Online-Journals.org (International Association of Online Engineering)
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Enhancing Information Literacy for Spotting Fake News: A Study on the Efficacy of a Serious Game for M-Learning Across Different Age Groups
Get PDFWith so many online information sources in recent years, it has become increasingly difficultto determine if the content is based on facts, half-truths, or lies. As a result, the goal of thisresearch is to propose a serious game design for learning to evaluate sources using the CRAAPtest. In the game, players take on the role of librarians who must evaluate news from socialmedia and newspapers, determine whether it is fake or true, and then inform the people ofthe city. During their efforts to make the correct decision, the players are able to observe andlearn about the impact of fake news on the community and the city as a result of their decisions.To evaluate the game, we did a randomized online field study, including quantitativeresearch based on pre-posttests involving 351 participants. The results revealed that using aserious game of “How to Spot Fake News” can improve the knowledge of information literacyneeded to evaluate online sources of information. Finally, we provide preliminary evidencethat gaming improves people’s ability to recognize and resist misinformation
Faculty Perceptions of Online Learning During the Coronavirus Outbreak
Get PDFThis study examined the perceptions of faculty members at Ajman University during the period of COVID-19 to estimate the reality of the experience of employing E-learn is applied during the 2020/2021 academic year at higher education establishments in UAE. A descriptive method was adopted in the research. The study participants consisted of all staff of the faculty (274) of Ajman University who were selected from different faculties with different specializations in the academic year 2020-2021. A questionnaire, consisting of (38) items, was developed as an instrument for the study after its validity and reliability were verified. The results indicated that faculty members' perspective of Ajman university as one of UAE universities as being highly prepared, well trained, and equipped to apply online learning at the period of the Covid-19. The findings also indicated that the faculty members’ perspective related to the process of teaching and learning via online learning reached at a moderate level, and the obstacles encountering the application of online learning reached at a high level, while their perspective concerning suggestions to develop the online learning experience was at mid-level. Faculty members' responses regarding applying online learning differed according to the college variables came with favor for Medicine college, depending on the year of experience (in favor of 5- to less than 10 years), and depending on gender and academic rank of faculty members (the perspective of faculty members is statistically insignificant according to the gender and academic rank variables
Smartphone-Based Wearable Gait Monitoring System Using Wireless Inertial Sensors
Get PDFThis paper presents a wearable virtual reality system with a wireless network of inertial sensors for lower limb monitoring. The system comprises seven sensor nodes sending data wirelessly to a master node. The information is then collected, organized, and sent to a screening device via a serial interface. An application executed either on a smartphone or a personal computer features an avatar which represents the received data and mimics the sensed movements of the patient, providing online feedback during and after the execution of a therapy. The data resulting from the therapy execution can be uploaded to a web server to facilitate the assessment and decision-making by health professionals. A pendulum featuring a rotary optical encoder is used for sensor functional behavior validation. In addition, the orientation angles measured by the proposed system are compared with respect to measurements from the motion analysis software Kinovea. The delay between the patient's body movement and the avatar is 33 ms, which is acceptable for visual feedback. This system is portable, inexpensive and enables a patient to complete physical therapy sessions at home or anywhere, with the advantage of enabling visual feedback through an avatar during rehabilitation therapy and allowing the reproduction of a therapy session for further analysis
Anomaly Detection from Crowded Video by Convolutional Neural Network and Descriptors Algorithm: Survey
Get PDFDepending on the context of interest, an anomaly is defined differently. In the case when a video event isn't expected to take place in the video, it is seen as anomaly. It can be difficult to describe uncommon events in complicated scenes, but this problem is frequently resolved by using high-dimensional features as well as descriptors. There is a difficulty in creating reliable model to be trained with these descriptors because it needs a huge number of training samples and is computationally complex. Spatiotemporal changes or trajectories are typically represented by features that are extracted. The presented work presents numerous investigations to address the issue of abnormal video detection from crowded video and its methodology. Through the use of low-level features, like global features, local features, and feature features. For the most accurate detection and identification of anomalous behavior in videos, and attempting to compare the various techniques, this work uses a more crowded and difficult dataset and require light weight for diagnosing anomalies in objects through recording and tracking movements as well as extracting features; thus, these features should be strong and differentiate objects. After reviewing previous works, this work noticed that there is more need for accuracy in video modeling and decreased time, and since attempted to work on real-time and outdoor scenes
Metaheuristics: A Review of Algorithms
Get PDFIn science and engineering, many optimization tasks are difficult to solve, and the core concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics have gained significant attention in recent years, with nature serving as the fundamental inspiration where self-organization property led to collective intelligence emerging from the behavior of a swarm of birds or colony of insects or more and more natural behavior. These swarms or colonies, even with extremely low individual competence, have the ability to accomplish many complicated activities that can be considered necessary for their existence. Accordingly, many MH algorithms have been developed based on natural phenomena. In this article, an analysis review of more than one hundred metaheuristics have been made. Further, the main contributions of this article are to give some vital insights about metaheuristics, presenting and proposing the general mathematical framework of MH algorithms and dividing it into a number of tasks with possible progress for each task. While there are still many open issues in this field, it is worth noting that there have been significant advancements in recent years. As a result, new algorithms are continuously being proposed to address these challenges
