Online-Journals.org (International Association of Online Engineering)
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Combined Teaching of Mathematics with the Halomda Platform
Get PDFDistance learning is very challenging for both teachers and students. Technology can help educators in combined teaching, which means combining traditional educational methods with active learning. The Halomda educational platform provides improving students’ active learning due to better students’ engagement. This enhances students’ performance as well as the ability to solve mathematics problems. In this paper, we share our experience of how using the Halomda system for combined teaching in the “differential equations” course significantly improves student learning outcomes
An Energy and Latency Trade-off for Resources Allocation in a MEC System
Get PDFThis paper addresses the issue of efficient resource allocation in a Mobile Edge Computing (MEC) system, taking into account the trade-off between energy consumption and operation latency. The increasing deployment of connected devices and data-intensive services in the Internet of Things (IoT) poses significant challenges in terms of managing computational resources. In this study, we propose a MEC system model that considers energy constraints and the need to minimize latency to ensure optimal performance. We formulate the resource allocation problem in terms of a trade-off between energy consumption and latency, and explore solutions based on heuristic task offloading techniques. Our experiments demonstrate that our approach achieves improved latency performance while reducing energy consumption. We also evaluate the impact of various parameters, such as workload and resource availability, on the energy-latency trade-off
Revolution in Engineering Education through Android-Based Learning Media for Mobile Learning: Practicality of Mobile Learning Media to Improve Electrical Measuring Skills in the Industrial Age 4.0
Get PDFThis study examines the practicality of Android-based learning media in improving students’ ability to use electrical measuring instruments in the Industrial Revolution 4.0 era. This study adopted a research and development (R&D) approach using the 4D model. The research process involved practical use tests conducted by lecturers and students using a questionnaire that evaluated convenience, time, and usability. The study’s results revealed that learning Android-based media for mobile learning showed a level of practicality that deserved a thumbs up. Aspects of convenience, time, and use all reach a good level of practicality, so they fall into the ‘practical’ category. Based on research findings, using Android-based learning media for mobile learning provides significant benefits to learning through easy access to learning materials, better interactive and practical visualization, efficiency of learning time, and self-evaluation. The benefits received can be added to understanding the use of electrical measuring instruments. However, the Android-based learning media currently being developed has not been integrated with artificial intelligence (AI), so there are still great opportunities for further research into its integration with education
Comparison of Predictive Algorithms for IOT Smart Agriculture Sensor Data
Get PDFThis paper compares predictive algorithms for smart agriculture sensor data in Internet of Things (IoT) applications. The main objective of IoT in agriculture is to improve productivity and reduce production costs using advanced technology and artificial intelligence. In this study, we compared various predictive algorithms for analyzing IoT smart agriculture sensor data. Specifically, we evaluated the performance of NeuralProphet, Random Forest Regression, SARIMA, and Artificial Neural Networks (ANN) by KERAS algorithms on a dataset containing temperature, humidity, and soil moisture data. The dataset was collected using IoT sensors in a smart agriculture system. The results showed that Random Forest Regression, Seasonal ARIMA, and Artificial Neural Networks by KERAS algorithms outperformed NeuralProphet algorithm in terms of accuracy and computational efficiency
Perfusionists’ Perception of a Blended Training Process in the Management of Extracorporeal Membranes
Get PDFDuring the SARS-CoV-2 pandemic, many challenges were faced in the global healthcare system, one of which was the lack of competent professionals to implement therapies such as extracorporeal membrane oxygenation (ECMO), which proved to be lifesaving during the H1N1 virus infection. In response to this need, this project aimed to determine the characteristics of a blended training process to contribute to the development of competencies in the management of ECMO therapy and to understand the perception of participants regarding this training process as a suitable strategy for competency development. A mixed design with a descriptive scope based on design-based research was used. The main results indicated that the designed learning environment was suitable for competency development in ECMO therapy management, as well as the importance of including high-quality simulation scenarios in the development of skills for managing this type of therapy. However, the most significant impact was observed in the development of competencies and skills of the participating healthcare professionals through the process of feedback
Meta-Analysis of Different Mobility Devices for Rehabilitation of Persons with Disabilities
Get PDFLoss of physical mobility poses significant challenges to full participation in daily activities and can even lead to complete limitations. In India alone, based on census data from 2011, there are over 5.5 million individuals with lower limb disabilities who rely on manually propelled wheelchairs for their mobility needs. While wheelchairs, crutches, and tricycles are commonly used mobility aids in India, this paper explores mobility technologies that have been conceptualized and developed in other parts of the world to assess their potential applicability in the Indian context
