Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
Evaluating the quality of proposed agile XScrum model
Статья научная
The software companies are practicing XP and Scrum models from last several years. XP lacks in management practices whereas Scrum is weak in engineering practices. Due to continually promising need of agile development, this research tackles the problems of XP and Scrum by integrating them to enrich the strengths of XP and Scrum and suppress their limitations. The previous attempts provide little effective empirical evidence regarding the integration of XP and Scrum. Therefore, there is a pressing need to provide empirical evidence for the integration of XP and Scrum to show its usefulness developing the software projects. The same is accomplished by proposing XScrum model. Another goal of this paper is to analyze the quality of proposed XScrum with existing XP and Scrum. The proposed XScrum is validated by performing three case studies for three industrial projects and the results are described in the paper. The results are presented using quantitative and qualitative data. The results provide empirical evidence that there is a significant improvement in quality of proposed XScrum as compared to the existing XP and Scrum.
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Evaluating the use of Toondoo for collaborative e-learning of selected pre-service teachers
Статья научная
With the growing reliance on information technology, new trends were marshaled in the field of education to produce graduates endowed with 21st century skills. It is unequivocal that collaborative e-learning encourages teachers to innovate for the enhancement of students' learning. In furtherance of the ongoing teaching-learning upgrades, this study aimed to evaluate the use of Toondoo as a tool for collaborative e-learning to selected education students. Specifically, this study determined the extent to which Toondoo has promoted students' collaborative e-learning, and identified the influence of Toondoo to students' learning. Using descriptive-correlation design, results showed that students exhibit positive attitudes on the use of Toondoo. Results further revealed that Toondoo has significantly influenced students' performance, albeit they differ according to their attitudes toward the employment of Toondoo.
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Evaluation Framework for Disabled Students based on Speech Recognition Technology
Статья научная
This paper intends to develop an evaluation framework for the students with disabilities based on speech recognition technology. Education is the most significant ingredient in the development and empowerment of individuals. Till the last decade, education was provided to the persons with disabilities in segregated school settings or “special schools”. But in the recent years, there has been a great shift in societal attitude towards disabled students globally. The calls for “integration” of all students, disabled students and non–disabled students into the mainstream classroom environments have gathered momentum worldwide. In the pre–existing frameworks, the disabled students faced great difficulty while interacting with the system. The prime objective of our proposed framework is to provide a user–friendly and interactive environment that gives equal opportunities to all the students being evaluated. The utilization of speech recognition technology would lead to the elimination of all misinterpretations arising due to the human scribe or mediator and would enhance the ability of the disabled students to keep pace with the other students.
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Evaluation of Data Mining Techniques for Predicting Student’s Performance
Статья научная
This paper highlights important issues of higher education system such as predicting student’s academic performance. This is trivial to study predominantly from the point of view of the institutional administration, management, different stakeholder, faculty, students as well as parents. For making analysis on the student data we selected algorithms like Decision Tree, Naive Bayes, Random Forest, PART and Bayes Network with three most important techniques such as 10-fold cross-validation, percentage split (74%) and training set. After performing analysis on different metrics (Time to build Classifier, Mean Absolute Error, Root Mean Squared Error, Relative Absolute Error, Root Relative Squared Error, Precision, Recall, F-Measure, ROC Area) by different data mining algorithm, we are able to find which algorithm is performing better than other on the student dataset in hand, so that we are able to make a guideline for future improvement in student performance in education. According to analysis of student dataset we found that Random Forest algorithm gave the best result as compared to another algorithm with Recall value approximately equal to one. The analysis of different data mini g algorithm gave an in-depth awareness about how these algorithms predict student the performance of different student and enhance their skill.
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Evaluation of Ensemble Classifiers for Handwriting Recognition
Статья научная
One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed for homogeneous ensemble classifiers using bagging and heterogeneous ensemble classifiers using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of recognizing totally unconstrained handwritten numerals. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase and combining phase. A wide range of comparative experiments are conducted for real and benchmark data sets of recognizing totally unconstrained handwritten numerals. The accuracy of base classifiers is compared with homogeneous and heterogeneous models for data mining problem. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and also heterogeneous models exhibit better results than homogeneous models for real and benchmark data sets of recognizing totally unconstrained handwritten numerals.
