Search Results (215)

In the era of artificial intelligence, higher education is embracing new opportunities for pedagogical innovation. This study investigates the impact of integrating AI into college English teaching, focusing on its role in enhancing students’ critical thinking and academic engagement. A controlled experiment compared AI-assisted instruction with traditional teaching, revealing that AI-supported learning improved overall English proficiency, especially in writing skills and among lower- and intermediate-level learners. Behavioral analysis showed that the quality of AI interaction—such as meaningful feedback adoption and autonomous revision—was more influential than mere usage frequency. Student feedback further suggested that AI-enhanced teaching stimulated motivation and self-efficacy while also raising concerns about potential overreliance and shallow engagement. These findings highlight both the promise and the limitations of AI in language education, underscoring the importance of teacher facilitation and thoughtful design of human–AI interaction to support deep and sustainable learning. Full article

Modification to a thin beverage consistency is frequently recommended when swallowing is impaired, but proper thickening during preparation is essential. Contemporary technologies provide innovative ways of addressing quality control due to ongoing challenges in the accuracy of beverage preparation. This study explored two-dimensional (2D) and three-dimensional (3D) methods for visualizing beverages representing different levels of consistency (thin, mildly thick, or moderately thick). A total of 48 adults with limited knowledge about swallowing and no experience with thickened beverages participated. They learned about levels of modification and then viewed 2D images (photos) and 3D virtual models of beverage content. Results showed that their ability to recognize beverage consistency and their decision confidence was generally similar across dimensions even though study participants conveyed a strong preference for viewing 3D models. Qualitative findings underscored the importance of beverage attributes, especially color. Participants differed in their perceptions in using a constant (2D) or multiple angles (3D) when evaluating visualizations. Results help inform about the potential role of visual content in developing instructional resources about thickened beverages prescribed for patients with special medical needs. Full article

This study presents the design and evaluation of AquaSignalNet, a deep learning-based system for recognizing underwater visual commands to enable the autonomous navigation of a Remotely Operated Vehicle (ROV). The system is built on a ResNet50 V2 architecture and trained with a custom dataset, UVSRD, comprising 33,800 labeled images across 12 gesture classes, including directional commands, speed values, and vertical motion instructions. The model was deployed on a Raspberry Pi 4 integrated with a TIVA C microcontroller for real-time motor control, a PID-based depth control loop, and an MPU9250 sensor for orientation tracking. Experiments were conducted in a controlled pool environment using printed signal cards to define two autonomous trajectories. In the first trajectory, the system achieved 90% success, correctly interpreting a mixed sequence of turns, ascents, and speed changes. In the second, more complex trajectory, involving a rectangular inspection loop and multi-layer navigation, the system achieved 85% success, with failures mainly due to misclassification resulting from lighting variability near the water surface. Unlike conventional approaches that rely on QR codes or artificial markers, AquaSignalNet employs markerless visual cues, offering a flexible alternative for underwater inspection, exploration, and logistical operations. The results demonstrate the system’s viability for real-time gesture-based control. Full article

This study interrogates whether Augmented Reality (AR) enhances vocabulary and content acquisition within Content and Language Integrated Learning (CLIL), situating the question in the broader debate on how immersive, multimodal technologies shape achievement and engagement. This study’s novelty lies in its direct AR-versus-print comparison in a real CLIL classroom using markerless, smartphone-based technology. Using a mixed-methods, classroom-based experiment, we drew on a convenience sample of 129 secondary students (ages 16–18), assigning them to an AR intervention (n = 64) or a print-based control (n = 65). Both cohorts received parallel instruction covering identical objectives and materials; vocabulary attainment was gauged using matched pretest and post-test measures, while engagement, attitudes, and perceived usefulness were captured through paired pre- and post-surveys and open-ended prompts. Quantitative analyses compared change scores across conditions and were complemented by qualitative summaries of learner comments. Results indicate that exposure to AR exerted a positive influence on learners’ engagement and supported learning processes, with perceptible shifts in students’ views of AR between baseline and post-intervention; nevertheless, effects were heterogeneous across instruments, items, and subgroups, suggesting that benefits accrued in a targeted rather than uniform fashion. Compared to the print-based group, students using AR demonstrated greater gains on visually supported vocabulary and content items, while other items showed no significant differences between groups. We conclude that AR constitutes a promising pedagogical resource for CLIL, capable of scaffolding vocabulary/content development and motivating participation, while the observed variability underscores the need for principled, context-sensitive integration. Future work should specify boundary conditions—such as task type, prior proficiency, cognitive load, and technology familiarity—and employ robust mixed-methods designs to determine for whom, and under which instructional circumstances, AR yields the greatest and most sustainable gains. Full article

