Online-Journals.org (International Association of Online Engineering)
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Applying Optimized Algorithms and Technology for Interconnecting Big Data Resources in Government Institutions
Get PDFThe quality of the data in core electronic registers has constantly decreased as a result of numerous errors that were made and inconsistencies in the data in these databases due to the growing number of databases created with the intention of providing electronic services for public administration and the lack of the data harmonization or interoperability between these databases.Evaluating and improving the quality of data by matching and linking records from multiple data sources becomes exceedingly difficult due to the incredibly large volume of data in these numerous data sources with different data architectures and no unique field to create interconnection among them.Different algorithms are developed to treat these issues and our focus will be on algorithms that handle large amounts of data, such as Levenshtein distance (LV) algorithm and Damerau-Levenshtein distance (DL) algorithm.In order to analyze and evaluate the effectiveness and quality of data using the mentioned algorithms and making improvements to these algorithms, through this paper we will conduct experiments on large data sets with more than 1 million records
Mobile Learning in Medical Coding Course: Intention to Use MedCoS
Get PDFMedical coding is a subject in which students must assign proper ICD-10 codes to patients’ diagnoses as reported in the coding exercises. However, due to students’ inadequate knowledge, incorrect codes are assigned to the cases, leading to coding errors. Thus, creating Medical Coding Simulation (MedCoS) is to help students strengthen their motor and technical abilities in challenging scenarios. The purpose of this study is to predict students’ intention to use MedCoS based on attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC). To meet the objective, SPSS was used to conduct descriptive, reliability, and multiple regression analyses. This study includes students in Semester five and six who have attended both courses. Majority respondents were female (89.9%, n=116) and aged between 23 and 24 years old (90.2%, n=102). Results showed that attitudes and perceived behavioral predicted the intention to use MedCos among the students. The significant outcome allows MedCoS to plan the next stage of the application’s development with the goal of achieving the desired improvement in course performance
The “Who” in Engineering: Sociotechnical Engineering as Memorable and Relevant
Get PDFDoes emphasizing the role of people in engineering influence the memorability of engineering content? This study is part of a larger project through which our team developed a new undergraduate energy course to better reflect students’ cultures and lived experiences through asset-based pedagogies to help students develop a sociotechnical mindset in engineering problem solving. In this study, students in the class were invited to participate in semi-structured interviews (n=5) to explore our effectiveness in helping them develop a sociotechnical mindset around energy issues and conceptualize engineering as a sociotechnical endeavor. This study focuses on an activity during the interview where the participants were asked to sort a variety of images associated with class learning experiences along a spectrum of least to most memorable. Emergent themes from students’ responses revolved around learning experiences that included global perspectives and emphasized a “who” (i.e., whose problems, who is impacted by engineering, and what type of engineers the students will choose to become) as the most memorable. Our results indicate that students found the sociotechnical aspects of the course more memorable than the traditional canonical engineering content. These findings suggest that framing engineering content as sociotechnical can be one strategy to increase student engagement, increase memorability of lessons, and help students to think more deeply about their own goals as future engineers
Survey of VR Products to Treat Social Phobia among College Students Based on Logistic Regression and K-Means Clustering Analysis
Get PDFSocial phobia or social anxiety disorder, is characterized by a fear of embarrassing situations in front of others, leading to long-term chronic anxiety disorders. The purpose of our study is to examine the market prospects of using virtual reality (VR) technology for the treatment of social phobia. Specifically, we aim to investigate the current prevalence of social phobia among college students in eight universities in Guilin and explore their willingness to adopt VR technology as a treatment option. To achieve this, we utilized various data collection methods, including questionnaire surveys, literature surveys, and field interviews. Through descriptive statistical analysis we gained insights into the respondents’ demographics and their perceptions of social phobia and its treatment. Subsequently, we constructed a binary logistic regression model to identify the influencing factors contributing to social phobia among college students. Additionally, we conducted factor analysis, which revealed that the aspects of service quality, safety, and environmental quality were or utmost concern. Finally, we employed K-Means cluster analysis to differentiate the distinctive characteristics of potential users and develop effective strategies for the advancement of VR technology in social phobia treatment
The Applications of Platinum Catalysts in PEM Fuel Cells: Process and Data Analysis
Get PDFAchieving global carbon neutrality and reducing airborne pollution require innovative solutions. One potential solution is to replace fossil fuel-based energy with clean energy production and supply, necessitating the advancement of fuel cells, metal-air cells, supercapacitors, and water splitting. This paper analyzes data and predicts future trends for the quality of catalysts, carrier structure, construction characterization, environmental impact, and recycling preparation techniques for waste platinum catalysts. The findings presented in this study serve as inspiration for related research, aiding the successful promotion of clean energy technologies
How Did We Deliver Team-Based Learning (TBL) Remotely to Overcome Digital Divide and Internet Access Inequality?