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Evaluation of Information Retrieval Based Ontology Development Editors for Semantic Web
Статья научная
Ontology is one of the central area in natural language processing (NLP), artificial intelligence (AI) information retrieval (IR) and semantic web (SW). If you are working on ontology project, this paper will give you the relevant information about ontology related terms and best ontology development editor. In this paper five ontology development editors are reviewed and compared with their updated versions. They are Apollo1.0, SWOOP 2.3Beta4, Protégé 5.0, Graffoo 1.0 and Neon 2.5.2. Comparison of two main data models ontology and RDBMS is also done. This paper also present the classification of ontology languages from those reported in the Literature, with a special attention accorded to the interoperability between them. Additionally, this paper presents the important terms related to ontology. The main criterion for comparison of these tools and languages was the user interest and their application in different kind of real world tasks. The primary goal of this study is to introduce these important tools, languages and data models to ensure more understanding from their use.
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Evaluation of Performance on Open MP Parallel Platform based on Problem Size
Статья научная
This paper evaluates the performance of matrix multiplication algorithm on dual core 2.0 GHz processor with two threads. A novel methodology was designed to implement this algorithm on Open MP platform by selecting time of execution, speed up and efficiency as performance parameters. Based on the experimental analysis, it was found that a good performance can be achieved by executing the problem in parallel rather than sequential after a certain problem size.
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Evaluation of Tennis Teaching Effect Using Optimized DL Model with Cloud Computing System
Статья научная
Evidence from psychology and behaviour therapy shows that engaging in sports activities at home might help alleviate stress and depression during COVID-19 lockdown periods. A clever virtual coach that provides table tennis instruction at a low cost without invading privacy might be a great way to maintain a healthy lifestyle without leaving the house. In this article, we look at creating the second main constituent of the virtual-coach table tennis shadow-play training scheme: an evaluation system for the effectiveness of the forehand stroke. This research was carried out to demonstrate the efficacy of the suggested bidirectional long-short-term memory (BLSTM) model in assessing the table tennis forehand shadow-play sensory data supplied by the authors in comparison with LSTM time-series investigation approaches. Information was collected by tracking the rackets of 16 players as they performed forehand strokes and assigning assessment ratings to each stroke based on the input of three instructors. The scientists looked at how the hyperparameter values, which are chosen via an optimisation approach, affected the behaviour of DL models. The adaptive learning differential approach has been introduced to enhance the functionality of the standard dragonfly algorithm. Optimal BLSTM settings are selected with the help of the enhanced dragonfly algorithm (IDFOA). The experimental findings of this study indicate that the BLSTM-IDFOA is the most effective regression approach currently available.
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Evaluation of the Cost Estimation Models: Case Study of Task Manager Application
Статья научная
The need to accurately estimate time and cost for effective planning of software projects is becoming crucial driven by the escalating demands of the software market. Several models proposed in the history of Software Engineering discipline to estimate time, costs associated with planning and managing software projects as Line of Code (LOC), Function Point (FP) and Constructive Cost Model (COCOMO). This paper focuses upon the COCOMO Model. It is further consisted of its two sub models called COCOMO I and COCOMO II. The primary objective of this research is to use an appropriate case study to evaluate the accuracy of the sub models COCOMO I and II and ascertain the variation of the realistic resource effort, staff and time. The findings to date show that the Application Composition Model of COCOMO II is more accurate in determining time and cost for the successful conclusion of a software project than the other two COCOMO I and II Models for a similar application for example Task Manager.
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Evaluation: The New Philosophical Roles & Psychological Means
Статья научная
Evaluation Roles and Means are very broad. It concerns with n number of attributes. This paper discussed the relationship between evaluation & research, philosophy of evaluation, physiology of evaluation, Evaluation in applied psychology. In the above context, how the basic logic of evaluation is set with evaluation fields and the phases of evaluation process.
