International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1096
Статья научная
In this paper, we prove two common fixed point theorems. In first theorem, we prove common fixed point theorem for two weakly compatible self maps of type (A) satisfying an integral type contractive condition in intuitionistic fuzzy metric space. In the second theorem, we prove common fixed point theorem for two weakly compatible maps satisfying an integral type contractive condition in intuitionistic fuzzy metric space. These results are proved without exploiting the notion of continuity and without imposing any condition of t-norm and t-conorm.
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Статья научная
The article is devoted to the question of communicative competence formation, represented in all spheres of professional application in higher education and states that the degree of its formation depends on a person's approach to behave in different social situations. This study examines the essence and structure of communicative competence, as well as the system of its formation while teaching a foreign language to higher education students of economics. Evaluation of the characteristics of developing communicative competence when working with economic texts is carried out as the main communicative unit on the example of the use of specific material in speech. The methodology of the formation of communicative competence among future economists is theoretically determined and experimentally tested through interaction with economic texts in English for professional purposes (49 students aged 17–20 years participated in the research). Analysis of linguistic, psychological, psycholinguistic and methodological bases of communicative competence formation, questionnaires of students and survey results gave grounds for the development of experimental methods of these competences formation by future economists in the process of studying modern foreign language. The interactive methods of learning from economic texts were developed under a new concept of teaching foreign language for the formation of communicative competence and introduced in experimental groups of learners. The data indicated a significant increase in intermediate and high levels of future economists’ communicative competences formation in groups with interactive classes.
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Communicative Tasks as a Means of Developing the Emotional Intelligence of Students
Статья научная
Emotional intelligence (EI), the ability to manage emotions, empathize, and regulate one's behavior, is essential for every member of society nowadays. Various social institutions, including these at the educational institutions, influence its development. The paper examines the relationship between solving communicative tasks and developing students' emotional intelligence and describes the features of students' native language training. Here, we are providing examples of analytical, associative, and research communicative tasks. The tasks involve communicative activities, emotional and sensory perception of the text, and the involvement of analytical and creative abilities. A pedagogical experiment was conducted to confirm the development of EI in the process of solving communicative tasks. Hall's methodology determined the level of EI formation. The total number of respondents was 156 (control group – 77 people, experimental group – 79 people). Three control surveys were conducted in March (at the beginning of the experiment), June (in the middle of the experiment), and December (at the end of the experiment) of 2022 to track changes in the development of EI. The empirical results were subjected to statistical analysis. Pearson's criterion confirmed the normality of the distributions, and Student's criterion showed the statistical significance of changes at the end of the experiment for all indicators and for the indicators "emotional awareness," "managing one's emotions," and "empathy" in the middle of the experiment. The study confirmed a new method of developing EI - the use of communicative tasks in teaching the native language, which extends the existing research results on the development of EI in learning foreign languages. The study lays grounds for several conclusions, including that solving communicative tasks may model "life situations" and indirectly form models of the future behavior of young people. It also identifies an urgent need for special courses for teachers on developing skills to create communicative tasks; it is essential to modernize teacher training programs, which should include the development of skills to model situational emotionally colored tasks that do not have an unambiguous answer and require analysis, comparisons, and evaluations.
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Статья научная
Compression is a way to compress data to produce a file with a size smaller than its original size. Compression techniques can be performed on text data or binary, image (JPEG, PNG, ....), Audio (MP3, AAC, RMA, WMA, ... ..) and video (MPEG, H261, H263, ....). Compression Data is a way to process information using bits or other information units lower than the representation of data that is not encoded with a particular encoding system. Data compression has a function to condense, shrink data to its size becomes smaller. With the smaller size of storage space required then less to make it a more efficient storing process, but it also can shorten the time of the data exchange. Data compression using the run-length encoding (RLE) is a technique used to compress the data contains recurring characters. Run-length encoding (RLE) is a very simple form of data. In RLE running data (sequence data value is the same with many of the data elements in a row) is stored as the value of a single data and calculated the length of the data. This method is useful for data that contains a lot of data, such as simple graphic images (icons, line drawings, and animation). Data compression can be realized in various ways. Data compression can be designed using the VHDL language and can also use a microcontroller. Every realization of data compression has different performances. In this research, the performance was analyzed at the speed of compression. From the experiments conducted, the results of compression speed using VHDL implementation are 6.95 KB / s and microcontroller implementation is 5.34 KB/s. Based on the experimental results from the implementation of data compression using VHDL proposed in this study has a speed of 30.11% better.
