Online-Journals.org (International Association of Online Engineering)
Not a member yet
9805 research outputs found
Sort by
The Design of An Adaptive E-learning Model Based on Artificial Intelligence for Enhancing Online Teaching
Get PDFNowadays, teaching involves more and more the usage of digital tools to accompany face-to-face learning. Such a system is being referred to as hybrid teaching. These digital tools include mainly distance learning platforms based on LMS (Learning management systems). LMS help to create on-line digital spaces to store and organize teaching material while providing a pedagogical learning process to connect educational communities. Despite the many forms of content that can be implemented on these platforms, from traditional file-based to interactive and animated content, these systems remain both passive and generic. They lack the ability to adapt to the learner in terms of learning skills, preferences, languages, intellectual abilities, learning patterns and rhythms. This paper proposes a design and modeling of an intelligent and dynamic adaptive learning system based on artificial intelligence with the main objective of identifying and providing personalized learning environments adapted to the learner needs.
 
The Effectiveness of Students’ Use of Computer Modeling in Learning Engineering Mathematics
Get PDFThe aim of this study is to explore the effectiveness of teaching mathematics using computer modeling. It was conducted for a five-grade engineering unit by modeling concepts, terminology, and issues related to engineering in collaboration between groups of students and teachers from several primary schools. in Amman, Jordan, in the academic year 2021/2022. The working group consisted of thirty students. An action research model was used to conduct this study. Photographs, videos, teacher records, graded grading model, focus group discussions, and researcher's record were used to collect data. Through percentage statistics and content analysis, the obtained qualitative data were analyzed. And concluded that the positive impact of students' use of computer modeling in learning aeronautical engineering mathematics and motivating students towards studying mathematics and increasing study skills and the ability to represent and model to clarify any issue in mathematics in space engineering
Analyzing and Tracking Student Educational Program Interests on Social Media with Chatbots Platform and Text Analytics
Get PDFThis research presents a chatbot application to provide educational information for university students. There are three objectives: 1) to study the problem of providing information to university students with chatbots, 2) to develop a model and construct a chatbot to predict the interest of university students, and 3) to assess the satisfaction of the information provided by the chatbot application. The research datasets were the conversations from the Messenger Facebook Page of the Faculty of Information Technology, Rajabhat Maha Sarakham University, during the academic year 2020-2021. In total, there were 1,094 transactions used in this research work. Furthermore, data mining and machine learning techniques, including CRISP-DM, Naïve Bayes, K-Nearest Neighbors, and Neural Network, were used as the research tools. The cross-validation and confusion matrix techniques were used to test the model performance. Moreover, a questionnaire was the application satisfaction assessment tool for 30 respondents. As a result, it showed that the developed model provided high-level results, which are 88.73% accuracy and an average of 3.97 for application satisfaction. In the future, the researchers plan to apply the results for the next academic year and expand into other academic programs
Delay-Oriented Resource Allocation for OFDMA Real-Time Mobile Broadband Services
Get PDFRadio Resource Management (RRM) is the key component that influences the Quality of Service (QoS) in emerging mobile systems. The harsh requirements of recent multimedia applications press on the behavior of the resource allocation model at the Medium Access Control (MAC). This, under certain conditions, deteriorates awareness of the scheduler in satisfying QoS characteristics for the diverse attending traffic flows. The trade-off between QoS metrics may be a viable remedy to this problem. However, if the tradeoff is not meticulously addressed, it definitely increases the delay beyond the allowed threshold and plummets the data rates of the involved flows. In this article, a Delay-oriented Resource Allocation (DoRA) scheduler is proposed for the downlink channel to transmit multimedia applications. The main aim of DoRA is to schedule flows of different volumes with guaranteed low delay values and acceptable throughput under harsh network conditions (i.e., high traffic load and mobility). An efficient priority weight function is formulated based on a delay-oriented rule considering the buffer delay of the diverse flows. Eventually, a greedy algorithm assigns channel resources to the prioritized flows with high weights. DoRA is compared to reference schedulers using system-level simulation over two scenarios. The performance results indicate that DoRA maintains a low end-to-end delay with robust throughput and efficient spectrum efficiency for different flow volumes over congested network states
The Design and Development of Augmented Reality (AR) Application for Internet Evolution Learning Topics
Get PDFEducation field has seen numerous revolutions and innovations that have altered the teaching and learning process through the emergence of Information and Communications Technology (ICT) which provides numerous benefits to both educators and students. However, there is concern that students focus in the classroom becomes less due to the lack of pleasurable during the teaching and learning sessions. Thus, the existence of learning using Augmented Reality (AR) applications seems to help students improve their thinking skills in terms of cognitive as well as behaviourism. Therefore, this study proposed the Design and Development of Augmented Reality (AR) Application for Internet Evolution Learning Topics known as AREvo. The methodology used in this study was based on a design and development research (DDR) and ADDIE Model were used for designed and developed AREvo. Several platforms and software were used to develop AREvo. Several experts in Creative Multimedia field from higher education were appointed to evaluate the AREvo in terms of its functionality, content design, interaction design and presentation. The data analyze and obtained is in the form of frequency and feedback. Result revealed that AREvo application can be used as an additional material for instructors as well as students who are taking basic ICT course. In addition, AREvo is expected to provide a positive impact in terms of functionality and usability of this AR application in the present and also in the future
