Online-Journals.org (International Association of Online Engineering)
Not a member yet
9805 research outputs found
Sort by
A New Pyramid Model of Empathy: The Role of ICTs and Robotics on Empathy
Get PDFEmpathy and compassion have become a major focus for international research and appear to be important concepts in human development. There are several definitions and models of empathy and compassion available in the literature. Based on theoretical foundations, a new model of empathy – compassion - love is proposed in the present article. This new model emphasizes the evolution of the concept of empathy, which, at higher levels, takes the form of compassion, which will then be transformed into even higher universal love making empathy and compassion a creative and significant process for the gradual evolution of individuals. In addition, emphasis is placed on ICT tools that contribute to the development of empathy and compassion
A Convolutional Neural Network Model to Segment Myocardial Infarction from MRI Images
Get PDFCardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively
Analysis of Student Performance Applying Data Mining Techniques in a Virtual Learning Environment
Get PDFStudents' academic performance is a key factor for educational institutions and society, which is an important indicator of the quality of the teaching-learning process and the appropriation of knowledge. Its analysis allows an understanding of the behavior of students and teachers, generating valuable knowledge for making timely academic decisions. In this study, the following phases were carried out: (i) identification of factors that influence the academic performance of engineering university students, (ii) early prediction of academic success, and (iii) identification of use patterns in a virtual learning environment (VLE). The Knowledge Discovery in Databases (KDD) methodology was applied based on predictive and descriptive data mining techniques, using academic and socioeconomic data and interactions (resources and activities) with the VLE. The tools and programming languages used were Pentaho Data Integration for data integration and processing; Jupyter Notebook, Python, and Scikit-Learn for correlation analysis and prediction modeling; and R Studio for the clustering task. The results show that VLE resources such as files, links, and activities such as participation in forums are factors that lead to good academic performance. On the other hand, it was possible to make predictions of academic success (pass or not) with an accuracy greater than 95% and to identify the main patterns of use of the VLE. The group with excellent academic performance (grades 9 to 10) is recognized for using file-type resources and high participation in class and forum activities
Influence of APP-Assisted Teaching on Teaching Quality in Mobile Learning
Get PDFAt present, a large number of education APPs have been developed and widely applied, making mobile learning one of the more popular learning methods under influence of the epidemic. Undeniably, control of college students is indeed an issue that needs to be considered to prevent non-learning behaviors of students in APP learning. Education APPs are more suitable to assist traditional education and to help teachers’ teaching and students’ learning. Based on the theory of fragmented learning and activity learning, a questionnaire on the influence of APP-assisted teaching technology on teaching quality of mobile learning was designed, and mediating effect of team interdependence on the influence of APP-assisted teaching technology on teaching quality of mobile learning was measured. Kruskal-Wallis test was used to measure difference between APP usage quantity and teaching quality. Results show that convenience, individuation and immediacy of APP-assisted teaching technology have significant influence on teaching quality of mobile learning. Team interdependence plays a part in mediating effect of APP-assisted teaching technology on teaching quality of mobile learning. Different APP usage quantity samples all show a significant effect on teaching quality (p<0.05). Conclusions have important reference value for learners to rely on education APPs to carry out fragmented, efficient and personalized learning, to improve education APPs as a teaching method to assist traditional teaching, and to avoid learners falling into “technology-oriented” misunderstanding of over-reliance on APPs for learning
Students’ Attitudes towards Mobile Learning: A Case Study in Higher Education in Vietnam
Get PDFThe use of mobile learning has been investigated in many educational settings to support the effectiveness of mobile devices in teaching and learning. The study aims to explore students’ attitudes towards the use of mobile technology in higher education. To gain insight into students’ attitudes towards it, both quantitative and qualitative methods were employed from a 5-point Likert scale questionnaire and a semi-structured interview with the participation of 118 students in a university. The results showed that students expressed highly positive attitudes towards the use of mobile technology in learning. The easy access to resources and course materials was most beneficial to students accompanied by enhanced communication with peers and instructors to help students achieve better academic scores. Besides, students could develop various skills through mobile learning such as computer skills, analytical skills, and note-taking skills. It is to suggest the implication of using mobile devices to support teaching and learning to improve the quality of education in higher education as a whole
Research Trend of Big Data in Education During the Last 10 Years