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Comparative Studies of Self-organizing Algorithms for Forecasting Economic Parameters
Статья научная
This manuscript presents the economic research results based on their input-output characteristics and functional description with inductive modeling methods and tools. There are a wide plethora of methods to be used for solving this type of problem, including various neural network models, linear and nonlinear regressions, reference vectors’ methods, fuzzy models, etc. The main disadvantage of these methods is that the obtained models cannot always interpret and obtain a model of optimal complexity. Unlike the mentioned methods and tools, the group method of data handling (GMDH) allows building models directly from a data sample without the attraction of additional a priori information. This algorithm admits finding internal dependencies in the data and determining optimal model complexity. There is a broad range of iterative GMDH algorithms that have been developed and studied. Oversampling algorithms are applicable for solving the structural identification problems for a limited number of arguments. Iteration algorithms are suitable for solving tasks with many arguments, but they do not guarantee proper structure development. Multi-row GMDH iteration algorithms are the most popular ones. However, they have several sufficient defects, such as informative argument loss or non-informative argument inclusion, as well as a polynomial degree of exponential growth. In this context, the applicability of the GMDH-based iterative and combined architectures for solving the model's interrelation problems between a volume of capital investments and GDP by activity types in the transport branch is considered. The determination coefficient is utilized for the estimation of the obtained models based on a complicated evaluation procedure. The Kolmogorov-Smirnov criterion estimates the model’s adequacy. The F-criterion Fisher assesses the significance of polynomial models. The demonstrated results proved that the combined iterative and combinatorial algorithms turned out to be the most effective solution for all evaluation criteria.
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Comparative Study of High Speed Back- Propagation Learning Algorithms
Статья научная
Back propagation is one of the well known training algorithms for multilayer perceptron. However the rate of convergence in back propagation learning tends to be relatively slow, which in turn makes it computationally excruciating. Over the last years many modifications have been proposed to improve the efficiency and convergence speed of the back propagation algorithm. The main emphasis of this paper is on investigating the performance of improved versions of back propagation algorithm in training the neural network. All of them are assessed on different training sets and a comparative analysis is made. Results of computer simulations with standard benchmark problems such as XOR, 3 BIT PARITY, MODIFIED XOR and IRIS are presented. The training performance of these algorithms is evaluated in terms of percentage of accuracy, and convergence speed.
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Comparative Study of Supervised Algorithms for Prediction of Students’ Performance
Статья научная
Predicting academic performance of the student is crucial task as it depends on various factors. To perform such predictions the machine learning and data mining algorithms are useful. This paper presents investigation of application of C5.0, J48, CART, Naïve Bayes (NB), K-Nearest Neighbour (KNN), Random Forest and Support Vector Machine for prediction of students’ performance. Three datasets from school level, college level and e-learning platform with varying input parameters are considered for comparison between C5.0, NB, J48, Multilayer Perceptron (MLP), PART, Random Forest, BayesNet, and Artificial Neural Network (ANN). Paper presents comparative results of C5.0, J48, CART, NB, KNN, Random forest and SVM on changing tuning parameters. The performance of these techniques is tested on three different datasets. Results show that the performances of Random forest and C5.0 are better than J48, CART, NB, KNN, and SVM.
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Comparative analysis of stemming algorithms for web text mining
Статья научная
As the massive data is increasing exponentially on web and information retrieval systems and the data retrieval has now become challenging. Stemming is used to produce meaningful terms by stemming characters which finally result in accurate and most relevant results. The core purpose of stemming algorithm is to get useful terms and to reduce grammatical forms in morphological structure of some language. This paper describes the different types of stemming algorithms which work differently in different types of corpus and explains the comparative study of stemming algorithms on the basis of stem production, efficiency and effectiveness in information retrieval systems.
