Location information is the most crucial information used in context-aware applications, e-commerce and IoT-based consumer applications. Traditional methods doesn’t focus on network coverage, accuracy, hardware cost, and noise in dense environment. To defeat these issues, this paper presents a novel localization algorithm for UWB nodes adopting self-calibration and ToA measurement for context-aware applications. The Link quality induction values are used instead of RSSI for distance estimation by costing technique. A calibration factor (CF) is further introduce to automatically update the location information in mobility. As the signal strength can be distorted heavily due to shadowing and multi-path fading, the localization is estimated in noisy condition and extended Kalman filtering (EKF) is applied to refine the node coordinates. Simulation results shows that the positioning error is decreased with an overall accuracy of 0.23m and standard-deviation of 0.76m.

Creativity has long been viewed as the bastion of human expression. With the advent of generative artificial intelligence (AI), there is an emerging notion of artificial creativity that contests traditional perspectives of artistic exploration. This paper explores the complex dynamics of this evolution by examining how generative AI intertwines with and transforms the art world. It presents a comprehensive analysis of the challenges posed by generative AI in art, from questions of authenticity and intellectual property to ethical dilemmas and impacts on conventional art practices. Simultaneously, it investigates the revolutionary opportunities generative AI offers, including the democratization of art creation, the expansion of creative boundaries, and the development of new collaborative and economic models. The paper posits that the integration of generative AI in art is not just a technological advancement but a significant cultural shift, which necessitates a reevaluation of our understanding of art and the artist. It concludes with a forward-looking perspective, advocating for a collaborative approach to harness the potential of this technology in enriching human creativity and ensuring the vibrant evolution of the art world in the era of AI-driven generation.

Teachers play a central role in achieving the mission, vision, and goals of educational institutions. However, the multitude of responsibilities and obligations they must fulfill demands a high level of productivity. Consequently, productivity software is increasingly becoming a necessity for teachers to lessen their day-to-day work pressure and instead focus on offering quality education. Despite their popularity, the key antecedents and precursors affecting the intention to use productivity software have yet to be investigated. Therefore, the goal of this study was to determine what factors contribute to the adoption of productivity software by applying the theoretical lens of the Technology Acceptance Model (TAM). A total of 947 responses from basic and higher education teachers were analyzed using a structural equation modeling approach. Results show that the usefulness and ease of use of productivity software are key in predicting behavioral intention. It is also indirectly affected by external variables such as subjective norms, professional reputation, job relevance, and output quality through perceived usefulness as well as facilitating conditions and self-efficacy through perceived ease of use. Overall, the findings of this study support the applicability of the specific TAM version as well as its employment in the context of productivity software.

This manifesto critically examines the unfolding integration of Generative AI (GenAI), chatbots, and algorithms into higher education, using a collective and thoughtful approach to navigate the future of teaching and learning. GenAI, while celebrated for its potential to personalize learning, enhance efficiency, and expand educational accessibility, is far from a neutral tool. Algorithms now shape human interaction, communication, and content creation, raising profound questions about human agency and biases and values embedded in their designs. As GenAI continues to evolve, we face critical challenges in maintaining human oversight, safeguarding equity, and facilitating meaningful, authentic learning experiences. This manifesto emphasizes that GenAI is not ideologically and culturally neutral. Instead, it reflects worldviews that can reinforce existing biases and marginalize diverse voices. Furthermore, as the use of GenAI reshapes education, it risks eroding essential human elements— creativity, critical thinking, and empathy—and could displace meaningful human interactions with algorithmic solutions. This manifesto calls for robust, evidence-based research and conscious decision-making to ensure that GenAI enhances, rather than diminishes, human agency and ethical responsibility in education.

Field trips are steadily declining due to limited funding, time constraints, safety concerns, and other logistical issues. Many schools are resorting to a virtual field trip (VFT), especially when education is disrupted due to public health concerns, natural disasters, or other unforeseen significant events. Virtual reality as a common form of VFT is likely not an option for many schools due to cost and other barriers. The purpose of our study was to explore the potential of going in a VFT using 360-degree (360°) videos as an alternative to a physical field trip in primary education. We recruited third-grade pupils (aged 8–9) from two private elementary schools to experience VFTs using 360° videos (360V) and regular videos (REGV). Using a switching-replications experimental design, we compared their content recall (assessment tests) and VFT experience (attitude, perceived usefulness, involvement, inquiry, video engagement, and virtual guide) across four-time points. Our results show that the increase in content recall scores of 360V groups after VFTs was consistently higher compared to REGV groups at all time points, although it was only significant in one quarter. We also found pupils’ video engagement, involvement, and attitude as significant factors in their VFT experience. These results call attention to a possible implementation of VFTs and continue the long-standing tradition that has been acknowledged as a student-centered, interactive instructional method.