Background: Vascular endothelial function is closely related to brain health, especially in individuals with cardiovascular risk factors. In a randomized, crossover clinical trial (NCT04121741), we have previously shown that 30 min of singing improves microvascular endothelial function in older adults with coronary artery disease. Here, we report on secondary and exploratory analyses, including (1) changes in cortisol and cytokine levels and their impact on vascular endothelial function, and (2) the impact of personal music experience on vascular function. Methods: Participants had three study visits separated by 2–7 days, according to a randomized, researcher-blinded, crossover, controlled design: (1) a 30-min period of live singing with an in-person music therapist, (2) a 30-min period of singing along to an instructional video and (3) a 30-min rest (control). Primary outcomes included macrovascular endothelial function assessed by brachial artery flow-mediated dilation (BA FMD%) and microvascular function assessed by peripheral arterial tonometry [Framingham reactive hyperemia index (fRHI) and reactive hyperemia index (RHI)]. Exploratory outcomes included (log) changes in salivary cortisol and cytokine (IL-6, TNF-α, IL-1β, IL-8) levels. Participants were asked to complete the Brief Music Experience Questionnaire (BMEQ), a 53-item validated self-report questionnaire designed to measure an individual’s overall experience with music. The BMEQ assesses how people perceive, react to, and engage with music in various aspects of their lives. Results: Sixty-five subjects (mean age 67.7 ± 6.6 years, 40% female) completed the study. Compared to those subjects completing the BMEQ (n = 31), there were no significant differences in age, sex, race, or presence of diabetes mellitus, hypertension, high cholesterol, heart failure, chronic kidney disease, or chronic respiratory disease in subjects who did not complete the BMEQ (n = 34). Total BMEQ score did not impact changes in BA FMD% (−3.49 ± 2.00, p = 0.086), changes in fRHI (0.58 ± 0.93, p = 0.535), or changes in RHI (0.73 ± 0.65, p = 0.262). When we decompose the sum of squares based on intervention, sex, race, and age, the BMEQ score does not predict changes in vascular function measures. In cross-over analyses, there were no acute changes in salivary cortisol or cytokine levels with 30 min of singing compared to control. Changes in IL-8 were directly related to changes in microvascular endothelial function (0.470 ± 0.184, p = 0.012 for RHI and 0.780 ± 0.248, p = 0.002 for fRHI). Changes in TNF-α were inversely related to changes in fRHI (−0.547 ± 0.263, p = 0.040). Changes in cortisol concentrations were not related to measures of vascular function. Conclusions: The beneficial changes in microvascular endothelial function are not modified by personal music experience in older subjects with known coronary artery disease. There were no changes in salivary cortisol or cytokine levels after 30 min of singing compared to control. Full article