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Статья научная
Though University enrolment in Nigeria is on the increase, more males than females are still being enrolled today, which varies according to discipline as well as from one geopolitical zone of the country to another. This is more pronounced in Science, Technology, Engineering and Mathematics fields, as female enrolment seems to be higher in the commercial and arts courses than the sciences and engineering. Secondary data were obtained from the Nigerian Bureau of Statistics, based on the Joint Admission and Matriculation Board registrations for a period of 5 years, spanning 2011 to 2015. The data were classified based on the six geopolitical zones in Nigeria, and multivariate data analysis, supported by Multivariate Analysis of Variance was carried out on the data. The results obtained revealed that there is still a wide variance in male and female enrolment in these fields, with male enrolment being significantly higher than that of female candidates. It also revealed that female enrolment varies depending on the geopolitical zone, with female enrolment in Science, Technology, Engineering and Mathematics being generally higher in geographical zones in southern Nigeria compared with those in northern Nigeria. The results obtained were further compared with data obtained from previous researches and the comparison was discussed. In addition, this study offers recommendations on how to encourage more female participation in Science, Technology, Engineering, and Mathematics.
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Comparative study of inspired algorithms for trajectory-following control in mobile robot
Статья научная
This paper is devoted to the design of a trajectory-following control for a differentiation nonholonomic wheeled mobile robot. It suggests a kinematic nonlinear controller steer a National Instrument mobile robot. The suggested trajectory-following control structure includes two parts; the first part is a nonlinear feedback acceleration control equation based on back-stepping control that controls the mobile robot to follow the predetermined suitable path; the second part is an optimization algorithm, that is performed depending on the Crossoved Firefly algorithm (CFA) to tune the parameters of the controller to obtain the optimum trajectory. The simulation is achieved based on MATLAB R2017b and the results present that the kinematic nonlinear controller with CFA is more effective and robust than the original firefly learning algorithm; this is shown by the minimized tracking-following error to equal or less than (0.8 cm) and getting smoothness of the linear velocity less than (0.1 m/sec), and all trajectory- following results with predetermined suitable are taken into account. Stability analysis of the suggested controller is proven using the Lyapunov method.
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Статья научная
Dynamics of Malaria parasite diagnosis is complex and been widely studied. Research is on-going on the effects of climatic variations on symptomatic malaria infection. Malaria diagnosis can be asymptomatically or symptomatically low, mild and high. An analytical program is needed to detect individual malaria parasite counts from complex network of several infection counts. This study adopted the experimental malaria parasite counts collected from selected hospitals in Minna Metropolis, Niger State, Nigeria and Climatic data collected at the time the experiment was conducted from NECOP, Bosso, FUT Minna, Niger State, Nigeria. One thousand and two hundred (1,200) experimental data were collected and two classifiers Support Vector Machine (SVM), Artificial Neural Network (ANN) do the prediction. Experimental results indicated that SVM produced Accuracy 85.60%, Sensitivity 84.06%, Specificity 86.49%, False Positive Rate(FPr) 0.1351% and False Negative Rate(FNr) 0.1594% than Neural Network model of Accuracy 48.33%, Sensitivity 60.61%, Specificity 45.48%, low False Positive Rate (FPr) 0.5442% and False Negative Rate(FNr) 0.3939% as depicted in their respective confusion matrix.
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Comparing Elementary Students' Programming Success based on Programming Environment
Статья научная
In the Republic of Croatia Informatics is an elective course in elementary school for students from 5th to 8th grade. When it comes to programming language teachers can choose between BASIC and Logo. There are a lot of new programming environments for learning and teaching programming like Scratch and also new ways of teaching programming like game based learning. This study compares attitudinal and learning outcomes of 7th-grade students programming in Logo and Scratch. The classes were normal classes, non-extracurricular activities. The questionnaire is used to measure the attitude towards programming and programming languages. The test is constructed to measure learned programming concepts in both compared programming languages Logo and Scratch. Results showed that learning Scratch first can provide a better understanding of basic programming concept for novices in elementary school than Logo.
