Online-Journals.org (International Association of Online Engineering)
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Gamification: Enhancing Constructivist Skills through Line-Following Robots
Get PDFThis study addresses the challenge of enhancing student engagement and constructivist skills in engineering education by integrating gamification with line-following robots. The problem arises from the need for more interactive and engaging learning experiences in technical disciplines, where traditional methods often fail to actively involve students in the learning process. To tackle this challenge, the study explores how gamification, using game design elements in non-game contexts, can motivate students and create a more dynamic learning environment. The main objective is to investigate the effectiveness of this approach in promoting student engagement, motivation to learn, critical thinking skills, problem solving, and student collaboration, which are all core elements of the constructivist learning theory. The research employs the analysis, design, development, implementation, and evaluation (ADDIE) model as a framework, using a quantitative research design to evaluate both validity and practicality. The study was conducted at the Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Yogyakarta, Indonesia. Data collection involved expert validation from media and gamification specialists, with the average validity scores of 0.90 and 0.89, indicating a highly valid approach. Practicality assessments from educators yielded an average score of 91.85%, while student feedback showed an effectiveness rating of 90.62%. These results highlight the significant potential of combining gamification with robotics to enhance constructivist skills in an engineering education context. Future research should investigate the long-term effects of this integration and explore its applicability across broader educational environments and age groups
Cost-Effective Electromagnetic Lens-Assisted Microstrip Patch Antenna Design for Location-Based Services in 5G/6G Technology Radio Frequency Front End
Get PDFMicrostrip patch antennas (MPAs) are popular in wireless communication systems due to their compact size and easy-to-design properties. However, the performance of such antennas sometimes becomes limited, especially when used in location-based services that require either sophisticated antenna arrays-based radio frequency front-end (RFFE) design or complex signal processing techniques. This paper introduces the concept of an electromagnetic (EM) lens-assisted MPA where a polylactic acid (PLA) substrate-based EM lens is combined with a conventional MPA. Because the EM lens has focused ability, the EM lens-assisted MPA provides improved overall antenna performance. In this paper, we design and simulate the EM lens-assisted MPA and analyze the performance at different frequencies, i.e., 4.2 GHz and 10 GHz, and dielectric substrates for the MPA, i.e., FR4, RO4350b, and RT Duroid 5880. The obtained results show that the EM lens-assisted MPA, particularly the RT Duroid substrate- based MPA integrated with the EM lens, outperforms the traditional MPA without the EM lens. Furthermore, the proposed lens antenna can steer the beam as a function of the MPA position with less complexity and improved performance. Thus, the proposed EM lens antenna in this paper has the potential to revolutionize the RFFE design to be used for location-enabled services, especially in fifth/sixth generation (5G/6G) technology
Sedentary: A Healthy Lifestyle App for Home Office Workers
Get PDFAlthough home office employment has been happening for several decades, the COVID-19 pandemic has led to an unprecedented surge in telework. Concurrently, the prevalence of sedentary individuals has gradually increased, posing health challenges. In this study, we introduce a mobile app designed to promote healthy lifestyles (HLs) among home office workers (HOWs). Central to this app is an IBM Watson Assistant-powered Chatbot, offering remote workers a near-natural interface to enhance their well-being. Users can establish lifestyle improvement goals, receive activity reminders, earn rewards upon achieving goals, and employ their smartphone’s pedometer to measure their physical activity (PA) levels. Additionally, the app includes questionnaires to gauge the user’s knowledge on sedentarism and HL. The app’s efficacy was assessed via a two-week trial involving 20 participants. The results showed that HL knowledge was improved in 46% of the users. Usability surveys yielded high ratings in terms of usefulness, user-friendliness, and recommendations
Effectiveness of Gamification in Mobile and Interactive Learning: Analysis of Approaches and Outcome
Get PDFThe use of new approaches in pedagogy, which is partly due to the digitalisation of this process, creates the language for the further evolution of the field. The purpose of the paper is to study the effectiveness of using gamification in the educational process and to investigate different research approaches and their results. The proposed study is based on a systematic review of scientific literature. Certain scientific methods were used: content analysis of professional literature. The results of the study indicate that today the possibilities of combining the traditional use of gamification and the digital environment are actively used. The study findings indicate positive effects of gamification include improved motivation for learning activities, the benefits of developing skills and abilities, the development of communication and teamwork skills, and psychological relief. The difficulty in using gamification is price. It is shown that the importance of implementing various gamification models – role-playing games, story-based learning, quests, simulations, virtual reality, etc. gamification plays a positive role primarily in the motivational component of learning. The conclusions emphasise the further prospect of studying gamification through the prism of its potential evolution. The contribution of the study lies in its systematic review of various gamification approaches in education
Understanding AI and Mobile Learning Adoption in Malaysian Universities: A UTAUT-Based Model
Get PDFThis study explores the key determinants influencing the intention to adopt artificial intelligence (AI) applications and mobile learning in Higher Education Institutions (HEIs) in Malaysia. As AI technologies and mobile learning increasingly transform the higher education landscape, it is crucial to understand the specific factors driving their adoption. The research identifies five critical determinants—social influence (SI), effort expectancy (EE), hedonic motivations (HM), performance expectancy (PE), and consumer trust (TR)—that significantly impact the intention to use AI-powered mobile learning solutions. Through a survey of 263 undergraduate and postgraduate students from Malaysian universities, the study develops an adapted model to assess these adoption factors, contributing unique insights into the integration of AI and mobile learning within the Malaysian higher education context. This model provides actionable recommendations for university administrators, educators, and mobile learning developers, offering practical guidance on promoting the adoption of these technologies to enhance student engagement and learning outcomes. By focusing on real-world application, this study not only bridges theoretical research with practical implementation but also offers valuable lessons for similar educational contexts globally, particularly in emerging markets
