Search Results (235)

This study examines how international educators come to understand Lesson Study as a form of professional learning through participation in the Lesson Study Immersion Program in Japan (LSIP-JR). While prior research has documented the impact of Lesson Study on individual teachers’ knowledge and instructional practices, less attention has been paid to how teachers recognize the norms of learning communities and how they conceptualize curriculum and instructional tasks as objects of collective inquiry. Drawing on reflective journals produced by program participants, this study analyzes how these often-implicit dimensions of Lesson Study were interpreted through engagement with Japanese classroom practices and professional learning discourse. The findings suggest that participants did not view research lessons as polished demonstrations but rather as provisional inquiries shaped by uncertainty, shared responsibility, and openness to critique. Such interpretations brought into focus norms that are deeply embedded—and often taken for granted—within the Japanese educational context. In addition, participants came to recognize curriculum materials and instructional tasks not simply as tools for implementation but as shared research objects through which hypotheses about student learning are generated and examined, within both normative and institutional conditions. Rather than presenting Japanese Lesson Study as a model to be replicated, this study clarifies the conditions under which Lesson Study functions as collective inquiry. By making these typically unarticulated elements visible, the study offers a conceptual foundation for teachers and professional development leaders seeking to design and sustain meaningful Lesson Study across diverse educational contexts. Full article

Artificial intelligence (AI) has become central to the evolution of learning analytics (LA), transforming how higher-education institutions capture and interpret student engagement data. This narrative review synthesises research published between 2015 and 2025 to examine how AI-driven analytics link learner engagement to measurable academic outcomes, with emphasis on the South-African higher-education context. Drawing on global reviews of AI in education and emerging governance frameworks, the study highlights the shift from traditional dashboards toward deep-learning and transformer-based systems that integrate behavioural, cognitive, and affective indicators. Ethical and policy challenges, particularly around data privacy, transparency, and institutional capacity, remain significant. Grounded in UNESCO and OECD guidance and South Africa’s Protection of Personal Information Act, the review outlines a governance-driven approach for equitable and transparent adoption of AI-enhanced learning analytics. It identifies key challenges, data fragmentation, algorithmic opacity, and limited contextual adaptation, and translates them into practical recommendations for policy, capacity building, and future research. The findings underscore that sustainable AI adoption requires human-centred ethics, robust data governance, and context-sensitive innovation to achieve inclusive and data-driven higher education. Full article

Museums are cultural spaces that should promote accessibility and inclusion for all. However, accessibility is often interpreted as removing physical barriers, overlooking less visible obstacles—such as cognitive, sensory, and communicative challenges—that can profoundly shape the museum experience for people with intellectual disabilities. This paper presents an ethnographic case study conducted in the Veneto region of Italy, in collaboration with a group of individuals with Down Syndrome (DS), aiming to explore their lived experiences of a museum visit. Drawing on participant observation and in-depth interviews, the study examines how visitors with DS engage with the museum environment on behavioural and sensory levels. Findings reveal the impact of environmental stimuli, difficulties in navigating abstract or densely layered visual content, and the importance of embodied interaction with objects and spatial cues. Positive experiences emerged from relational engagement, guided facilitation, and the use of multi-sensory supports. The study underscores the need for museums to move beyond compensatory or charity-based models of accessibility, and instead adopt inclusive design principles that value neurodiversity and participatory co-creation. In doing so, this research contributes to the emerging discourse on how museums can become safe spaces for learning, dialogue, and self-expression for people with intellectual disabilities. Full article

Students with attention deficit hyperactivity disorder (ADHD) face a continuous challenge with their attention span, putting them at a greater risk of academic or psychological difficulties compared to their peers. Innovative communication technologies are demonstrating potential to address these attention-span concerns. Virtual Reality (VR) is one such example, and has the potential to address attention-span difficulties among ADHD students. Accordingly, this study presents an EEG-based multimodal sensing pipeline as a methodological contribution, focusing on sensor-based data acquisition, signal processing, and neurophysiological interpretation to assess attention in VR-based environments, simulating a university supply chain educational topic. Thus, in this paper, a sequential exploratory approach investigated how 35 participants experienced an interactive VR-learning-driven supply chain game. A Brain–Computer Interaction (BCI) sensor generated insights by quantitatively analysing electroencephalogram (EEG) data that were processed through the proposed pipeline and integrated with subjective measures to validate participant’s subjective feelings. These insights originated from questions during the experiment that followed the Spatial Presence and Technology Acceptance Model to form a multimodal assessment framework. Findings demonstrated that the experimental group experienced a higher improved attention, concentration, engagement, and focus levels compared to the control group. BCI results from the experimental group showed more dominant voltage potentials in the right frontal and prefrontal cortex of the brain in areas responsible for attention, memory, and decision-making. A high acceptance of the VR technology among neurodiverse students highlights the added benefits of multimodal learning assessment methods in an educational setting. Full article