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Статья научная
This study aimed to compare 5th graders' scores obtained from Scratch projects developed in the framework of Information Technologies and Software classes via Dr Scratch web tool with the scores obtained from Computational Thinking Levels Scale and to examine this comparison in terms of different variables. Correlational research model was utilized in the study that 31 students participated in. Students were taught basic programming by using Scratch during a 6-week period. At the end of training, students' programming skills were measured via Dr. Scratch web tool. Computational thinking skills were measured using Computational Thinking Levels Scale which includes 5 factors: creativity, problem solving, algorithmic thinking, collaboration and critical thinking. Data were analyzed for internal reliability to calculate scale reliability. Cronbach Alpha reliability coefficient was found to be 0.809. It was found that scores obtained by students by using any of the measurement tools did not differ according to gender or period of computer use, however, a high level significant relationship was observed between students' programming skills with Scratch and their computational thinking skills.
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Статья научная
This article discusses the findings of a study that elucidated users’ acceptance of two management systems for key performance indicators (KPIs) in terms of their usefulness and ease of use scores at a higher education institution in Malaysia. The two management systems were Key Performance Indicators Monitoring System (KPI-MS) and Excel Spreadsheet System (ESS). ESS is a system developed using Microsoft Excel and has been in used since the year 2008 in the institution to calculate KPIs marks. The ESS system, however, has several shortcomings, and the KPI-MS system was developed with the intention to replace ESS. KPI-MS is an online KPI performance monitoring system which allows users to access the system wherever and whenever they want using a web browser. In addition, KPI-MS is designed as an intelligent system that is able to process raw data automatically to produce results that can be easily visualized in a graphical manner. A survey questionnaire was used to collect data on the acceptance of both systems. A total of 78 participants who were involved in KPI data processing from all 42 schools and centres in the higher education institution in Malaysia participated in this study. The instrument of this study was adapted and modified from Davis’ Technology Acceptance Model (TAM). This instrument was content-validated by three experts in the related field and the reliability index computed with Cronbach alpha was 0.955. A descriptive analysis was conducted to compare the mean scores of both KPI-MS and ESS rated by the users. The results showed that the users rated KPI-MS as a very useful system in monitoring KPI performance of their schools or centres compared to ESS. Also, users rated the KPI-MS to be significantly easier (p≤0.01) and more enjoyable to use. In conclusion, it is recommended that KPI-MS should replace the ESS system in managing KPIs data.
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Comparison Analysis of AHP-SAW, AHP-WP, AHP-TOPSIS Methods in Private Tutor Selection
Статья научная
Private tutoring was a non-formal education, it was used as an alternative by parents to help support and maximize the learning process that students get at school. Sometimes parents have difficulty in adjusting the desired and needed criteria with available alternatives or teachers. To overcome these obstacles, this research used the MADM approach in providing alternative recommendations, based on the criteria used as the basis for decision making. MADM consists of SAW, WP, TOPSIS, and AHP. The advantages of the SAW, WP, and TOPSIS methods in managing cost and benefit data were used in the ranking process. While the weaknesses of the three methods in the weighting process can be overcome by the AHP method, which was able to provide more objective weighting results. Therefore, this research aimed to analyze the comparison of the combination of AHP-SAW, AHP-WP, and AHP-TOPSIS methods in the selection of private tutors. The combination of these methods was compared based on accuracy, ranking, and preference to get the best combination of MADM methods in determining the selection of private tutors. The criteria used in this research were education, experience, cost, duration, rating, and distance. The comparison of the three combinations of methods showed the AHP-SAW method has an accuracy rate of 88.14%, AHP-WP of 68.64%, and AHP-TOPSIS of 66.95%. The average ranking showed the AHP-SAW method gave results of 91%, AHP-WP of 88%, and AHP-TOPSIS of 89%. In addition, the average preference showed the AHP-SAW method gave a value of 0.771, AHP-WP of 0.073, and AHP-TOPSIS of 0.564. Thus, it showed the AHP-SAW gave better results in the case of private tutor selection than the AHP-WP and AHP-TOPSIS.
