This study examined the effectiveness of assessment techniques applied in an online language learning context in a Sri Lankan university on the improvement of English as a Second Language (ESL) learning of a group of undergraduates. With the increasing integration of technology in education, traditional assessment methods are being replaced or supplemented by digital tools that offer interactive, flexible, and immediate feedback. This study investigated the assessment methods used in online ESL classes and undergraduates’ perception of the effectiveness of the assessment methods. It employed a qualitative case study approach to investigate this contemporary phenomenon using two data sources: semi-structured interviews with twelve undergraduates and the first author's reflective journal. Various digital assessment tools, such as online quizzes, discussion forums, e-portfolios, and gamified platforms like Kahoot!, were used in the assessments. The data were analyzed using thematic analysis, and the first theme includes the positive impact of the online examinations that contributed in terms of increased student engagement, motivation, and participation. The second theme included the impact of formative assessment methods, including instant feedback quizzes and peer evaluation, which were found to be highly effective in improving language skills. The third theme included challenges faced by the undergraduates including technical issues, limited digital literacy, and concerns regarding academic integrity. Some undergraduates reported difficulties in adapting to fully online assessments, while others expressed concerns about the fairness and reliability of them. Despite these challenges, the majority of participants preferred digital assessment methods over traditional approaches due to their flexibility and accessibility. This research suggests that digital assessment strategies are an important part of contemporary ESL teaching as they contribute to lifelong learning and skills acquisition. It suggests that the educators should implement a balanced approach between the formative and summative digital assessments, with sufficient training and support given to students.

Artificial intelligence (AI) is rapidly reshaping architectural practice, yet its pedagogical integration remains uneven, especially in contexts where digital infrastructure, faculty training, and curriculum reform are still developing. Focusing on Bangladesh, this paper examines how AI-powered design tools can be incorporated into undergraduate architecture education in ways that expand learning while protecting foundational design competencies. The study adopts a structured literature review, analyzing scholarship on AI in architectural practice, architecture and design education, and technology-enhanced learning. Sources were selected for their relevance to four themes: types of AI tools used in design, pedagogical opportunities, educational risks, and models for curriculum integration. The review shows that tools such as Midjourney, DALL-E, Grasshopper, Dynamo, and Autodesk Forma can support broader creative exploration, faster iteration, early exposure to contemporary professional workflows, and engagement with computational and performance-driven design. At the same time, the Bangladeshi context presents significant challenges, including over-reliance on machine-generated outputs, possible weakening of freehand and spatial reasoning skills, unresolved authorship and academic integrity questions, uneven faculty preparedness, and inequitable access to hardware, internet, and paid platforms. In response, the paper proposes a four-phase pedagogical framework: foundational manual skill development in Year 1; supervised AI-assisted ideation and image critique in Year 2; performance-based generative and parametric applications in Year 3; and ethically reflective, professionally oriented AI integration in senior studios. By framing AI adoption as a pedagogical and institutional issue rather than a purely technical one, the paper offers a context-sensitive model for balancing innovation, equity, and disciplinary values in architecture education.

In recent decades, schools have ceased to be mere educational institutions and have become key nodes for territorial cohesion, especially in rural and peripheral areas. In these territories, schools are often the only center of public infrastructure, fulfilling functions such as internet access points, state services, and community meeting places. This phenomenon has given rise to the concept of the "connected school," which integrates spatial, social, technological, and educational factors to contribute to territorial cohesion, a particularly relevant challenge in Argentina, given the fragmentation in physical and digital accessibility.

Although progress has been made in the role of schools as agents of local development, research that comprehensively addresses the interaction between school infrastructure, digital connectivity, and territoriality is still lacking. Educational and technological planning has been sectoral, without considering schools as organizers of territory, especially in rural and peri-urban areas, where problems such as population seasonality and inequality in access to services limit educational quality and territorial coverage.

This project focuses on a case study in rural areas and small towns to understand how schools can promote territorial and digital equity. The research combines quantitative and qualitative approaches, using Geographic Information Systems (GISs) to map school distribution and surveys of teachers and community members about digital connectivity and its social and educational impact.

The results are expected to contribute to improved school infrastructure planning, its role in territorial cohesion, and equitable access to educational and digital resources. Preliminary findings suggest that schools with greater digital connectivity have a positive impact on educational quality and community resilience, reducing territorial and social inequalities.