Machine Learning Based Phishing Attacks Detection Using Multiple Datasets
Get PDFNowadays, individuals and organizations are increasingly targeted by phishing attacks, so an accurate phishing detection system is required. Therefore, many phishing detection techniques have been proposed as well as phishing datasets have been collected. In this paper, three datasets have been used to train and test machine learning classifiers. The datasets have been archived by Phish-Tank and UCI Machine Learning Repository. Furthermore, Information Gain algorithm have been used for features reduction and selection purpose. In addition, six machine learning classifiers have been evaluated, namely NaiveBayes, ANN, DecisionStump, KNN, J48 and RandomForest. However, the classifiers have been trained and tested over the three datasets in two stages. The first stage is using all features included in each dataset while the second stage using selected features by IG algorithm. At the first stage RandomForest classifier has shown the best performance over Dataset-1 and Dataset-2, while J48 has shown the best performance over Dataset-3. On the other hand, after features selection, the RandomForest classifier was the superior among the other five classifiers over Dataset-1 and Dataset-2 with accuracy of 98% and 93.66% respectively. While ANN classifier has shown the best performance with accuracy of 88.92% over Dataset-3. Because of the few number of instances as well as features in Dataset-3 comparing to the other two dataset; the performance of the classifiers has been affected
Augmented Reality for Quechua Language Teaching-Learning: A Systematic Review
Get PDFAs time goes by, it is evident that technology advances, Augmented Reality (AR) is an innovative technological tool that has emerged and has been highly attractive to users, allowing sharing information in a dynamic and realistic way. In the present systematic literature review (SLR), a search was conducted for manuscripts published in 6 databases between the years 2017 to 2022, related to the implementation of AR to improve the teaching-learning (TL) process of the Quechua language, which were analyzed and systematized using the prism methodology, obtaining as a result 56 manuscripts that supported to answer the research questions, where the various factors that allow improving the TL process of the Quechua language and the various benefits generated by its implementation were identified. It is concluded that, according to the results, the application of RA in the TL of the Quechua language is an efficient and productive tool; however, it can also be a source of distraction in the study, so it is necessary to have a good management of this methodology and of the study environment to obtain better achievements. For this reason, a model is proposed to serve as a basis for the proper management in the implementation of RA to improve the process of Quechua language TL
Reliable Fuzzy-Based Multi-Path Routing Protocol Based on Whale Optimization Algorithm to Improve QOS in 5G Networks for IOMT Applications
Get PDFThe Internet of Medical Things (IoMT) faces stiff competition from the 5th Generation (5G) communication standard, which includes attributes like short and long transmission ranges, Device to Device (D2D) connectivity, low latency, and high node density. To function in the linked ecosystem, IoMT based on 5G is anticipated to have a diversity of energy and mobility. It is currently difficult to create an IoMT routing system based on 5G that maximizes energy efficiency, lowers transmission latency, and increases network lifespan. The "Quality of Services (QoS)" in 5G-based IoMT is improved by the Reliable Fuzzy-based Multi-path routing system shown in this study. The Whale Optimization Algorithm (WOA) enhances the routing protocol performance. The residual energy-based Cluster Head (CH) selection strategy rotates the CH location among nodes with greater energy levels than the others. The method chooses the following set of CHs for the network that is suitable for IoMT applications by considering initial energy, residual energy, and an ideal value of CHs. According to the simulation results, our suggested routing technique enhances QoS in comparison to current approaches
VideoDL: Video-Based Digital Learning Framework Using AI Question Generation and Answer Assessment
Get PDFAssessing learners’ understanding and competency in video-based digital learning is time-consuming and very difficult for educators, as it requires the generation of accurate and valid questions from pre-recorded learning videos. This paper demonstrates VideoDL, a video-based learning framework powered by Artificial Intelligence (AI) that supports automatic question generation and answer assessment from videos. VideoDL comprises of various AI algorithms, and an interactive web-based user interface (UI) developed using the principles of human-centred design. Our empirical evaluation using real-world videos from multiple domains demonstrates the effectiveness of VideoDL
What Motivate Students to Continue Using Online Collaborative Tools: Post-Acceptance of Information System Approach
Get PDFThis paper aims to understand what motivates students at universities in Indonesia to continue using Online Collaborative Tools (OCTs) for their collaboration work. Utilising OCTs is crucial as Covid-19 hit us in 2019 and forced all of us, particularly those who studied at university, to work online as precautionary measures. This research employs the Post-Acceptance Model of Information Systems (IS) approach to understand this issue. For an OCT to continue use, performance: effectivity, efficiency, and certainty is the key determinant, and perceived usability: perceived usefulness, perceived ease of use, and perceived enjoyment mediates confirmation and satisfaction and the intention to continue use. A total of 354 participants are involved in the data analysis employing Structural Equation Modelling (SEM). Our results revealed that while the relationship between confirmation and satisfaction is partially mediated by perceived ease of use and enjoyment, the relationship between confirmation and intention to continue use is also partially mediated by perceived usefulness and enjoyment, and satisfaction. We found that the intention to continue using the OCT can be determined by 67.9% (substantial) of the variance of the model. Our research contributes theoretically to the IS research in this context and practically to the OCT discourse. Limitations and future research directions are discussed