The digitalisation of education has introduced new possibilities for inclusive teaching practices, particularly in supporting students with special educational needs (SEN). While digital tools have demonstrated potential to enhance learning outcomes and engagement for these students, the role of school leadership in fostering teachers’ digital competence remains underexplored. The aim of the study is to investigate the association between school leadership, as rated by teachers, and teachers’ self-reported digital competence in supporting students with SEN. To this end, cross-sectional data from 285 Swedish teachers enrolled in special education training programmes have been used. The data were collected through the SELFIE survey, a European Commission tool designed to assess schools’ digital capacity. A stepwise linear regression analysis was conducted to examine the association between perceived school leadership and teachers’ self-reported digital competence in supporting students with SEN, controlling for teacher collaboration, infrastructure and equipment, and demographic variables. The results show a consistent and significant positive relationship between school leadership and teachers’ digital competence, even when other factors are accounted for. Teacher collaboration also contributed positively, though to a lesser extent, while infrastructure and equipment and demographic variables showed no significant effect. The study contributes knowledge by showing that teachers’ digital competence development depends not only on individual efforts but also on organisational factors, such as supportive school leadership, highlighting the importance of recognising school leadership as vital alongside digital resources in schools. Given the cross-sectional design, the findings should be interpreted cautiously and not as evidence of causal relationships. These findings suggest that school leadership is important in enabling teachers to use digital technologies to support students with SEN, highlighting practical and policy implications for strengthening school leadership in developing teachers’ digital competence in supporting students with SEN. Full article

This study proposes an indicator system for evaluating AI-assisted learning in higher education, combining evidence-based indicator development with expert-validated weighting. First, we review recent studies to extract candidate indicators and organize them into coherent dimensions. Next, a Delphi session with domain experts refines the second-order indicators and produces a measurable, non-redundant, implementation-ready index system. To capture interdependencies among indicators, we apply a hybrid Decision-Making Trial and Evaluation Laboratory–Analytic Network Process (DEMATEL–ANP, DANP) approach to derive global indicator weights. The framework is empirically illustrated through a course-level application to examine its decision usefulness, interpretability, and face validity based on expert evaluations and structured feedback from academic staff. The results indicate that pedagogical content quality, adaptivity (especially difficulty adjustment), formative feedback quality, and learner engagement act as key drivers in the evaluation network, while ethics-related indicators operate primarily as enabling constraints. The proposed framework provides a transparent and scalable tool for quality assurance in AI-assisted higher education, supporting instructional design, accreditation reporting, and continuous improvement. Full article

Background/Objectives: In mainstream educational settings, deaf and hard-of-hearing (DHH) students may have limited or no access to the spoken lectures and discussions that are central to the hearing majority classroom. Yet, engagement in these educational and social exchanges is fundamental to their learning and inclusion. Two primary visual accessibility solutions can support this need: real-time speech-to-text transcriptions (i.e., captioning) and high-quality sign language interpreting. Their combined use (or coexistence), however, raises concerns of competition between concurrent streams of visual information. This article examines the empirical evidence concerning the effectiveness of using both captioning and sign language simultaneously in educational settings. Specifically, it investigates whether this combined approach leads to better or worse content learning for DHH students, when compared to using either visual accessibility solution in isolation. Methods: A review of all English language studies in peer-reviewed journals until August 2025 was performed. Eligible studies used an experimental design to compare content learning when using sign language and captions together, versus using sign language or captions on their own. Databases Reviewed: EMBASE, PubMed/MEDLINE, and PsycInfo. Results: A total of four studies met the criteria for inclusion. This limited evidence is insufficient to decide on the coexistence of captioning and sign language. Yet, it underscores the potential of captions for content access in education for DHH, even when sign language is available. Conclusions: The present article reveals the lack of evidence in favor or against its coexistence with sign language. With the aim to be constructive for future research, the discussion offers considerations on the attentional demands of simultaneous visual accessibility resources, the diversity of DHH learners, and the impact of current and forthcoming technological advancements. Full article

This article proposes an interpretable adaptive control model for dynamically regulating task difficulty in Artificial intelligence (AI)-augmented reading-comprehension learning systems. The model adjusts, on the fly, the level of task complexity associated with reading comprehension and post-text analytical tasks based on learner performance, with the objective of maintaining an optimal difficulty level. Grounded in adaptive control theory and learning theory, the proposed algorithm updates task difficulty according to the deviation between observed learner performance and a predefined target mastery rate, modulated by an adaptivity coefficient. A simulation study involving heterogeneous learner profiles demonstrates stable convergence behavior and a strong positive correlation between task difficulty and learning performance (r = 0.78). The results indicate that the model achieves a balanced trade-off between learner engagement and cognitive load while maintaining low computational complexity, making it suitable for real-time integration into intelligent learning environments. The proposed approach contributes to AI-supported education by offering a transparent, control-theoretic alternative to heuristic difficulty adjustment mechanisms commonly used in e-learning systems. Full article

