article

The integration of artificial intelligence (AI) into educational environments is fundamentally transforming the learning process, raising new questions regarding student engagement and motivation. This empirical study investigates the relationship between AI-based learning support and the experience of flow, defined as the optimal state of deep attention and intrinsic motivation, among university students. Building on Csíkszentmihályi’s flow theory and current models of technology-enhanced learning, we applied a validated, purposefully developed AI questionnaire (AIFLQ) to 142 students from two Hungarian universities: the Ludovika University of Public Service and Eszterházy Károly Catholic University. The participants used generative AI tools (e.g., ChatGPT 4, SUNO) during their academic tasks. Based on the results of the Mann–Whitney U test, significant differences were found between students from the two universities in the immersion and balance factors, as well as in the overall flow score, while the AI-related factor showed no statistically significant differences. The sustainability of the flow experience appears to be linked more to pedagogical methodological factors than to institutional ones, highlighting the importance of instructional support in fostering optimal learning experiences. Demographic variables also influenced the flow experience. In gender comparisons, female students showed significantly higher values for the immersion factor. According to the Kruskal–Wallis test, educational attainment also affected the flow experience, with students holding higher education degrees achieving higher flow scores. Our findings suggest that through the conscious design of AI tools and learning environments, taking into account instructional support and learner characteristics, it is possible to promote the development of optimal learning states. This research provides empirical evidence at the intersection of AI and motivational psychology, contributing to both domestic and international discourse in educational psychology and digital pedagogy. Full article

Analyses of teaching behaviors in physical education (PE) classrooms are critical for evaluating teaching quality. Traditional evaluation methods primarily rely on manual analysis, which suffers from complex coding procedures, low efficiency, and suboptimal accuracy, hindering long-term sustainability in teaching quality improvement. Artificial intelligence (AI) technology offers a novel approach by enabling real-time data collection, automated annotation, and in-depth analysis of teaching behaviors, thereby supporting sustainable PE teaching optimization. Leveraging the CogVLM2-Video model, the research presents a system for real-time data collection, automated annotation, and in-depth analysis of teaching behaviors. It consists of four key modules: The perception layer handles data acquisition and input providing foundational data for analysis. The platform layer manages data processing and storage, ensuring integrity and security for long-term evaluation. The model layer focuses on behavior recognition and analysis, employing advanced algorithms for precise interpretation of teaching behaviors. The application layer delivers real-time feedback and adaptive recommendations, promoting sustained teaching improvement. The system architecture was initially validated using 50 basketball lesson videos. Then, the recognition model was trained on a Kinetics-400 subset, achieving 92% accuracy and 95% consistency with manual annotations. These results demonstrate the system’s practical value and long-term applicability, offering an efficient, precise solution for PE classroom teaching behavior assessment. Full article

Large Language Models (LLMs) have emerged as powerful tools in cyber security, enabling automation, threat detection, and adaptive learning. Their ability to process unstructured data and generate context-aware outputs supports both operational tasks and educational initiatives. Despite their growing adoption, current research often focuses on isolated applications, lacking a systematic understanding of how LLMs align with domain-specific requirements and pedagogical effectiveness. This highlights a pressing need for comprehensive evaluations that address the challenges of integration, generalization, and ethical deployment in both operational and educational cyber security environments. Therefore, this paper provides a comprehensive and State-of-the-Art review of the significant role of LLMs in cyber security, addressing both operational and educational dimensions. It introduces a holistic framework that categorizes LLM applications into six key cyber security domains, examining each in depth to demonstrate their impact on automation, context-aware reasoning, and adaptability to emerging threats. The paper highlights the potential of LLMs to enhance operational performance and educational effectiveness while also exploring emerging technical, ethical, and security challenges. The paper also uniquely addresses the underexamined area of LLMs in cyber security education by reviewing recent studies and illustrating how these models support personalized learning, hands-on training, and awareness initiatives. The key findings reveal that while LLMs offer significant potential in automating tasks and enabling personalized learning, challenges remain in model generalization, ethical deployment, and production readiness. Finally, the paper discusses open issues and future research directions for the application of LLMs in both operational and educational contexts. This paper serves as a valuable reference for researchers, educators, and practitioners aiming to develop intelligent, adaptive, scalable, and ethically responsible LLM-based cyber security solutions. Full article

The implementation of new curricula presents significant challenges for teachers and necessitates the adaptation of their professional competencies. This study examines how the digital skills of Swiss teachers differ during and after the implementation of the Media and Information Literacy (MIL) modular curriculum. To achieve this, two independent samples totaling 617 teachers were surveyed at different stages of the reform. The analysis employed a multivariate analysis of variance (MANOVA) to identify differences in the four facets of MIL competence between the samples. The results indicate that MIL competencies did not improve uniformly. While no significant differences were found in the facets of ‘ICT knowledge and application’ and ‘media education knowledge and application’, significant differences were observed in the facets of ‘specialized didactics MIL’ and ‘interdisciplinary pedagogical and didactic knowledge’. The latter facet showed higher values after the reform, likely due to increased exposure to further training measures. These findings illustrate that teachers’ competencies can develop differently throughout a reform process, highlighting the importance of targeted professional development programs. The study provides valuable empirical findings for educational research and offers practical implications for the design of future reform processes. Full article