Search Results (1,065)

Fire safety plays a vital role in protecting lives, property, and the environment, and it keeps communities and organizations running safely. Many existing fire pump control systems fall short in educational and small-to-medium industrial settings: they often control only one pump at a time, rely heavily on manual monitoring, and come with high costs that limit accessibility. To address these gaps, we developed an affordable, hands-on educational kit that brings real-world fire safety systems into the classroom using modern automation technology. The system is built around a Delta DVP12SA211R PLC chosen for its built-in real-time clock, integrated RS-232/RS-485 ports for reliable communication, and expanded with DVP16SP11R digital I/O and DVP04AD-S2 analog input modules to interface with simulated sensors mimicking smoke detection and water pressure. Students interact with the system through a Delta DOP-110IS HMI, which features Ethernet connectivity for remote observation, electrical isolation for safe operation, and a 200 ms screen update rate to ensure responsive, realistic feedback. The kit enables learners to explore critical emergency scenarios, including automatic switching between jockey and main pumps, low-pressure alerts, and system failover, transforming theoretical concepts into tangible skills. In user evaluations, 57.1% of students with no prior experience reported that the simulations closely mirrored real-world systems, while 80% of those with a fire safety background found the kit reinforced their existing knowledge; notably, 57.1% of instructors rated it as highly effective for teaching core fire safety principles across diverse learner profiles. By integrating industrial-grade hardware with scenario-based learning, this tool not only deepens understanding of fire protection systems but also better prepares future engineers for the practical demands of fire safety and industrial automation careers. Full article

This article analyses the professional needs of foreign language teachers in rural territories, with a primary analytical focus on teachers’ linguistic competence and how it is sustained over time. Using a mixed-methods needs analysis informed by Participatory Action Research, data were obtained from questionnaires, interviews, and classroom observations in rural Andalusia (southern Spain). The results foreground persistent challenges in maintaining a high level of command of the target language—especially oral fluency and pronunciation—within linguistically isolated professional environments. Methodological and technological issues are reported as contextual conditions that shape (and sometimes constrain) teachers’ opportunities to develop and enact linguistic competence, including multi-grade and multicultural classrooms, limited time for peer collaboration, and uneven student access to devices and connectivity at home. Overall, the findings point to the need for localized, flexible, and participatory professional development that prioritizes teachers’ ongoing linguistic development while addressing contextual barriers in rural schools. Full article

The research problematises the different micro-exclusion practices in rural primary schools and their impact on learners’ participation and academic development. Rural primary school classrooms perpetuate systemic micro-exclusion of learners in various ways, reflecting injustice and a colossal squandering of human potential. All learners, at some point, in the same learning spaces often face different classroom experiences as they are subtly excluded through teacher commissions and omissions. The paper presents an exploration of the phenomenon of micro-exclusion practices in rural primary school classrooms, drawing on the perspectives and reflections of six primary school teachers. Using a qualitative phenomenological multi-case study design, we explore the everyday behavioral activities of these teachers through in-depth semi-structured interviews and non-participant observation to uncover their experiences and insights regarding subtle micro-exclusionary practices that impact learner participation and inclusivity. It responds to two questions: how do teachers micro-exclude learners during teaching and learning in rural primary schools in Zimbabwe, and what mitigation strategies can be implemented to minimise micro-exclusion in rural primary school classrooms? Findings revealed that micro-exclusion affects all learners and is multifaceted. It exists and manifests in the form of social isolation, subtle biases in attention, and disparities in feedback, which have a strong bearing on learners’ participation. Teachers reported varying degrees of awareness and challenges concerning micro-exclusion practices and expressed a desire to address implicit or explicit biases and foster greater participation in classroom environments. The study highlights the importance of reflective practices among rural primary school teachers and suggests strategies for creating an inclusive participatory atmosphere that mitigates micro-exclusion. Full article

