Online-Journals.org (International Association of Online Engineering)
Not a member yet
9805 research outputs found
Sort by
Time Series Analysis with Systematic Survey on Covid-19 Based Predictive Studies During Pandemic Period using Enhanced Machine Learning Techniques
Get PDFCoronavirus 2 virus is responsible for the spread of the infectious disease COVID-19 (also known as Coronavirus disease). People around the globe who got infected with the virus experienced a respiratory illness that could become as serious as leading someone to lose their life. However, the upside of the pandemic is that it has led to numerous types of research and explorations, majorly in the medical science field. Since a systematic survey of previous research activities and bibliometric analysis gives a brief idea about such contributions and acts as a reference to future research, this study aims to cover the research related to COVID-19 in the computer technology domain. It is limited to the works accepted and accessible with the keywords - Covid-19, prediction, and pandemic, in the Scopus search engine to justify the scope of this survey. Further, the paper highlights a few prior works used for predictive analysis and presents a quantitative angle on their algorithms. Earlier works showcase Time Series Analysis using ARIMA/SARIMA models for predicting the vaccination rates, and Extreme Gradient Boosting (XGBoost), Xtremely Boosted Network (XBNet) Regression, and Recurrent Neural Network (RNN) for Confirmed, Cured, and Death cases. Amongst the algorithms used in the latter use case, XBNet regression performed better than XGBoost regressor
Prediction of Depression via Supervised Learning Models: Performance Comparison and Analysis
Get PDFThis document Among all the various types of mental and psychosocial illnesses, the most commonly occurring type is depression. It can cause serious problems such as suicide. Therefore, early detection is important to stop the progression of this disease that could endanger human lives. Predicting and detecting early-stage depression using machine learning (ML) techniques is a promising strategy. This study’s main purpose is to assess which ML techniques are highly appropriate and accurate regarding such diagnoses. Six supervised ML techniques namely: K-nearest neighbor (KNN), Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), Support vector machine (SVM) and Naive Bayes (NB) were applied on dataset collected from Kaggle and compared for their accuracy (ACC) and performance in predicting depression. The performance of each model was evaluated using 10-fold cross-validation and evaluated in terms of ACC, F1-score, Precision (PR), and Sensitivity (SEN). Based on the experimental results analysis, we can conclude that SVM and LR performed better than all other methods with an ACC of 83,32%. Therefore, we found that a simple ML algorithm can be used to assist clinicians and practitioners predict depression at an early stage, with excellent potential utility and a considerable degree of ACC
Spatial Strategies Employed by Blind and Low-Vision (BLV) Individuals on the Tactile Mental Cutting Test (TMCT)
Get PDFSpatial ability is a well-known predictor of success in science, technology, engineering, and mathematics (STEM) fields. The purpose of this study was to investigate and understand the spatial strategies that were used by blind and low-vision (BLV) individuals as they solved problems on the tactile mental cutting test (TMCT), an instrument that was designed to measure the spatial ability of BLV audiences. The TMCT is an accessible adaptation of the older, 1938 version of the mental cutting test (MCT) that has been used extensively in spatial ability research. Additionally, this paper seeks to compare these strategies with existing strategies that have been investigated with sighted populations. The BLV community is underrepresented in engineering and in spatial ability research. By understanding how BLV students understand and solve spatial problems and concepts, educators can develop and enhance educational content that is relevant to this population. By incorporating perspectives from the BLV community and making STEM curricula accessible to this population, more BLV individuals may be encouraged to pursue STEM or engineering career pathways
Proposing a Multi-Stakeholder Lens to Examine Global Community-Based Design Projects
Get PDFOne implementation of global, community-based, engineering-student design projects invites students to practice design from a distance. Though it may not be possible to bring an entire engineering design class to the international location for students and various stakeholders to interact, a meaningful global experience can be educational and beneficial for all stakeholders. Recognizing that the impact of community-based projects extends beyond the students to numerous stakeholders, this paper proposes a multi-stakeholder lens which examines the roles, interactions, motivations, and responsibilities of stakeholders in a global, community-based design project. The lens was developed in part by a case study of a global design project connecting a first-year Canadian engineering design course, a rural Kenyan preschool, a non-profit organization, and additional Kenyan and Canadian stakeholders. Written by three of the stakeholders in the case study, the course instructor, a Canada-based community partner, and a design student, this paper concludes with recommendations on how to incorporate global projects in a domestic setting. Ultimately, adopting a multi-stakeholder lens transitions a myopic student-centric focus to an inclusive experience for all stakeholders, creating partners in the design and achieving a greater set of objectives
Learning Mathematics with Large Language Models: A Comparative Study with Computer Algebra Systems and Other Tools
Get PDFArtificial intelligence (AI) has permeated all human activities, bringing about significant changes and creating new scientific and ethical challenges. The field of education could not be an exception to this development. OpenAI’s unveiling of ChatGPT, their large language model (LLM), has sparked significant interest in the potential applications of this technology in education. This paper aims to contribute to the ongoing discussion on the role of AI in education and its potential implications for the future of learning by exploring how LLMs could be utilized in the teaching of mathematics in higher education and how they compare to the currently widely used computer algebra systems (CAS) and other mathematical tools. It argues that these innovative tools have the potential to provide functional and pedagogical opportunities that may influence changes in curriculum and assessment approaches
Practical Analysis of Digital Technology in an Electronic Education Platform in PE Training