Our paper introduces a novel idea of a virtual mouse character driven by gesture detection, eye-tracking, and voice monitoring. This system uses cutting-edge computer vision and machine learning technology to let users command and control the mouse pointer using eye motions, voice commands, or hand gestures. This system’s main goal is to provide users who want a more natural, hands-free approach to interacting with their computers as well as those with impairments that limit their bodily motions, such as those with paralysis—with an easy and engaging interface. The system improves accessibility and usability by combining many input modalities, therefore providing a flexible answer for numerous users. While the speech recognition function permits hands-free operation via voice instructions, the eye-tracking component detects and responds to the user’s gaze, therefore providing exact cursor control. Gesture recognition enhances these features even further by letting users use their hands simply to execute mouse operations. This technology not only enhances personal user experience for people with impairments but also marks a major development in human–computer interaction. It shows how computer vision and machine learning may be used to provide more inclusive and flexible user interfaces, therefore improving the accessibility and efficiency of computer usage for everyone. Full article

The high environmental impact caused by the accumulation of single-use plastic calls for measures to curb this problem, from a ban on single-use plastic tableware to the production of a wide range of biodegradable and reusable products. The aim of this study was to investigate how tableware made of different materials affects consumers’ sensory perception and emotional and hedonic responses when eating the same meal. In this study, four types of meals of animal or plant origin were selected for the experiments, which were served warm or cold. Accordingly, four groups of university students were instructed to taste the corresponding meal while using three sets of tableware made of different materials: polypropylene, wood/cardboard, and a stainless steel/ceramic/glass control set (regular set). Overall, the results suggest that the use of regular tableware elicited a positive emotional profile, while the use of disposable, wooden, and plastic tableware elicited negative emotional responses, which is consistent with the acceptability of the meal samples—regular tableware received higher ratings, while both types of disposable tableware received lower ratings. Finally, the material of the tableware only led to changes in odor and flavor perception when warm-served meals were sampled—higher intensities were reported when students used the regular tableware sets. Wooden cutlery imparted an atypical woody flavor to the meals, regardless of the type of meal. Full article

Educator agency in the form of choice over learning experiences is widely thought to enhance educator engagement and instructional improvement, yet causal evidence is scarce. We conducted a preregistered randomized controlled trial in an online computer science course with volunteer instructors who teach students worldwide. All instructors (N = 583) received automated feedback on their instruction, with half randomly assigned to have choice over the feedback topic. Choice alone did not increase feedback engagement or yield observable changes in practice, but it raised student attendance—an effect that was strongest for instructors who voluntarily engaged with additional training resources, including training modules and teaching simulations. For this subset of instructors, having choice over feedback had significant positive impacts on their instruction and student outcomes compared to the control group. This suggests that agency in choosing feedback topics may be most effective when combined with instructors’ intrinsic motivation to pursue self-directed improvement. Our study also demonstrates a scalable method for testing design principles in educator training and underscores the need to examine when, how and for whom agency might drive improvement. Full article

The tunnel construction environment is complex, and workers’ cognitive load directly affects safety and efficiency, making a dynamic assessment urgently needed. This study aims to explore the cognitive load of tunnel construction workers under different working environments using EEG technology. In the experimental design, subjects adapted to the virtual reality (VR) environment and received instructions before wearing a wireless EEG system and VR equipment to begin the formal experiment. Each subject underwent four rounds of experiments, corresponding to four different scenarios: control, night shift, noise, and confined space. Each round included three tasks of low, medium, and high difficulty. Analysis of EEG data showed that tunnel construction tasks in different environments significantly affected cognitive load, especially during night shifts and in confined spaces, with cognitive load increasing significantly with task difficulty. The results provide a theoretical basis for optimizing the management of tunnel construction environments and task design. Full article