Teaching is widely recognized as a highly stressful profession, and recent educational changes have further increased the pressure on teachers to manage demanding classroom situations while adapting to new technologies. To address this challenge, the present study examines the feasibility and user acceptance of XRSkills, a virtual reality serious game designed to strengthen teachers’ coping and problem-solving strategies through realistic school-based scenarios. A feasibility evaluation was conducted with teachers from all school grades and students from multiple European countries, combining a standardized usability measure with open-ended feedback on the game experience. Overall results indicate that XRSkills achieved a good level of usability and was generally perceived as engaging and relevant, particularly for in-service teachers. Participants appreciated the game format and learning approach, while also reporting areas for improvement such as clearer guidance, richer content, and smoother technical performance. These findings support the potential of virtual reality serious games as a practical and scalable training pathway to help teachers rehearse responses to stressors in a safe environment, while also fostering confidence in using immersive technologies for professional development. Full article

Enclosed learning spaces, e.g., classrooms, are used in most schools. Open learning spaces, which enable teaching more than one group of students at a time, have become increasingly popular. A recent survey showed that acoustic satisfaction was lower among teachers working in open learning spaces. Our purpose was to compare the acoustic conditions of these learning space types. We investigated the room acoustic quality of 73 learning spaces in 20 schools. Ten schools involved only enclosed and ten both open and enclosed learning spaces. Measurements concerned speech transmission index, STI, background noise level, L_Aeq, and reverberation time, T. Variation in results in both learning space types was rather large. In enclosed learning spaces, STI varied within 0.64–0.83, L_Aeq within 25–47 dB, and T within 0.34–0.82 s. The corresponding variations in open learning spaces were 0.47–0.91, 29–44 dB, and 0.44–0.72 s. The differences between enclosed and open learning spaces were surprisingly small. Due to the different intended uses of these space types, Finnish target values are tighter for open than for enclosed learning spaces. These target values were fulfilled in 56% of enclosed and 9% of open learning spaces. The more frequent violation of target values in open learning spaces was due to the STI being too large at longer distances. Our study provides suggestive evidence that the room acoustic conditions are worse in open than enclosed learning spaces. Further research is needed to prove whether room acoustic conditions could explain worse acoustic satisfaction in teachers. Full article

The accelerating digitalization of education has heightened the need for instructional approaches that are developmentally appropriate for young learners and capable of supporting both linguistic growth and creative speech production. This study investigates the pedagogical potential of integrating adapted English-language podcasts and media-based tasks into primary English instruction to foster originality, contextual coherence, expressive flexibility, and emotional richness in learners’ productive speech. The research employed a quasi-experimental pretest–posttest design implemented in intact classroom groups and involved 233 third- and fourth-grade students (experimental group, n = 116; control group, n = 117). Over one academic semester (January–May 2025), the experimental group participated in a structured programme embedded within regular lessons that combined short podcast episodes with dialogic and narrative tasks, while the control group followed the standard curriculum without podcast integration or comparable multimedia enrichment. Data analysis combined quantitative comparison of pre- and post-intervention speech outcomes with qualitative evaluation of learners’ oral and written products, supplemented by student and teacher feedback. The results showed statistically significant improvements in the experimental group across key indicators of creative speech performance. Qualitative evidence further indicated a shift toward more independent, personally meaningful language use, with learners demonstrating greater willingness to experiment with narrative transformation, evaluative retelling, and expressive variation. Taken together, the findings suggest that adapted podcasts, when systematically integrated into routine classroom practice, can serve as an effective and feasible tool for strengthening creative speech development in primary English language education and for enriching contemporary media pedagogy in digitally evolving learning environments. Full article