Get PDFTo improve the practical effect of digital technology (DT) in electronic education platform (ECP) in sports training, this study proposes using OpenPose as the main method of posture matching in sports teaching. MobileNet was introduced to replace the backbone network in OpenPose to improve the efficiency of the model. At the same time, self-attention mechanism (SAM) is introduced to improve the accuracy of the model. In the performance verification results, the proposed algorithm has a mean mean absolute error (MAE) of 0.793 and a root mean square error (RMSE) of 0.628. The accuracy of the proposed algorithm reached a maximum of 0.893 in the test set. The accuracy of the proposed algorithm exceeds 90% in the training set. In the practice of physical education (PE) and training, the absolute error between the actual value and the predicted value does not exceed 1.5 cm, while the relative error does not exceed 1.2%. The minimum absolute error and relative error are 0.01 cm and 0.2%, respectively. The proposed algorithm has high prediction effect and performance, and can be applied to PE training
Promoting Virtual Learning Management Competencies in the Metaverse with Mobile Technology to Support Competency-Based Learning for Computer Major Preservice Teachers
Get PDFThe metaverse, a fundamental framework with the potential to revolutionize social communication and learning processes, offers an enhanced learner experience for accessing the real world. Proficiently developing virtual classrooms and effectively managing learning with current technology are essential skills for teachers. This study aimed to develop competency- based learning activities (CBLA) designed to enhance virtual learning management competencies among computer teacher students in the metaverse, using mobile technology to support. The research employed purposive sampling, selecting 78 students for participation. Data analysis involved statistical measures such as the mean, standard deviation, and onegroup pre-test-post-test analysis of variance (ANOVA). The findings revealed that the CBLAs developed to enhance virtual learning management competencies in the metaverse consisted of eight components and four steps. Following the completion of the learning activities, students demonstrated a significant increase in their competencies in virtual learning management, surpassing 70% of the established criteria. The statistical analysis confirmed the significance of this improvement, with a p-value of less than 0.05. This study’s results highlight the effectiveness of the developed CBLAs in enhancing virtual learning management skills among computer teacher students in the metaverse. The findings indicate that students experienced a significant improvement in their competencies after participating in the learning activities. Furthermore, the students expressed the highest levels of satisfaction conducted activities
Effects of Social Media Use on Adolescent Psychological Well-Being: A Systematic Literature Review
Get PDFThis study aims to explore the intricate relationship between social media use and the overall well-being (WB) of young people. Previous research has presented conflicting findings, indicating both positive and negative effects of online platforms. Issues such as excessive use, reduced face-to-face interactions, social isolation, heightened stress levels, and disrupted sleep patterns have been identified as potential concerns. However, studies have also highlighted that moderate and mindful use of social media can enhance WB by facilitating social connections and support. It is crucial to consider the vulnerabilities of young individuals when examining this complex topic and provide them with age-appropriate guidance. This research project aims to address gaps in the existing literature and inform strategies for promoting positive online experiences and safeguarding the WB of young people by investigating the association between social media use and affective WB. The review process involved systematically searching for relevant research and evaluating its quality and relevance. The analysis encompassed 111 articles and reviews published between 2013 and 2023. The dataset comprised articles with an average age of 2.76 years and an average of 40.45 citations per article, sourced from 78 journals and other publications. Several variables were examined, including authors, publishers, affiliations, countries, and keywords used in the research articles. The discourse surrounding the benefits and drawbacks of social media use was found to be ongoing. Concerns were raised regarding the potential negative consequences of excessive use, including diminished face-to-face interactions, social isolation, increased stress levels, and sleep disturbances. However, it was also observed that moderate and mindful social media use could positively impact WB by promoting social support and connection. Given the complex nature of the relationship between social media use and WB, it is important to acknowledge the vulnerabilities of young people and provide appropriate assistance and guidance tailored to their age group
Software Development for Comprehensive Assessment of English Online Teaching Quality in Universities Based on Data Mining
Get PDFIn the context of big data in education, the education industry is combined with information technology to form an online teaching model. In order to analyze the actual effectiveness of online teaching methods, a comprehensive evaluation model of online teaching quality is developed based on data mining. The model is divided into two parts: an improved K-modes algorithm to evaluate English teachers’ “teaching” and a feed-forward neural network to evaluate students’ “learning”. The improved K-modes algorithm cleansed, analyzed, and mined the teaching data, and improved the calculation of cosine similarity to establish a model for evaluating teachers’ teaching status, the neural network model has more excellent index results, where the average error is 0.98, within 1, so the neural network model has a smaller error result. The combined model has a strong feasibility for the comprehensive evaluation of English online teaching quality
The Degree of Practicing Creative Thinking Skills by Basic School Teachers in Emirate of Sharjah from their Point of View
Get PDFThis study aimed at finding out the degree of practicing creative thinking skills by basic school teachers in Emirate of Sharjah, from their point of view. The descriptive – survey methodology was used in the study. The study sample consisted of (50) female teachers of the basic stage. A questionnaire was developed to collect the study data. It consisted of (22) items, distributed on five domains: (fluency, flexibility, sensitivity to problems, taking risk and enriching detail skills). Validity and reliability of the tool were assured. The findings showed that the degree of practicing creative thinking skills by basic female school teachers was high from their point of view. There were no statistically significant differences at (α ≤ 0.05) in the degree of practicing creative thinking skills by the basic female school teachers in Al – Sharjah Emirate attributed to academic qualification and experience variables. Among the recommendations of the study was: Supporting the effectiveness of practicing creative thinking skills of the basic female school teachers in Emirate of Sharjah