Get PDFBig Data research has rapidly developed in the last 10 years, making it an interesting topic to investigate to understand the trends and developments of Big Data in Education. This study aims to analyze source documents and state contributions, and visualize research trends on the subject of Big Data in education during the last 10 years and identify potential research topics related to Big Data in Education in the future. This study uses a literature review and Meta-Analyses (PRISMA) method associated with bibliometric analysis using the Scopus and VOSViewer databases, through which 1,076 documents were obtained. The results of the bibliometric analysis show that Big Data research in education has increased significantly in the last 10 years. However, in the last year, it has decreased, this is the next challenge, and an opportunity for future research. The most common types of documents are conference papers, the source of most documents is conference proceedings, and the country that contributes the most is China. English is the most widely spoken language, and the authors with the highest contribution are Daniel, B. K. Further research related to Big Data can be used and implemented in the business world for Big Data analysis in education. Big Data can also be integrated with Science, technology, engineering, and mathematics (STEM) which can be a further research opportunity that can be applied to education because analyzing Big Data requires STEM learning skills. Thus, this research recommends finding updates in the study of Big Data in education by integrating STEM in education because analyzing Big Data again requires STEM learning expertise. This study has limitations in using only one database, namely Scopus, to obtain research data. Therefore, it is recommended that Big Data in Education research be conducted using other databases besides Scopus to obtain more extensive data
Online Sharing Mechanism of Digital Teaching Resources Considering Knowledge Potential Difference
Get PDFThe rapid development of emerging technologies, such as the Internet, big data, and artificial intelligence, has provided the technical foundation and conditions for digital online education resources. Knowledge potential difference has been ignored in current studies on teaching resource sharing, which cannot effectively meet the specific learning needs of students with different cognitive levels, and reduces their participation. Therefore, this paper studied the online sharing mechanism of digital teaching resources considering knowledge potential difference. This paper conducted and analyzed an online sharing model of learning resources between teachers and students considering knowledge potential difference, and described in detail the assumptions and steps for constructing the model. Then this paper constructed an effectiveness evaluation index system for the online sharing mechanism of digital teaching resources considering knowledge potential difference, and elaborated the specific steps for evaluating the effectiveness of the mechanism based on extension evaluation method. Experiment results verified the effectiveness of the proposed modeling and evaluation method
Practical Knowledge Level Characteristics and Innovative Practice Achievement Transformation Mechanism of Vocational College Students
Get PDFCultivating talents with innovation ability is both the goal of higher vocational colleges and their responsibility given by the era. Focusing on improving the practical knowledge level of students means that students should be exposed to nature, society and problems through practical activities, thus providing the maximum space for them to think, explore, discover and innovate. As for existing studies on cultivating innovative ability of students and improving their practical knowledge level, they mainly have focused on ability evaluation and analysis of influencing factors, and few of them has involved analysis of their practical knowledge level characteristics. Therefore, this paper studied the characteristics and transformation mechanism of their innovative practice achievements. A multi-level comprehensive evaluation system was constructed, which aimed to evaluate the practical knowledge level of those students. The input dimension of quantized data of indexes was reduced in accordance with the principal component analysis (PCA). Then the quantized data of the low-dimensional indexes were mined by hierarchical clustering, and different training subsets were generated to participate in the evaluation model training. Based on the idea of clustering-prediction-integration, Gated Recurrent Unit (GRU) model was used for nonlinear integration of the output results of two-way Long Short-Term Memory (LSTM) model, which further fit the nonlinear characteristics in the quantized data of all indexes. By introducing Bootstrap-Data Envelopment Analysis (DEA) method, the transformation rate of innovative practice achievements of the students was collected and calculated in order to obtain a small calculation error. Experimental results verified the effectiveness of the proposed calculation method of the model
Preliminary Emotional User Experience Model for Mobile Augmented Reality Application Design: A Kansei Engineering Approach
Get PDFThe user experience, often known as UX, is the key factor in determining a product success and increase user’s acquisition. However, this field of research lacks conceptual and practical models to follow when designing pervasive technologies such as mobile augmented reality (MAR). To convey a pleasant UX, it is necessary to identify the contributing factor and the components that influence the enhancement of the MAR design. The findings of the study indicated that emotions are the main factor that drives the user’s perception and hence, their choice and pleasure. This paper presents a preliminary model for designing an emotional UX mobile augmented reality application with the use of Kansei engineering approach. Ultimately, this model will provide insight into the design fundamentals that influence the user experiences. The outcomes of this study will assist researchers and designers in shaping the emotional user experience design
Digital Passion Projects for Online Education in Emergencies
Get PDFThe research studied the effectiveness of the digital passion project activity for developing oral presentation skills of undergraduate students learning English as a foreign language in online education in emergencies. Considering the basic intervention principles suggested by psychologists for students affected by disasters and mass violence circumstances, the researchers conducted a quasi-experiment exploiting the recognized potential of the passion project to build a positive emotional environment and encourage more efficient learning. The findings revealed that experimental group students outperformed control group students in the four out of five aspects of the rubric applied (content, coherence and cohesion, vocabulary richness and adequacy, and grammatical correctness). The results can be attributed to the observed increased creativity, inquisitiveness, engagement in learning, and self-efficacy as well as to the project marketplace method applied at the initial stage. The passionate involvement in the project was proved by the survey administered to check student’s level of passion during the work on the passion project