A smart classroom integrates emerging technologies such as the Internet of Things and cloud computing, optimizes resource allocation, and transforms classroom interaction. A smart classroom encourages students to participate in a pressing concern as Chinese institutions steadily promote the development and implementation of such classrooms. Identifying the key spatial factors that influence learning engagement is essential. Current work has identified learning factors for a smart classroom that encourage dealing with learning environments, perceptions, experiences, and engagement by following a learner-centered educational philosophy. A questionnaire was designed to collect data from the Yibin Campus of Chengdu University of Technology and data was collected by using a survey method. The statistical analysis was applied to 156 valid student perception samples, which were empirically explored. Four factors related to classroom infrastructure and design are examined: physical environment, spatial layout, table and chair design, and technological equipment. Among these, technological equipment has the strongest effect on learning engagement. The findings provide practical guidance for designers seeking to optimize smart classroom environments, thereby enhancing teaching quality and improving learning efficiency. Full article

This article presents a case study of the relationship between the scope of inquiry that classroom teachers provided to Year 4 students during inquiry-based science lessons and the learning autonomy evidenced by those students. This study investigated the practices of two primary school classroom teachers engaging in similar teaching contexts and curriculum imperatives, but each teacher provided a different scope of inquiry to students during their learning. The findings indicate a complex, non-linear relationship between the scope of inquiry provided by teachers and the student learning autonomy demonstrated. Predictably, students who experienced a narrow scope of inquiry, as provided by teachers, demonstrated a low level of learning autonomy. However, this study found that when students experienced inquiry with a broad scope provided by the teacher, they demonstrated a large range of learning autonomy, not only high levels of learning autonomy but also low levels. Moreover, when students experienced inquiry with a broad scope provided by the teacher, they manifested more diverse emotions, ranging from frustration to enjoyment, when compared with times that they experienced a narrow scope of inquiry. The findings demonstrated that students could remain on task in a broad scope of inquiry environment, but found that the minimal guidance provided was challenging. The results of the current study underscore the importance of a balance between a broader scope and a narrower scope of inquiry to optimise student learning. The non-linear relationship between the scope provided and the student level of learning autonomy experienced has ramifications for unresolved conflicts about closed vs open inquiry and for quantitative research on this complex construct. Full article

Folklore, as an expression of intangible cultural heritage, plays a key role in the transmission of collective memory, values, and cultural identity and has been widely recognized for its educational potential in early childhood. This study analyzes the perceptions of Early Childhood Education teachers in the province of León (Spain) regarding the pedagogical value of folklore and its use in classroom practice. A quantitative, cross-sectional, non-experimental design was employed using a validated questionnaire administered to a voluntary sample of 100 teachers from schools offering the second cycle of Early Childhood Education. The instrument assessed three dimensions: knowledge of folklore, perceived relevance of folk literature, and application in educational practice. The results indicate that teachers hold very positive attitudes toward folklore as a cultural and educational resource, particularly for children’s social, emotional, and cultural development. However, a clear gap emerges between this strong theoretical appreciation and its occasional classroom use. Significant differences were identified according to school environment, type of school, and teaching experience, indicating that contextual and professional factors influence folklore integration. Insufficient training and low self-confidence were identified as the main barriers. This study highlights the need to strengthen initial and in-service teacher education in cultural heritage and in the didactics of literature and music to promote a more meaningful and sustainable use of folklore in early childhood education. Full article

Sustainable and equitable STEM education requires assessment mechanisms that support timely instructional decisions while remaining feasible in resource-constrained classroom environments. Traditional assessments typically report only class-level statistics, limiting teachers’ ability to diagnose individual learning difficulties. This study proposes a classroom-oriented AI-assisted diagnostic framework that integrates generative adversarial networks (GANs) and convolutional neural networks (CNNs) to support learning pattern identification under conditions of severe data scarcity. Student response-behavior data collected through an online testing platform were used to categorize learners into predefined learning behavior types. The GAN was employed to generate locally perturbed samples for stability-oriented data expansion at multiple scales, while the CNN served as a pattern consistency learner operating on the expanded dataset. Rather than aiming for population-level generalization, the framework examines the stability and consistency of learning behavior classification within a single classroom context. Classification results across different expansion scales showed stable performance, with CNN accuracies exceeding 72%. Based on diagnostic outputs, teachers implemented targeted remedial instruction. Case study results show that four out of five remedial interventions exhibited observable improvement. These findings indicate that the proposed framework functions as a proof-of-concept decision-support tool for formative diagnosis and targeted instruction, supporting more equitable learning opportunities, improving instructional efficiency, and contributing to sustainable STEM education aligned with SDG 4. Full article