Development of the Hands-free AI Speaker System Supporting Hands-on Science Laboratory Class: A Rapid Prototyping
Get PDFThe recent progress of natural language processing (NLP), speech recognition, and speech generation envisions using hands-free artificial intelligence (AI) speakers in classrooms to support student learning. In science education, the conventional hands-on laboratory education has been considered crucial in fostering students’ manipulative experimentation skills. However, touching things with gloved hands other than experimental equipment and apparatuses is strictly restricted because of the safety issue, which calls for another channel to get timely support. Therefore, we ideated that adopting hands-free AI speakers in the hands-on science laboratory classroom would support student learning. Using the rapid prototyping method, we designed and developed an AI speaker-based system that answers student queries concerning solution-making, experimental process, and waste liquid disposal, which corresponds to the initial, middle, and final phases of a laboratory class. The system was internally validated by usability tests of 9 expert panels and 18 university students, and then revised. The revised system was externally validated in an analytical chemistry experiment class for 3 sessions with 13 university students. We present the result of the prototype development, internal and external validations with quantitative and qualitative data. The AI speaker system enabled students to use the auditory learning mode in the laboratory while concentrating on the experimentation with their hands in the external validation
Experience with Online Learning of Mathematics in Primary Education
No full textA spread of COVID-19 has significantly influenced teaching methods at universities all over the world. In 2020, face-to-face lectures at our university were banned, or were allowed only with limited number of students. Thus, in an effort to keep high academic standards, teachers had to rely on synchronous and asynchronous forms of online learning. The paper analyze our experience with online learning of the subject Mathematics in Primary Education. We focus on several problems: an influence of a ban of face-to-face lessons to students’ ability to pass the final test, difference in level of knowledge of full-time and part-time students, correlation between an average study mean and results in a final test, impact of online learning on the satisfaction of students with their results, students’ preference of face-to-face lessons to online learning. The paper expands the results presented on the international conference XXXV DIDMATTECH 2022, published in the collection of abstracts
The Implementation of Online Learning in Conventional Higher Education Institutions During the Spread of COVID-19: A Comparative Study
Get PDFThe purpose of this study is to investigate and explore the degree of success of the implementation of online learning in conventional higher education institutions instead of face-to-face learning during the spread of the Covid-19 Pandemic during the 2019/2020 academic year, via exploring the undergraduate students' perceptions of the application of the online learning system at Ajman University in UAE, and Griffith University in Australia. In the study, the descriptive approach was used. A questionnaire consisting of 40 items was designed and distributed to 630 students from Ajman University and 675 students from Griffith University, who were randomly selected from different faculties of the two universities during the 2019/2020 academic year during the COVID-19 pandemic. The results of the study revealed that students' a moderate satisfaction with the University's readiness, training, and technical support for online learning and the university's teaching and learning process during the COVID-19 pandemic, with female students finding them more satisfaction than male students. Disciplines and computer skills also showed an impact on such satisfaction, with Pharmacy & Health Science College students at Ajman University and Architecture, Art, and Design discipline students at Griffith University, and those with excellent computer skills in both Universities. In addition, the results showed positive attitudes of students towards the use of online learning at the two universities during the COVID-19 pandemic
A New Resource Recommendation Method for Experiential Leaching Based on the Completion Degree of Online Learning Tasks
Get PDFExperiential Learning (ExL) is an effective way to consolidate theoretical knowledge and deepen understandings, and the recommendation of ExL resources needs to also take the effect of students’ theoretical learning into consideration. However, existing studies generally ignore the stage-by-stage assessment of students’ completion of online learning tasks, and the recommendation performance of existing resource recommendation models for ExL is not satisfactory enough. Therefore, the recommendation method needs to be innovated, and the interpretability of recommendation results is facing challenges. To respond to these issues, this paper studied a new resource recommendation method for ExL based on the completion degree of online learning tasks. At first, the paper gave the principle of recommending ExL resources based on the completion degree of online learning tasks, and built an online learning task completion degree prediction model. Then, this paper adopted a bi-directional GRU network model based on attention mechanism to analyze the recent online learning behavior sequence of students and attain the completion degree of students’ short term learning tasks. After that, a knowledge map representing ExL resources and the correlation of knowledge attributes was drawn; by combining the completion degree of both the short-term and long-term learning tasks, the ExL resources suitable for students were recommended to them. At last, experimental results verified the effectiveness of the constructed model