The integration of artificial intelligence (AI) into English for Academic Purposes (EAP) instruction marks a substantial transformation in technology-enhanced education, especially for postgraduate students in need of advanced linguistic and critical thinking abilities. This study investigates the integration of an AI-driven adaptive learning platform within a compulsory postgraduate public English course at Harbin Engineering University, China, aiming to enhance personalized learning experiences and improve educational outcomes. The platform employs natural language processing to offer tailored feedback on academic writing and speaking tasks, focusing on aspects such as argumentation, lexical accuracy, and disciplinary discourse norms. Utilizing a mixed-methods approach that incorporates pre- and post-assessment scores, platform analytics, and semi-structured student interviews, the research assesses the platform's effectiveness in supporting academic English proficiency. Initial results from a semester-long study (N = 85) reveal statistically significant improvements in students' academic writing proficiency (p < .05, Cohen's d = 0.62), particularly in writing coherence and disciplinary vocabulary breadth. Qualitative data indicate that immediate, personalized feedback alleviated speaking anxiety and prompted more frequent attempts at using complex language structures. Nevertheless, students with lower initial proficiency continued to face challenges, highlighting the necessity for additional instructor support. The study suggests that AI-powered tools, when integrated pedagogically, can complement traditional instructional models by providing scalable, personalized support. This may enhance linguistic proficiency while also cultivating metacognitive awareness in academic communication. The paper concludes by presenting a framework for incorporating adaptive technology into EAP curricula, highlighting the indispensable role of teachers in promoting critical digital literacy and ensuring equitable learning experiences.

Lichens are sensitive bioindicators for environmental disturbances and air pollution [1]. This research investigates the synergy between digital tools and the Parco del Pineto naturalistic site in Rome [2], grounded in Maria Montessori’s pedagogy and inclusive, student-centred outdoor education [3]. The study involved 43 third- and fourth-year students from High School L.A. Seneca in Rome. The methodology followed a multi-phase scientific approach: field observation, photographic documentation, and specimen collection. Students utilised Pl@ntNet, an AI-based identification tool [4], alongside expert guidance to foster Citizen Science [5]. Google Earth served as the primary mapping base for recording positions via .kml files, enabling the management of three-dimensional geospatial data. Using open-source GIS software, students plotted coordinates and associated each location with specific data sheets and original photographs for laboratory-based species classification. Educational outcomes were documented through group dynamics observations and a qualitative survey evaluating the efficacy of merging outdoor education with technological resources. The primary outcome was a comprehensive GIS-based mapping system documenting the territory’s ecological recovery following the 2022 fire, particularly within wetland areas. Beyond scientific findings, the results indicate that students significantly strengthened their teamwork and rigorous scientific working methods. This project bridges the gap between scientific theory and environmental protection, providing a scalable model for urban heritage management and illustrating that technology is a vital ally in cultivating a deeper respect for our planet.

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Makerspaces have gained increasing attention in recent years. Research shows that makerspaces have significant potential to enhance students’ active learning and creative thinking skills. Professional learning opportunities, such as field trips to authentic makerspaces, enable teachers to explore maker pedagogy and technologies for innovative teaching. However, not all teachers have easy access to makerspace resources. Virtual field trips offer an alternative way to bring makerspace resources to teachers who are geographically or financially limited. In this study, we explored three approaches for virtual field trips: 1) Group A: Participants remotely operated telepresence robots to move around a makerspace and communicate with staff; 2) Group B: Participants used a 360° video conferencing device, Owl technology, to access makerspace resources and communicate with staff; 3) Group C: Participants watched a recorded video of a makerspace tour. A total of 105 teachers from the rural areas of West Georgia participated in this study. Consent forms were collected from these teachers. Results showed that participants engaged more in a virtual field trip when driving a robot or using a 360° video conferencing device—they demonstrated significantly higher levels of embodiment, social presence, and behavioral engagement than participants who watched the recorded content videos. Results of the multilinear regression analysis also showed that embodiment and social presence significantly contributed to the participants’ flow experience during the field trip. The significance of the findings and their practical implications for educators, instructional designers, and researchers will be discussed in the presentation.

Generative AI has fundamentally changed who can create with technology. Educators who have never written a line of code can now use natural-language prompting to produce interactive learning materials in minutes. This paper explores how that shift enables a new approach to teaching material design: using large language models (LLMs) to convert static PDFs and PowerPoint slides into interactive HTML resources that enhance the learning experience for every student. The resulting materials feature explorable figures, self-check activities, adjustable themes, and responsive layouts. These are not accommodations for a subset of learners; they are better learning experiences by design, aligned with Universal Design for Learning (UDL). The fact that they also meet WCAG 2.1 AA accessibility standards is a natural by-product, not an additional task. PowerPoint, while familiar, is limited as a learning medium: slides enforce linear delivery and offer minimal interactivity. Meanwhile, virtual learning environments such as Blackboard support direct HTML embedding, meaning educators can deliver interactive content within the platforms students already use, maximising capabilities that often go underutilised.

Through case studies from my own mathematics teaching, I demonstrate how prompting-based workflows can transform static problem exercises into self-checking activities, convert static plots and graphs into interactive explorable versions, and create interactive diagrams and virtual lab equipment. Early student feedback suggests increased engagement with the interactive versions compared to their static predecessors.

This work contributes to technology-enhanced education by demonstrating that generative AI does not merely automate existing workflows, but enables educators to create fundamentally better learning experiences that were previously out of reach without specialist technical skills. When every educator can produce interactive HTML as easily as they currently produce a PowerPoint, the result is a better experience for all learners, and a more accessible one too.