This study co-designed and developed multimodal educational games in collaboration with parents and teachers to engage girls in STEM from early childhood onward. Recent studies examine the supportive and complementary role of digital educational technology, such as multimodal games, in engaging girls in STEM education during primary and secondary schooling. Different skills, such as computational thinking, mathematical and scientific skills, can be developed via simulations, models, narrative-rich videos, and digital games. However, there is limited research on how parents and teachers perceive how multimodal games can engage children, especially girls in STEM, in early years learning environments, both at home and in formal educational classroom play-based learning contexts. Employing a multi-case study approach, the study conducted focus group discussions (N = 10) with 15 parents and 15 teachers of children from birth to 8 years of age. The theoretical framework underpinning Bronfenbrenner’s socioecological lens guided the thematic data analysis, particularly acknowledging theoretical ideas that a young girl’s natural learning environment comprises parents, siblings, peers, and early childhood professionals (e.g., educators) who play an essential role in the development of a child’s early STEM engagement. Findings indicate the essential role of the pedagogue (both parents and educators), with multimodal technologies (games) acting as the third teacher, being critical in scaffolding girls’ early STEM education by capitalising on multimodal learning environments. Implications pertain to designing hands-on, multimodal games that enable children to engage seamlessly with science and mathematics concepts through a variety of design features, including problem-solving, doing, constructing, role-play, and gamification. Full article

This entry presents a conceptual approach for how artificial intelligence (AI) can be used to support high school and college students’ reading comprehension of complex texts across disciplines, using the Revised Metacognitive Awareness of Reading Strategies Inventory (MARSI-R), as an organizing framework. Drawing on research in literacy, learning sciences, and educational technology, the entry conceptualizes AI tools as potential metacognitive supports that can assist learners in planning, monitoring, and evaluating reading. At the same time, it distinguishes between AI use that risks promoting cognitive outsourcing, particularly when tools replace rather than support readers’ active regulation of meaning-making. The entry emphasizes the importance of instructional design and teacher mediation in aligning AI-supported reading practices with established models of metacognitive strategy use. Central to this discourse is the distinction between cognitive scaffolding, using AI to support and extend students’ strategic engagement within their zone of proximal development, and cognitive outsourcing, using AI to bypass cognitive effort entirely, thereby undermining active meaning-making. A distinctive feature of this entry is its use of MARSI-R not only as an assessment instrument but also as a design heuristic for structuring AI-supported reading interactions. By mapping AI affordances onto MARSI-R’s three strategy dimensions, the entry provides a conceptual bridge between established metacognitive theory and the practical design of AI-enhanced reading environments. This framing distinguishes the present contribution from prior work that treats AI tools and metacognitive frameworks as separate domains. Using MARSI-R’s dimensions of Global, Problem-Solving, and Support reading strategies, this entry describes how AI may provide personalized prompts and feedback that encourage strategic engagement with texts in STEM, the humanities, and social sciences. Illustrative classroom examples and research findings are used to highlight AI’s potential to support students in becoming “architects of their own understanding,” while also addressing ethical considerations such as overreliance on automated summaries and data privacy concerns. This entry offers a practical and theoretically grounded roadmap for integrating AI to support thoughtful, reflective reading across disciplines. Full article