AI and Mobile Technologies for Driver Fatigue Detection: Sex Differences Revealed by Eye-Tracking Metrics
Get PDFThe present study examines sex differences in fatigue and visual attention during simulated driving. Using a driving simulator, we evaluated the effects of task duration and sex differences on fatigue-related eye-tracking metrics, including blink duration, fixation rate, and blink rate. Results indicate that fixation rate was significantly influenced by task duration but remained consistent across sexes, whereas blink duration exhibited marginal sex differences and a significant interaction with task duration, with females demonstrating longer blink durations compared to males. These findings suggest that males and females adopt distinct patterns in managing fatigue over prolonged tasks, with implications for visual attention and fatigue. This study advances the understanding of sex-specific fatigue responses in dynamic tasks and underscores the potential of eye-tracking technologies for improving road safety
Developing Multipath Routing Protocol Based on Source Routing Protocol in MANET
Get PDFMobile Ad hoc Networks (MANETs) provide a flexible solution for establishing networks in environments where conventional infrastructure is unavailable, such as disaster areas or military operations. However, routing in MANETs is a critical challenge due to node mobility and limited resources. Numerous protocols have been developed, though their performance varies in various conditions. This study paper introduces a multi-disjoint route technique built on the source routing principle, designed to improve MANET performance for the sake of meeting Quality of Service (QoS) requirements. The performance evaluations of the proposed on-demand multipath source routing protocol using NS-2 in comparison with other DSRbased protocols, namely Modified-DSR, Extended-DSR, and Updated-DSR, the results have suggested that the proposed on-demand multipath source routing protocol has obvious advantages in terms of Packet Delivery Ratio (PDR) and Normalized Routing Load (NRL) over the common existing routing protocols developed for MANET
Empowering Corporate Lawyers: AI-Driven Training for Strategic Leadership and Behavioral Mastery
Get PDFIn the fast-evolving corporate legal landscape, the integration of legal expertise with strategic business acumen has become indispensable. To meet this demand, e-REAL Labs, in partnership with leading legal and management experts, has developed a cutting-edge training program tailored for the corporate legal teams of a prominent multinational company. This innovative program combines advanced AI-driven simulations with an experiential learning approach to bridge the gap between traditional legal training and real-world challenges. Participants engage in immersive, high-stakes scenarios replicating corporate law practice’s complex dynamics. The curriculum focuses on building practical competencies, including collaborative business strategies, refined negotiation techniques, effective decision-making under pressure, and strategic foresight. By blending technology and expertise, the program empowers legal professionals to confidently navigate the intricate demands of today’s corporate environment. Graduates of the program benefit from enhanced negotiation skills, improved decisionmaking capabilities, and the ability to anticipate and influence multifaceted legal and business challenges. This transformative training equips corporate legal teams with the tools to excel in a competitive and dynamic global market
AI-Driven Avatars in Medical Training: Personalized Feedback for Enhanced Learning
Get PDFe-REAL Labs is at the forefront of educational technology, pioneering the use of intelligent avatars—also known as digital humans or embodied conversational agents (ECAs)—to enhance medical training. These sophisticated AI-driven avatars replicate complex human interactions, providing real-time, personalized feedback based on behavioral and conversational cues. This article presents an applied research project developed in collaboration with the Center for Medical Simulation in Boston, showcasing an innovative approach that goes beyond traditional feedback mechanisms. By enabling reflective dialogue and interactive learning, these digital humans foster deeper understanding and skill development. As dynamic learning partners, ECAs represent a transformative shift in medical education, offering an immersive and effective method for professional training. This AI-powered approach redefines the role of feedback in healthcare education, setting a new standard for simulation-based learning and professional development
A Stratified Modeling-Machine Learning Approach to Improve the Accuracy of Non-Invasive Blood Glucose Estimation Using Photoplethysmography Signals
Get PDFDiabetes is a silent killer that can only be controlled with continuous monitoring of blood glucose levels. The method commonly used is invasive and has various weaknesses, but it is more accurate than non-invasive methods. This research aims to develop a method to increase the accuracy of non-invasive estimation of blood glucose levels using photoplethysmography (PPG) signals. The proposed method is to carry out stratified modeling-machine learning. The tested classifiers were support vector machines (SVM), KNN, Naïve Bayes, decision tree, and neural network. The prediction model used simple linear, logarithmic, second-order polynomial, exponential, and power regression. Applying stratified modeling using linear regression in the non-diabetes stratum and logarithmic regression in the diabetes stratum obtained a mean absolute relative difference (MARD) value of 4.5%, root mean square error (RMSE) of 18.9 mg/dl, Pearson correlation 0.985 and Clarke error grid analysis (CEGA) 96% in region A and 4% in region B. The implementation of stratification reveals a marked improvement in efficacy, manifested as a reduction in the MARD by 77.83%, a decrease in the RMSE by 51.91%, an enhancement in the Pearson correlation by 0.065, and a CEGA by 100% in regions A and B, thereby being clinically acceptable. Implementing a stratified modeling-machine learning approach can improve the accuracy of non-invasive blood glucose level estimates