The article reports on a bilingual and interpretable book recommendation platform for schoolchildren. This platform uses a lightweight K-Nearest Neighbors algorithm combined with gamification and learning analytics. This application has been designed for a bilingual learning environment in Kazakhstan, supporting learning in Kazakh and Russian languages, and is intended to improve reading engagement through culturally adjusted personalization. The recommendation engine combines content and collaborative filtering in that it leverages structured book data (genres, target age ranges, authors, languages, and semantics) and learner attributes (language of instruction, preferences, and learner history). A hybrid ranking function combines the similarity to the user and the item similarity to produce top-N recommendations, whereas gamification elements (points, achievements, and reading challenges) are used to foster sustained activity.Teacher dashboards show learners’ overall reading activity and progress through real-time data visualization. The initial calibration of the model was carried out using an open-source book collection consisting of 5197 items. Thereafter, the model was modified for a curated bilingual collection of 600 books intended for use in educational institutions in the Kazakh and Russian languages. The validation experiment was carried out on a pilot test involving 156 children. The experimental outcome suggests a stable level of recommendation in terms of the Precision@10 and Recall@10 values of 0.71 and 0.63 respectively. The computational complexity remained low. Moreover, the bilingual normalization technique increased the relevance of recommendations of non-majority language items by 12.4%. In conclusion, the proposed approach presents a scalable and transparent framework for AI-assisted reading personalization in bilingual e-learning systems. Future research will focus on transparent recommendation interfaces and more adaptive learner modeling. Full article

Over the past five years, generative AI has carved out a major role in architecture, especially in education and visual idea generation. Most of the time, the literature talks about AI as a tool, an assistant, or sometimes a co-creator, always highlighting efficiency and the end product in architectural design. There is a steady rise in empirical studies, yet the real impact on how young architects learn still lacks a solid theory behind it. In this systematic review, we dig into peer-reviewed work from 2015 to 2025, looking at how generative AI fits into architectural design education. Using PRISMA guidelines, we pull together findings from 40 papers across architecture, design studies, human–computer interaction and educational research. What stands out is a clear tension: on one hand, students crank out more creative work; on the other, their reflective engagement drops, especially when AI steps in as a replacement during early ideation instead of working alongside them. To address this, we introduce the idea of “AI sparring”. Here, generative AI is not just a helper—it becomes a provocateur, pushing students to think critically and develop stronger architectural concepts. Our review offers new ways to interpret AI’s role, moving beyond seeing it just as a productivity booster. Instead, we argue for AI as an active, reflective partner in education, and we lay out practical recommendations for studio-based teaching and future research. This paper is a theoretical review and conceptual proposal, and we urge future studies to test these ideas in practice. Full article

Teachers’ language assessment literacy (LAL) encompasses the knowledge and competencies required to design and implement assessment practices that support learning. Although prior research has documented general trends in LAL development, less is known about how individual teachers, particularly student teachers, interpret, appropriate, and negotiate formative assessment (FA) task design within the context of initial teacher education (ITE). Adopting an in-depth qualitative case study approach, this study examines how a single student teacher in a Chinese initial teacher education developed her cognition and classroom practice related to FA tasks across a teaching methodology course and a practicum. Drawing on thematic analysis of semi-structure interviews, lesson plans, classroom observations, stimulated recall interviews, and reflective journals, the study traces developmental changes and the contextual factors shaping the student teacher’s LAL in relation to FA tasks. Findings show that the sustained engagement with FA task design supported more sophisticated understandings of FA, including (1) an increased recognition of the pedagogical necessity of incorporating authentic FA tasks into lesson planning, (2) a growing aspiration to implement FA-oriented instruction that promotes higher-order thinking, (3) an enhanced awareness of the empowering role of FA tasks in fostering students’ self-regulated learning, and (4) a more nuanced understanding of the challenges inherent in implementing FA practices. Meanwhile, the case illustrates how pre-existing assessment conceptions, school culture norms, and limited targeted mentoring can constrain LAL development in relation to FA. By providing a fine-grained account of developmental processes, this study offers insights into how ITE can mediate student teachers’ engagement with FA task design. The findings have implications for teacher education programs in other similar educational contexts, particularly regarding the integration of FA task design into assessment courses and the provision of sustained, context-sensitive support during teaching practicum. Full article