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in educational buildings represents an emerging opportunity to enhance intelligent environmental monitoring, data analysis, and energy optimization. This article presents a systematic literature review focused on AI-based applications in IoT-enabled learning environments, with special attention to indoor air quality (IAQ) management. A total of 585 documents were initially retrieved from Web of Science, Scopus, and IEEE Xplore using two targeted search strings. After removing duplicates and applying successive relevance filters based on title, abstract, and pertinence, 128 final documents were selected for full-text analysis. This study addresses four research questions: (RQ1) Which AI techniques are applied to environmental data analysis in educational contexts? (RQ2) What methods are used to detect sensor anomalies in IoT-based monitoring systems? (RQ3) How is AI applied in real-time decision making based on air quality indicators? (RQ4) What AI-driven strategies support energy efficiency in classrooms? The results reveal a growing use of machine learning and deep learning models, such as convolutional neural networks, decision trees, and LSTM architectures, particularly in applications focused on air quality classification, fault detection, and predictive control. Supervised learning methods were the most frequently applied, with CNN-based models leading in air quality prediction tasks and decision trees being preferred for anomaly detection. Deep learning approaches showed higher accuracy but required greater computational resources, limiting their use in low-cost educational environments. However, the literature also shows a lack of contextualized implementations, especially in low-resource or Latin American environments, and a limited focus on user-centered and educationally integrable systems. In addition, the review identifies a research gap regarding the integration of environmental and educational data, suggesting the potential for future empirical studies that evaluate real classroom conditions using IoT devices to inform AI-driven energy optimization strategies in academic settings. Full article

The evaluation of student performance often relies on basic spreadsheet outputs that provide limited insight into item functioning. This study presents a methodological demonstration showing how widely available spreadsheet software can be transformed into a practical environment for psychometric analysis. Using a simulated dataset of 40 students responding to 20 dichotomous items, spreadsheet formulas were developed to compute descriptive statistics and Classical Test Theory (CTT) indices, including item difficulty, discrimination, and corrected item–total correlations. The demonstration was extended to Item Response Theory (IRT) through the implementation of 1PL, 2PL, and 3PL logistic models using forward-calculated item parameters. A smaller dataset of 10 students and 10 items was used to illustrate the interpretability of the indices and the generation of Item Characteristic Curves (ICCs). Results show that spreadsheets can support teachers in in-terpreting test data beyond total scores, enabling the identification of weak items, refinement of distractors, and construction of small-scale item banks aligned with competence-based curricula. The approach contributes to Sustainable Development Goal 4 (SDG 4) by promoting accessible, equitable, and high-quality assessment practices. Limitations include the instability of IRT parameter estimation in small samples and the need for teacher training. Future research should apply the approach to real classroom data, explore automation within spreadsheet environments, and examine the integration of artificial intelligence for adaptive assessment. Full article

Critical thinking (CT) is widely recognized as a central goal of science education, yet its mechanisms within specific disciplinary contexts remain underexplored. This study developed a biology-specific theoretical model of CT through qualitative analysis of high school students’ engagement with contradictory evidence. Data included pen-and-paper responses from 196 students and eight classroom dialogue transcripts, analyzed using Corbin and Strauss’s coding procedures, with sequential batching and external validation. Selective coding identified questioning—transforming multiple criteria—as the core category, supported by four major categories: evolving evaluative criteria, various types of reasoning, analysis without judgment, and the application of empirical knowledge across criteria. This model explains how learners shift between confirmation, falsification, and reconstruction when anomalies disrupt initial assumptions. To extend its theoretical reach, the model was placed in heuristic dialogue with Kuhn’s structure of scientific revolutions. The comparison highlights the cyclical nature of CT development: anomalies destabilize prevailing frameworks and trigger reorganization of evaluative criteria, fostering cognitive growth. By explicating how students engage with contradictory evidence and transform evaluative criteria, this study elucidates the emergence of critical thinking in disciplinary practice. The findings also inform the design of biology learning environments that deliberately incorporate anomalies and cognitive conflicts, and justify the integration of history and philosophy of science (HPS) perspectives to support students’ questioning, analysis, and criteria revision in authentic scientific contexts. Full article