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Evolution and Future Generation of TV
Статья научная
No other electronic media has created as much mass impact as the TV. TV is both a personal as well as family/community device which makes it reach a large population. Obviously the immense popularity of TV has resulted in an unprecedented growth of TV viewing as well as technology. From the simple TV today one can have a smart TV with varying features satisfying all sections of society. The TV technology has grown in all aspects namely the TV studio technology, the TV transmitter & broadcast technology and the TV receiving device technology. Not only have the TV signals been converted from analog to digital, today one has high definition TV, the IPTV, the mobile TV and the 3D TV commercially available. It is very interesting and important to trace the evolution of TV technology from its basic form as in 1930s to date and to visualize their technical features at various stages of developments. This paper gives an overview of the developments in TV technology highlighting their important features.
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Examining Chen and Starosta's Model of Intercultural Sensitivity in the Taiwanese Cultural Context
Статья научная
The main purpose of this study was to empirically examine Chen and Starosta's Model of Intercultural Sensitivity and reproduce a valid scale in the Taiwanese cultural context, using both exploratory and confirmatory factor analyses. Results indicated that Chen and Starosta's five-factor model of intercultural sensitivity (IS) did not fit the Taiwanese cultural context. Instead, a four-factor model of IS was created using an exploratory factor analysis. The four factors were based on the 13 items of 24-item Intercultural Sensitivity Scale (ISS) formulated by Chen and Starosta. The reliability coefficient was .801, demonstrating high internal consistency. A confirmatory factor analysis was performed again to determine the construct validity of the alternative model of IS. Since cultural differences may influence the factor structure of a test, using both EFA and CFA can methodologically provide a meaningful explanation for replication studies. This study proposes an alternative model of the Intercultural Sensitivity Scale that is a better fit with Taiwanese culture by reinterpreting Chen and Starosta's ISS.
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Examining Mindfulness in Education
Статья научная
Despite the availability of numerous learning opportunities ranging from face-to-face to computer-based learning, there is need for better understanding of how to support the development of cognitive skills in students. Research has shown that cultivation of mindfulness skills help to develop cognitive skills such as retention, thinking, problem solving, and emotional balance. However, there is only limited research on the effect of mindfulness training in educational settings. We examined cognitive abilities of university students as identified in Bloom's taxonomy and mindfulness skills during a single traditional face-to-face class room session. We hypothesized that mindfulness is a specific cognitive ability that supports the development of other cognitive skills. This pilot study included 148 students from undergraduate and postgraduate programs at two universities in Sri Lanka. The study assessed cognitive abilities, including retention, thinking, out-of-the-box thinking, note-taking and mindfulness at the end of a one-hour lecture. The results showed that students' self-reported mindfulness following a lecture was significantly lower than other cognitive abilities. These results suggest conducting a more formal controlled experiment to investigate the effect of mindfulness training in education.
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Статья научная
Indigenous Knowledge (IK), can be preserved using Information Systems in order to protect cultural heritage and disseminate local knowledge for development. This knowledge often passed on orally for generations has become significant in searching for answers to several world's critical problems, are at risk of becoming extinct. This "traditional wisdom" is highly useful in solving complex problems of health, agriculture, education, use of natural resources and the environment. The main challenges of IK are inadequate documentation and diminishing transmission channels. Both descriptive and quantitative methods are used in this study that focuses on highlighting the importance of indigenous knowledge in the sustainable development process and illustrating ways in which technology can be used to preserve it, thereby enriching the development process from a holistic perspective. This research strengthens the preservation of local IK, enhances its adoption in the formal educational settings, leads to improvement in scientific knowledge development and inspire sustainable community development using a holistic approach.
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Experiences from Video Lectures in Software Engineering Education
Статья научная
Millennials have learned to seek information from the Internet whenever they need to know something and want to learn things. In this study, we present observations from several university courses with freely available online resources for the modern students. Ten different courses with video lectures were observed, often with positive outcomes and improved results compared to the previous course arrangements. Additionally, unlike in some previous literature, we observed that some issues such as the video length did not have a meaningful impact on the learning outcomes. Overall, the results indicate that videos offer excellent benefit-effort-ratio, and are an efficient way to reach the target audience: the students.