Introduction. Engineering students report the lowest AI policy clarity in courses that say nothing — even lower than courses that ban AI. This finding emerged from a dataset spanning nine semesters and 128 course experiences at a large public research university. The authors' prior work on technology integration across the K-12-to-university pipeline has shown that the framing around a technology predicts practitioner confidence more reliably than the technology itself. This study extends that principle to AI policy and asks whether the Clarity Gap observed among engineering undergraduates appears in K-12 STEM educators encountering AI tools through professional development.

Methods. Two datasets ground the analysis. The university dataset captures student-reported AI policy clarity, tool adoption, and verification behavior across five policy categories (Disallowed, Allowed-Informal, Allowed-Formal, Encouraged, and Critical Use) from 2023 through 2025. The educator dataset draws from a multi-session PD series delivered to STEM educators, scaffolding a progression from AI-assisted curriculum design through structured verification of AI-generated content to hands-on programming with LLM assistance — a direct translation of the "Trust but Verify" framework validated on the university side. Earlier PD sessions using micro:bit devices provide a longitudinal baseline.

Results. Allowed-Informal courses — where AI use was permitted without explicit guidance — produce clarity scores significantly below prohibition. Preliminary educator data indicate a parallel pattern: educators whose schools have issued explicit AI guidance report higher baseline verification confidence than those operating without institutional direction.

Conclusions. Despite widespread AI adoption, policies governing its classroom use remain underdeveloped. Policy silence is the primary barrier to productive AI integration in both collegiate and K-12 classrooms. Mandating explicit AI guidance, at the course level for universities, at the school or district level for K-12, addresses AI integration ambiguity directly. The authors posit that a specific policy stance matters less than its existence for effective educator and student use.

Introduction: Traditional accounting education relies heavily on passive lectures, often struggling to garner practical application and intrinsic motivation. Simulation games present a promising technology-enhanced alternative by immersing students in realistic, experiential environments. This study investigates the pedagogical potential of the commercial simulation game Farming Simulator 22™ as an active learning tool to teach fundamental accounting concepts to undergraduate students with no prior accounting background.

Methods: An exploratory sequential mixed-methods design was employed to capture both measurable outcomes and detailed student experiences. Participants were undergraduate students enrolled in an introductory global accounting course. Quantitative data were collected via pre- and post-intervention surveys measuring engagement and learning outcomes. Qualitative insights were gathered through semi-structured interviews with eight students selected via stratified random sampling.

Results: While survey results indicated high perceived effectiveness of the gaming approach and improved understanding of accounting concepts, significant initial hurdles were identified. Students, particularly non-gamers, found the game's mechanics and the sheer volume of variables overwhelming. A critical precondition for success was overcoming this steep learning curve; only after students became comfortable with the gameplay could they successfully apply accounting principles. Furthermore, participants noted the risk of merely "playing rather than learning" without explicit connections to course material. Once these barriers were navigated, the simulation fostered exceptional autonomous engagement and effectively bridged the gap between theory and practice.

Conclusions: Integrating commercial simulation games into the accounting curriculum enhances student motivation and practical comprehension, but its efficacy is highly conditional. For successful implementation, educators must carefully administer instructional scaffolding to mitigate the initial overwhelm. Providing structured guidance, worksheets, and weekly debriefing sessions that explicitly link game mechanics to theoretical accounting concepts are essential preconditions to ensure the technology serves as a robust pedagogical tool rather than just a distraction.

As Generative Artificial Intelligence (GenAI) rapidly permeates higher education, its application in safety-critical STEM fields—such as civil engineering—has raised significant concerns regarding "false mastery." This phenomenon occurs when students produce plausible-sounding answers via AI that lack mechanism-based reasoning or verifiable evidence. To address this, this study proposes and evaluates a technology-enhanced scaffolding workflow designed to operationalize verification-oriented risk reasoning within a civil engineering construction safety module (N = 50).

The study structures student–GenAI interaction into five staged prompts and artifacts to ensure logical depth: (1) Scenario Interpretation and Boundary Setting: Defining problem parameters to prevent hallucinations or irrelevant AI generation. (2) Mechanism-Based Hazard Identification: Requiring students to analyze the underlying physical or causal mechanisms of potential accidents. (3) Likelihood-Severity Justification: Providing logical or quantitative defenses for assigned risk levels. (4) Control Selection: Aligning mitigation strategies strictly with the Hierarchy of Controls. (5) Verification-Oriented Reflection: Mandating uncertainty marking, evidence/source cross-checking, and detailed revision logs.

Assessment via rubric-based scoring and behavioral coding revealed significant improvements in reasoning transparency and a stronger coupling between hazard mechanisms and control logic. Furthermore, students demonstrated increased explicit verification practices, such as active uncertainty labeling and revision tracing. This study contributes a transferable GenAI-enabled learning design and assessment package—including prompt templates, expected artifacts, and scoring signals—to cultivate measurable verification literacy in safety-critical engineering education.