Computer programming is a difficult course for many students. Prior works advocated for group learning pedagogies in pursuit of higher-level reasoning and conceptual understanding. However, the methodological gaps in existing implementations warrant further research. This study conducted a three-armed cluster-randomized controlled trial to comparatively evaluate the social and cognitive effects of group learning pedagogies in computer programming. Following an apprenticeship model, each group has a designated master: drivers in pair programming (PP), peer leaders in peer-led team learning (PLTL), and practitioners in practitioner-assisted group learning (PAGL). In all course deliverables, the PP group received the lowest mean scores. Meanwhile, no significant difference was found between the PLTL and PAGL groups. Except for psychological safety, social factors such as task cohesion, interdependence, and group potency were significantly different between the groups. Both PLTL and PAGL groups reported a significant increase in social factors after 14 weeks of intervention. These findings provide a rationale for educational leaders and teachers to formulate curricular plans that integrate PLTL and PAGL in computer programming education. Overall, this study contributes to the literature on group learning, expands the pedagogies in computer programming, and serves as additional empirical evidence on cognitive apprenticeship and sociocultural perspectives of learning.

The field of health and medical sciences has witnessed a surge of published research exploring the applications of ChatGPT. However, there remains a dearth of knowledge regarding its specific potential and limitations within the domain of nutrition. Given the increasing prevalence of nutrition-related diseases, there is a critical need to prioritize the promotion of a comprehensive understanding of nutrition. This paper examines the potential utility of ChatGPT as a tool for improving nutrition knowledge. Specifically, it scrutinizes its characteristics in relation to personalized meal planning, dietary advice and guidance, food intake tracking, educational materials, and other commonly found features in nutrition applications. Additionally, it explores the potential of ChatGPT to support each stage of the Nutrition Care Process. Addressing the prevailing question of whether ChatGPT can replace healthcare professionals, this paper elucidates its substantial limitations within the context of nutrition practice and education. These limitations encompass factors such as incorrect responses, coordinated nutrition services, hands-on demonstration, physical examination, verbal and non-verbal cues, emotional and psychological aspects, real-time monitoring and feedback, wearable device integration, and ethical and privacy concerns have been highlighted. In summary, ChatGPT holds promise as a valuable tool for enhancing nutrition knowledge, but further research and development are needed to optimize its capabilities in this domain.

Despite originating in the tech industry, hackathons have now been adopted in a variety of domains. However, little is known about the status of hackathon literature within educational research. As the number of studies grows, it is essential to develop an understanding of the current state and identify prevalent topics and trends shaping the literature. Toward this goal, this study conducted a bibliometric analysis and scoping review on hackathon research in the field of education. A total of 249 documents written by 1,309 authors and published in 180 unique sources for the period 2014–2022 were identified. Collectively, the dataset amassed 1,312 citations with an average of 6.69 citations per document. The most prevalent subject areas were computer science, social sciences, engineering, medicine, and business. Word frequency analysis showed that “innovation” was the most occurring word, which represents the fundamental objective of hackathon events. The most influential work was the analysis of hackathons as an informal learning platform. Engineering education was the most trending topic while healthcare is an emerging research cluster. Overall, this study provides a better understanding of the hackathon literature and its research landscape in an educational setting.

The transition to a Circular Economy (CE) depends on several factors, such as the implementation of circular business models. Although circular business models were developed, there are socio-cultural distinctions that need to be considered. One such distinction is the sachet culture of the Philippines. The country's consumers use single-use sachets for daily needs, including body care and hygiene. As the local sachet culture lead to significant waste emission to the ocean, designing circular business model for switching to a circular product (e.g., refillable shampoo bottle) is a key measure towards sustainable societies. The design of this business model, however, will need to consider consumer preference. In this sense, modeling consumer preference provides insights on how enterprises can design consumer-centric circular business models. The present study modeled consumer preference between single-use plastic shampoo sachet and refillable shampoo bottles through binary logistic regression, considering responses from 457 consumers of Metro Manila, Philippines. The independent variables used were the socioeconomic and demographic characteristics, product channel, and usage. The dependent variable was consumer preference between using sachet or refillable bottles shampoo. The model indicated a good fit with a McFadden R2 of 0.255. The model identified age, gender, education, environmental awareness, budget, daily use, and retailer as statistically significant independent variables. The variable 'environmental awareness' attained the highest significance for socioeconomic and demographic characteristics. Meanwhile, the variable 'retailer' attained the highest significance for product channel and usage. The two variables had the highest influence on consumer preference. This study recommends enterprises to focus on utilizing malls as the product channel and on ecolabelling of products. Future research works may use the model in integrating consumer preference on circular economy scenarios. Enterprises may also use the model in designing circular business models suitable for the target market.

Over the past decade, several studies have been conducted to discover a better-performing multipath clustering technique. Developing a multipath clustering technique with better accuracy performance is a big challenge considering the varying properties of the multipath propagations that change over time. In this study, several clustering techniques have been investigated and compared to the newly-developed technique for performance analysis. Using the Jaccard score as a metric for the accuracy of grouping correctly the wireless multipaths, the performance of the different clustering techniques has been determined and compared to the newly-developed technique. The proposed clustering algorithm shows improved performance in the indoor channel scenarios but needs further investigation in the semi-urban environment.