A Convolution Neural Network Design for Knee Osteoarthritis Diagnosis Using X-ray Images
Get PDFKnee osteoarthritis (OA) is a chronic degenerative joint disease affecting millions worldwide, particularly those over 60. It is a significant cause of disability and can impact an individual's quality of life. The condition occurs when the cartilage in the knee joint wears away over time, leading to bone-on-bone contact, which can result in pain, stiffness, swelling, and decreased range of motion. Deep neural networks, especially convolutional neural networks (CNN), are powerful tools in medical applications such as diagnosis and detection. This research proposes a CNN model to classify knee osteoarthritis into five categories using x-ray images. These classes are labeled: Minimal, Healthy, Moderate, Doubtful, and Severe. Furthermore, the proposed CNN model has been compared with two pre-trained transfer learning models: Xception and InceptionResNet V2. These models were evaluated based on precision, recall, F1 score, and accuracy. The results showed that although all three models performed very well, the proposed model outperformed both transfer learning models with 98% accuracy. It also achieved the highest values for other parameters such as precision, recall, and F1 score. The proposed model has several potential applications in clinical practice, such as assisting doctors in accurately classifying knee osteoarthritis severity levels by analyzing single X-ray images
Teachers’ Digital Skills and Methodological Characteristics of Online Education
Get PDFIn education, learning and teaching supported by information and communication technology tools are increasingly coming to the fore. In order to implement digital education, it is essential to develop teachers' digital skills, especially in terms of tool use and content development. During the period of school closures during the pandemic and the transition to online education, the digital preparedness of education participants became increasingly emphasized. Online education has created many difficulties for teachers, students and parents. After overcoming the initial technical problems, the methodological renewal of education became a key issue. Our research examined online education during the COVID-19 period, its positives, negatives, methodological aspects, and the impact of online education on classroom education. The research results can be used, among other things, in teacher training and further teacher training, as they draw attention to the specifics of digital/online education, as well as the necessity and possibilities of developing digital skills
Imagineering MOOC Instructional Design Model to Enhance Creative Thinking and Creative Health Media Innovation
Get PDFThe research aims to redesign and develop the Imagineering MOOC Instructional Design model (I-MOOC ID model) to enhance creative thinking and creative health media innovation. The exploratory sequential design mixed-method research method was used, and it was divided into three phases: (1) investigation and synthesis of the composition of the I-MOOC ID model based on qualitative research methods by using scoping reviews; (2) redesign and validation of the I-MOOC ID model based on quantitative research methods through measurement of items with the Content Validity Index (CVI); and (3) assessment of the suitability of the I-MOOC ID model based on quantitative research methods. The findings indicate that: (1) The I-MOOC ID model is composed of five compositions: 1) educational stakeholders; 2) the Imagineering learning experience cycle, which consists of nine steps: inspire, imagine, design, develop, present, publish, improve, evaluate, and reflect; 3) the MOOC learning platform; 4) the course syllabus; and 5) authentic assessment; (2) The I-MOOC ID model has five main processes and 16 sub-processes; and (3) The experts agreed with the overall model in terms of the instructional design based on integrating technological pedagogical content knowledge (TPACK) in the digital age to develop learners’ learning outcomes and rated the suitability of the model as most suitable, with a combined mean of 4.72. The standard deviation was 0.47
Validation of the Digital Transformation Model of the Universidad Autónoma de Chile
Get PDFThe emergence and massification of digital technologies are having such an impact on educational systems that universities are being forced to design transformation processes that make it possible to ensure the gradual incorporation of technologies into academic-administrative processes with a view to achieving greater student-centered educational quality. In response to this need and for the specific case of the Autonomous University of Chile, a digital transformation model composed of nine dimensions and 54 indicators was designed, which was subjected to an analysis process through structural equation modeling to check its consistency, reliability, and validity. With the data resulting from the application of surveys to 97 undergraduate students from that university, it was possible to demonstrate that the variables considered, and their corresponding dimensions form a solid construct that can explain the preliminary model of the digital transformation process at the university. Therefore, even recognizing limitations of a methodological nature, the model was intrinsically validated by the data. The findings represent a first approximation for the construction of a new academic-administrative scenario at the Autonomous University of Chile, which is based on the proper use of scientific-technological advances that have occurred in the global context
Influencing Factors of the Quality of MOOCs Based on the KANO Model
Get PDFMassive open online courses (MOOCs) represent a new online course and teaching mode, offering targeted instruction and timely services to learners. They have become a key direction for reforming online education. Although MOOCs have experienced significant growth in recent years, the quality of courses published on platforms varies greatly, and scientific quality evaluation mechanisms are lacking. Existing studies on online course quality have primarily relied on questionnaire survey data. In the online environment, an abundance of comment data on platforms reflects learners’ perceptions of course quality, and an analysis mode based on learning comments can address the limitations of questionnaire surveys effectively. In this study, comment texts from learners on Chinese university MOOC platforms were chosen as research data. The influencing factors of online open-course quality were analyzed using the KANO model combined with the ordinal Logit regression method. Results demonstrate that system features, video production, teaching level of teachers, usefulness of teaching content, and comprehensiveness of teaching content are essential quality factors. Course-supporting information is considered an expectant quality factor. Teachers’ teaching style and course interaction are categorized as engaging quality factors. This study provides valuable insights for improving MOOC quality in Chinese universities