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Experimental Analysis of SPF Based Secure Web Application
Статья научная
In this paper we will propose model driven software development and Security Performance Framework (SPF) Model to maintain the balance between security and performance for web applications. We propose that all security in a Trusted Operating System is not necessary. Some non-essential security checks can be skipped to increase system performance. These non essential security checks can be identified in any web application. For implementation of this Security Performance framework based trusted operating system, we propose object oriented based Code generation through forward engineering. This involves generating source code of web application from one or more Object oriented Rational Rose model. The novel integration of security engineering with model-driven software expansion approach has varied advantages. To maintain security in various applications like Ecommerce, Banking, Marketplace services, Advertising, Auctions, Comparison shopping, Mobile commerce Payment, Ticketing, Online insurance policy management, we have to use high secured operating systems. In this regard a number of trusted operating systems like Argus, Trusted Solaris, and Virtual Vault have been developed by various companies to handle the increasing need of security. Due to high security reason these operating systems are being used in defense. But still these secure operating systems have limited scope in commercial sector due to lower performance; actually this security will come at a cost. This paper analyzes UML-based software development solutions for SPF to manage the security, performance and modeling for web applications.
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Explainable Fake News Detection Based on BERT and SHAP Applied to COVID-19
Статья научная
Fake news detection has become a significant research top in natural language processing. Since the outbreak of the covid-19 epidemic, a large amount of fake news about covid-19 has spread on social media, making the detection of fake news a challenging task. Applying deep learning models may improve predictions. However, their lack of explainability poses a challenge to their widespread adoption and use in practical applications. This work aims to design a deep learning framework for accurate and explainable prediction of covid-19 fake news. First, we choose BiLSTM as the base model and improve the classification performance of the BiLSTM model by incorporating BERT-based distillation. Then, a post-hoc interpretation method SHAP is used to explain the classification results of the model to improve the transparency of the model and increase people's confidence in the practical application. Finally, utilizing visual interpretation methods, such as significance plots, to analyze specific sample classification results for gaining insights into the key terms that influence the model’s decisions. Ablation experiments demonstrated the reliability of the explainable method.
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Статья научная
A group of researchers and developers from Colombia and Mexico have recognised that the development of state-of-the-art Extended Reality software, a key technology for the Metaverse, has great potential to improve teaching-learning processes in educational institutions. However, the development process does not take into account accessibility, universal design and inclusion, especially for the deaf student community. An extended reality model is proposed for the creation of this type of software as a tool to support access to knowledge, based on information gathering, requirements analysis, user-centred design and video game programming, including the ludic and didactic. The aim is to minimise the barriers that limit the learning of programming logic by students with hearing disabilities through the use of new technologies, creating spaces in virtual worlds that are understandable, usable and practical in conditions of safety, comfort and as much autonomy as possible. To validate the model, a mixed reality software prototype was designed and programmed to train students in programming logic, both deaf and hearing. User and heuristic tests were carried out, showing how immersion can improve knowledge acquisition processes and develop skills in higher education students.
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Extending the SOLO Model for Software-Based Projects
Статья научная
In the process of assessing learning outcomes, educators use constructive tools for evaluating students' understanding and performance. In the present study MIS students were engaged in a full life cycle project as part of a Software Analysis and Design workshop. For evaluating their performance, we used the SOLO (Structure of the Observed Learning Outcomes) taxonomy. However during the various stages of the workshop we encountered some inherent limitations of the taxonomy that led us to the understanding that the SOLO taxonomy should be enhanced. This paper elaborates on these missing but required enhancements.
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Extractive Text Summarization Using Modified Weighing and Sentence Symmetric Feature Methods
Статья научная
Text Summarization is a process that converts the original text into summarized form without changing the meaning of its contents. It finds its usefulness in many areas when the time to go through a large content is limited. This paper presents a comparative evaluation of statistical methods in extractive text summarization. Top score method is taken to be the bench mark for evaluation. Modified weighing method and modified sentence symmetric feature method are implemented with additional characteristic features to achieve a better performance than the benchmark method. Thematic weight and emphasize weights are added to conventional weighing method and the process of weight updation in sentence symmetric method is also modified in this paper. After evaluating these three methods using the standard measures, modified weighing method is identified as the best method with 80% efficiency.
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