Get PDFThe shift to online learning during COVID-19 has uncovered the existing internet access inequality in the world. Shifting an interactive team-based learning (TBL) session to online is even more challenging since it necessitates interactions and feedback. Choosing the proper digital platforms for online TBL is critical to ensure achieving the intended benefits of TBL. A face-to-face TBL course was transformed fully to online. The basic TBL elements, i.e., pre-reading materials, iRAT, tRAT, and the tAPPS, remained the same in online TBL. Platforms that use less internet bandwidth and are familiar to students were used such as Google meet, WhatsApp, and Google Chat. An online questionnaire was disseminated to all students at the end of the semester to get their feedback. Sixty-six students responded to the questionnaire (54% response rate). The majority of the students (85%) perceived the online TBL positively and reported good interaction and engagement without any major technical issues. They reported that the application exercises and the online discussion through WhatsApp and the use of emoji have helped them to interact and comprehend the topics. Therefore, the use of technologies that operate at low internet bandwidth is an option to provide an equitable access to active learning
A Mobile Training Context for In-Service Teachers: Methods of Training and Task Practice to Enhance E-Content Production Skills
Get PDFMobile training is one of the modern training systems resulting from the integration of innovations in information and communication technology (ICT), which can be used to solve the problems of traditional training in educational institutions. Therefore, it is important to study the design variables of such training that enhance its effectiveness. Thus, the present study aims to design a mobile training context (MTC) and to investigate the effect of interaction between the training method, i.e., whole task (WT) versus part task (PT), and the task practice method, i.e., massed practice (MP) versus distributed practice (DP), on the skills of e-content production of 52 public education teachers in Jeddah, Saudi Arabia, through using the semi-experimental approach and the factorial design (2 × 2). Furthermore, an application-oriented knowledge test was used to measure the participant teachers’ skills through their application of 208 items related to e-content design, production, and publishing. Findings showed the effectiveness of part-task training (PTT) compared to whole-task training (WTT) and the effectiveness of the massed practice method (MPM) compared to the distributed practice method (DPM). In addition, there was a preference for the massed practice for part-task (MPPT) treatment in comparison to other treatments. This result encourages the possibility of providing a successful MTC for training in different skills. However, further research is still required to optimize the expected future potential of the mobile training context
BlockCode: A Web Application to Create Games that Support the Learning of Computer Programming Logic
Get PDFThis paper presents BlockCode, a web application developed to create board games that support the learning of computer programming logic. The goal of the games created with BlockCode is to move a bunny around a board using block-based programming in order to collect all the carrots that are placed on the board. In every game, the bunny has to deal with obstacles, represented by rocks and holes, which have to be avoided using the commands available. BlockCode was designed for teachers and students: teachers can create games, specifying the arrangement of the boards; and students play the games, specifying the sequence of commands with the aim of collecting all the carrots
Measuring Video Conferencing System Success in Higher Education: Scale Development and Evaluation
Get PDFThe COVID-19 pandemic has placed great importance on video conferencing tools in delivering instruction at higher education institutions (HEIs). Increased interest in video conferencing tools for hybrid and fully online teaching is also expected in the post-pandemic period. The main focus of this paper is on the analysis of the BigBlueButton video conferencing tool by using survey data collected from students (N = 175) at a HEI at the beginning of the COVID-19 pandemic. The assessment scales for data collection in the survey were based on the DeLone and McLean Information Systems Success Model (D&M ISSM), as well as on the concepts of usability (US), cognitive involvement (CI), and design appeal (DA). The analysis of the assessment scales indicated their good internal consistency and reliability (using the Cronbach alpha and other indicators). A correlation analysis and factor analysis were performed to assist in developing a structural model of the relations between independent variables; system quality (SYSQ), information quality (INFQ), service quality (SERQ), US, CI, and DA; and the dependent variable intention to use (IU) the BigBlueButton video conferencing system. A structural model was developed and confirmed with the use of partial least squares structural equation modeling (PLS-SEM), and the explanatory power (R2 value) of this model was .507 regarding the dependent variable IU the BigBlueButton system
Cognitive Status Analysis for Recognizing and Managing Students' Learning Behaviors
Get PDFOnline learning environments have become increasingly popular due to their flexibility and convenience, but they also present new challenges, such as maintaining student motivation and engagement. To address these challenges, it is crucial to understand and predict students’ learning behaviors. This study explores the recognition and management of students’ learning behaviors through cognitive status analysis. By conducting a thorough analysis of students’ cognitive status and applying advanced deep learning models and algorithms, this study demonstrates the effectiveness of recognizing and managing students’ learning behaviors. The proposed model combines convolutional neural networks and long short-term memory networks with attention mechanisms, which incorporate cognitive status evaluation features and use them as filters for text information. The model’s focus on text sentences with distinctive features in cognitive status evaluation leads to more effective recognition and management of students’ learning behaviors. Additionally, by integrating Most Informative Propositions and Semantic Propositional Value into the deep learning model, this study achieved excellent results in cognitive status evaluation recognition tasks. Further experiments show that by mixing different features and using advanced algorithms, the final model achieves high classification accuracy and F1 scores on multiple types of learning behaviors. Continuous assessment of students’ cognitive status and learning behaviors can lead to the development of effective learning strategies and intervention measures, which can enhance students’ mastery of knowledge and overall performance