Processes of preparing repertoire for performance in the field of artistic pianism are far from linear, often involving many epistemic modes contributing to an ever-evolving relationship between the pianist, the score and their instrument. Beyond the absorption and internalisation of the score (note-learning, memorisation, addressing technical issues), a range of contingent elements preoccupy pianists in their artistic journey of interpretation. These multifarious influences and approaches have increasingly been acknowledged in the field of Artistic Research, which has for some time sought to move beyond textualist, singular readings of works as bearers of fixed meanings and recognise the creative role of performers and the experience they bring. Through scholarly and phenomenological enquiry concerning the practice of ‘La vallée des cloches’ from Miroirs by Maurice Ravel, in this article, I attempt to represent the multi-modal complexity involved in the creative process of interpretation from my perspective as pianist and artistic researcher. I present novel engagement with scholarship in a multidisciplinary sense, demonstrating a dialogue through which scholarship and performance can interact. I reveal new insights about ‘La vallée des cloches’ through the analysis of my own diary entries logged over three practice sessions, exploring the themes of sound conceptualisation, the consideration of musical structure, and the creation of meaning. Full article

Integrating people with hearing disabilities into schools is one of the biggest problems that Latin American societies face. Mexican Sign Language (MSL) is the main language and culture of the deaf community in Mexico. However, its use in formal education is still limited by structural inequalities, a lack of qualified interpreters, and a lack of technology that can support personalized instruction. This study outlines the conceptualization and development of a mobile application designed as an adaptive assistive technology for learning MSL, utilizing a combination of computer vision techniques, deep learning algorithms, and personalized pedagogical interaction. The suggested system uses convolutional neural networks (CNNs) and pose-estimation models to recognize hand gestures in real time with 95.7% accuracy. It then gives the learner instant feedback by changing the difficulty level. A dynamic learning engine automatically changes the level of difficulty based on how well the learner is doing, which helps them learn signs and phrases over time. The Scrum agile methodology was used during the development process. This meant that educators, linguists, and members of the deaf community all worked together to design the product. Early tests show that sign recognition accuracy and indicators of user engagement and motivation show favorable performance and are at appropriate levels. This proposal aims to enhance inclusive digital ecosystems and foster linguistic equity in Mexican education through scalable, mobile, and culturally relevant technologies, in addition to its technical contributions. Full article

Mobile augmented reality games (MARGs) generate rich digital traces of how students engage with complex, place-based learning tasks. This study analyses gameplay logs from the Art Nouveau Path, a location-based MARG within the EduCITY Digital Teaching and Learning Ecosystem (DTLE), to develop a learning analytics workflow that uses detailed gameplay logs to inform sustainability-focused educational design. During the post-game segment of a repeated cross-sectional intervention, 439 students in 118 collaborative groups completed 36 quiz tasks at 8 Art Nouveau heritage Points of Interest (POI). Group-level logs (4248 group-item responses) capturing correctness, AR-specific scores, session duration and pacing were transformed into interpretable indicators, combined with error mapping and cluster analysis, and triangulated with post-game open-ended reflections. Results show high overall feasibility (mean accuracy 85.33%) and a small subset of six conceptually demanding items with lower accuracy (mean 68.36%, range 58.47% to 72.88%) concentrated in specific path segments and media types. Cluster analysis yields three collaborative gameplay profiles, labeled ‘fast but fragile’, ‘slow but moderate’ and ‘thorough and successful’, which differ systematically in accuracy, pacing and engagement with AR-mediated tasks. The study proposes a replicable event-based workflow that links mobile AR gameplay logs to design decisions for heritage-based education for sustainability. Full article

Eyeblink conditioning (EBC), a form of Pavlovian learning that relies on cerebellar circuits, offers a translationally relevant assay of adaptive learning and cerebellar integrity. In delay EBC, a conditioned stimulus (CS), such as a tone, overlaps with and co-terminates with the unconditioned stimulus (US), typically a brief air puff to the cornea. Trace EBC introduces a stimulus-free interval between CS offset and US onset, engaging additional brain structures such as the hippocampus. Acquisition of conditioned responses (CRs), their timing, and resistance to extinction have all been linked to cerebellar function. While EBC is a well-established paradigm in the experimental analysis of behavior and neuroscience, human studies applying it to ADHD populations remain limited and show inconsistent findings. One potential explanation for this variability lies in procedural differences across studies, particularly in the temporal structure of conditioning trials. A key parameter in Pavlovian learning is the ratio of the inter-US interval (C; time between USs) to the CS–US interval (T; time between CS onset and US onset). Known as the C/T ratio, this value indexes the informational value of the CS in predicting the US and has been shown to influence acquisition speed and response strength. Despite its theoretical importance, the C/T ratio is rarely reported or standardized in human EBC studies involving ADHD. The present review aims to characterize procedural features—especially C/T ratios—used in EBC research with ADHD populations or models, with a focus on how such parameters may shape performance and interpretability in studies probing cerebellar function. Full article