Industry 4.0 has intensified the skills gap in industrial automation education, with graduates requiring extended on boarding periods and supplementary training investments averaging USD 11,500 per engineer. This paper introduces VisFactory, a multimedia learning system that extends the cognitive theory of multimedia learning by incorporating haptic feedback as a third processing channel alongside visual and auditory modalities. The system integrates a digital twin architecture with ultra-low latency synchronization (12.3 ms) across all sensory channels, a dynamic feedback orchestration algorithm that distributes information optimally across modalities, and a tripartite student model that continuously calibrates instruction parameters. We evaluated the system through a controlled experiment with 127 engineering students randomly assigned to experimental and control groups, with assessments conducted immediately and at three-month and six-month intervals. VisFactory significantly enhanced learning outcomes across multiple dimensions: 37% reduction in time to mastery (t(125) = 11.83, p < 0.001, d = 2.11), skill acquisition increased from 28% to 85% (${\eta }_p^2=0.54$), and 28% higher knowledge retention after six months. The multimodal approach demonstrated differential effectiveness across learning tasks, with haptic feedback providing the most significant benefit for procedural skills (52% error reduction) and visual–auditory integration proving most effective for conceptual understanding (49% improvement). The adaptive modality orchestration reduced cognitive load by 43% compared to unimodal interfaces. This research advances multimedia learning theory by validating tri-modal integration effectiveness and establishing quantitative benchmarks for sensory channel synchronization. The findings provide a theoretical framework and implementation guidelines for optimizing multimedia learning environments for complex skill development in technical domains. Full article

This study investigated the impact of preparing lesson plans and conducting microteaching activities—aligned with the learning outcomes of the mathematics curriculum—on the development of sustainability beliefs among teacher candidates. The rationale behind this research stems from the growing global emphasis on sustainability and the urgent need to embed sustainability literacy into teacher education programs, particularly in disciplines such as mathematics, which are often perceived as abstract and value-neutral. There is a recognized gap in equipping pre-service teachers with the pedagogical skills and conceptual awareness needed to integrate sustainability meaningfully into mathematics instruction. Employing a mixed-methods design, the Sustainability Belief Scale was administered to 45 teacher candidates (22 in the experimental group and 23 in the control group) as both a pre-test and post-test. During the intervention, participants in the experimental group collaboratively designed lesson plans and delivered them through microteaching sessions. Throughout the process, they maintained individual reflective journals. The lesson plans and microteaching performances were evaluated using instructor-developed rubrics. Data were analyzed using both quantitative statistical techniques and qualitative content analysis. The findings indicate that integrating sustainability themes into mathematics education significantly enhances teacher candidates’ sustainability beliefs and informs their pedagogical orientations. This study underscores the importance of structured, practice-based learning experiences—such as sustainability-focused microteaching—as a means to develop the competencies needed for education for sustainable development in mathematics classrooms. Full article

With advancements in remote sensing technology and very-large-scale integration (VLSI) circuit technology, the Earth observation capabilities of spaceborne synthetic aperture radar (SAR) have continuously improved, leading to significantly increased performance demands for on-board SAR real-time imaging processors. Currently, the low data access efficiency of traditional direct memory access (DMA) engines remains a critical technical bottleneck limiting the real-time processing performance of SAR imaging systems. To address this limitation, this paper proposes a dedicated instruction set for spaceborne SAR data transfer control, leveraging the memory access characteristics of DDR4 SDRAM and common data read/write address jump patterns during on-board SAR real-time imaging processing. This instruction set can significantly reduce the number of instructions required in DMA engine data access operations and optimize data access logic patterns. While effectively reducing memory resource usage, it also substantially enhances the data access efficiency of DMA engines. Based on the proposed dedicated instruction set, we designed a DMA engine optimized for efficient data access in on-board SAR real-time imaging processing scenarios. Module-level performance tests were conducted on this engine, and full-process imaging experiments were performed using an FPGA-based SAR imaging system. Experimental results demonstrate that, under spaceborne SAR imaging processing conditions, the proposed DMA engine achieves a receive data bandwidth of 2.385 GB/s and a transmit data bandwidth of 2.649 GB/s at a 200 MHz clock frequency, indicating excellent memory access bandwidth and efficiency. Furthermore, tests show that the complete SAR imaging system incorporating this DMA engine processes a 16 k × 16 k SAR image using the Chirp Scaling (CS) algorithm in 1.2325 s, representing a significant improvement in timeliness compared to existing solutions. Full article

As an introductory core course in computer science and related fields, “Fundamentals of Programming” has always faced many challenges in stimulating students’ interest in learning and cultivating their practical coding abilities. The traditional teaching model often fails to effectively connect theoretical knowledge with practical applications, resulting in a low retention rate of students’ learning and a weak ability to solve practical problems. Digital twin (DT) technology offers a novel approach to addressing these challenges by creating dynamic, virtual replicas of physical systems with real-time, interactive capabilities. This study explores DT integration in programming teaching and its impact on learning engagement (behavioral, cognitive, emotional) and skill acquisition (syntax, algorithm design, debugging). A quasi-experimental design was employed to study 135 first-year undergraduate students, divided into an experimental group (n = 90) using a DT-based learning environment and a control group (n = 45) receiving traditional instruction. Quantitative data analysis was conducted on participation surveys, planning evaluations, and qualitative feedback. The results showed that, compared with the control group, the DT group exhibited a higher level of sustained participation (p < 0.01) and achieved better results in actual coding tasks (p < 0.05). Students with limited coding experience showed the most significant progress in algorithmic thinking. The findings highlight that digital twin technology significantly enhances engagement and skill acquisition in introductory programming, particularly benefiting novice learners through immersive, theory-aligned experiences. This study establishes a new paradigm for introductory programming education by addressing two critical gaps in digital twin applications: (1) differential effects on students with varying prior knowledge (engagement/skill acquisition) and (2) pedagogical mechanisms in conceptual visualization and authentic context creation. Full article

Self-regulated learning (SRL) has been widely recognized as a critical skill for academic success in online and blended learning contexts. However, many students experience difficulty in effectively applying SRL strategies in the absence of structured instructional guidance. To address this challenge, this study developed and implemented a learning management system integrated with SRL support (SRL-LMS), specifically designed for the online component of a blended learning course. The SRL-LMS consisted of two sections: a conventional course content section and a SRL training section designed to support students in applying SRL strategies. A quasi-experimental design was adopted with 69 college students assigned to either an experimental group, with access to both course and SRL sections, or a control group, which accessed only the course section. Results indicated that students in the experimental group reported higher levels of self-regulation and showed more frequent and diverse application of SRL strategies compared to the control group. In terms of academic performance, the experimental group performed significantly better than the control group on the first exam, though no significant difference was observed on the second exam. These results highlight the effectiveness of structured SRL interventions within digital learning platforms for improving students’ self-regulatory behaviors. Future implementations should address cognitive load and incorporate strategic approaches to sustain student motivation. This study advances current SRL intervention designs and offers valuable insights for educators and instructional designers aiming to integrate targeted SRL supports in online and blended learning environments. Full article

The increasing integration of 3D technologies and machine learning is fundamentally reshaping mineral sciences and cultural heritage, establishing the foundation for an emerging “Mineralogy 4.0” framework. However, public engagement with digital 3D collections is often limited by complex or costly interfaces, such as VR/AR systems and traditional touchscreen kiosks, creating a clear need for more intuitive, accessible, and more engaging and inclusive solutions. This paper presents PETRA, an open-source, gesture-controlled system for exploring 3D rocks and minerals. Developed in the TouchDesigner environment, PETRA utilizes a standard webcam and the MediaPipe framework to translate natural hand movements into real-time manipulation of digital specimens, requiring no specialized hardware. The system provides a customizable, node-based framework for creating touchless, interactive exhibits. Successfully evaluated during a “Long Night of Museums” public event with 550 visitors, direct qualitative observations confirmed high user engagement, rapid instruction-free learnability across diverse age groups, and robust system stability in a continuous-use setting. As a practical case study, PETRA demonstrates that low-cost, webcam-based gesture control is a viable solution for creating accessible and immersive learning experiences. This work offers a significant contribution to the fields of digital mineralogy, human–machine interaction, and cultural heritage by providing a hygienic, scalable, and socially engaging method for interacting with geological collections. This research confirms that as digital archives grow, the development of human-centered interfaces is paramount in unlocking their full scientific and educational potential. Full article