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Comparison and Evaluation of Intelligence Methods for Distance Education Platform
Статья научная
In this paper two favorite artificial intelligence methods: ANN and SVM are proposed as a means to achieve accurate question level diagnosis, intelligent question classification and updates of the question model in intelligent learning environments such as E-Learning or distance education platforms. This paper reports the investigation of the effectiveness and performances of two favorite artificial intelligence methods: ANN and SVM within a web-based environment (E-Learning) in the testing part of an undergraduate course that is "History of Human Civilizations" to observe their question classification abilities depending on the item responses of students, item difficulties of questions and question levels that are determined by putting the item difficulties to Gaussian Normal Curve. The effective nesses of ANN and SVM methods were evaluated by comparing the performances and class correct nesses of the sample questions using the same 3 inputs as: item responses, item difficulties, question levels to 5018 rows of data that are the item responses of students in a test composed of 13 questions. The comparative test performance analysis conducted using the classification correctness revealed yielded better performances than the Artificial Neural Network (ANN) and Support Vector Machine (SVM).
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Comparison of ANFIS with MLP ANN in Measuring the Reliability based on Aspect Oriented Software
Статья научная
In fact, Reliability as the qualities metric is the probability success or The probability that a system or set of tasks without failure for a specified constraints of time and space, as specified in the design and operating conditions specified temperature, humidity, vibration and action. A relatively new methodologies for developing complex software systems engineering is an aspect-oriented software systems, that provides the new methods for the separation of concerns multiple module configuration or intervention and automatic integration them with a system. In this paper, using MLP artificial neural networks and adaptive fuzzy neural network assess the reliability of the aspect oriented software and at the end, two methods were compared with each other. After examination, the root means square error method based on artificial neural networks, fuzzy neural network-based method of 0.024262 and 0.021874 to be adaptive. The results show that the method is based on adaptive fuzzy neural networks with low error in the estimation of reliability, performance is better than the MLP artificial neural network approach.
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Comparison of Requirement Prioritization Techniques to Find Best Prioritization Technique
Статья научная
This paper describes an assessment of different requirement prioritization techniques (binary search tree, AHP, hierarchy AHP, spanning tree matrix, priority group/Numerical Analysis, bubble sort, MoSoW, simple ranking and Planning Game) on the basis of previous literature. Five research papers and thesis are critically reviewed, in order to select best requirement prioritization method. The study of literature shows that AHP is the best requirements prioritization technique amongst all the requirements prioritization techniques. It provides the most efficient and reliable results which are on ratio scale. It is fault- tolerant and provides a consistency check.
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Статья научная
The development of methods for assessing lecturers' performance is needed to motivate lecturers to achieve institutional targets. Currently, lecturers are required to be able to adapt to the rapid development of technology. Lecturer performance assessment must be done periodically. Competence is measured as a basis for planning resource development activities. The method that is often used for assessing lecturer performance is the Simple Additive Weighting (SAW) method. However, the SAW method has drawbacks, namely 1) the process of determining criteria is only carried out by the leadership (subjective); 2) The SAW method can only be applied to multi-criteria data ; 3) Data ranking problems. Based on this deficiency, a new method was built, namely, the Weighted Performance Indicator (WPI) method using respondents’ opinion to determine the criteria. This study aims to compare the performance of the two methods. Testing criteria using SPPS application dan WPI method, while testing methods utilized the SAW method and the WPI method. The results of the criterion test show the Percentage of Similarity of data validity = 96.7 % witht the minimum percentage limit (MPL) = 40%. While the results of the SAW method and WPI method testing resulted in the highest score in the 13th alternative, namely SAW score (v13) = 793.76 and WP score (WP13) = 0.928, and the lowest value in the 30th alternative, SAW score (v30) = 18.60 and WP score (WP30) = 0.140. the ranking positions in these two methods show similarities. However, for other alternatives, the rating value can be different. The WPI method is a scientific development in the field of decision support systems that can be applied to other performance assessments, such other human resources, system performance assesment etc. The results of this study prove that the WPI method can be used as a performance assessment method with different characteristics from the SAW method.
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Статья научная
In the work, an analysis of modern methods of Educational Data Mining (EDM) was carried out, on the basis of which a set of methods of EDM was developed for the training of vocational education teachers. The basic methods of EDM are considered, namely Prediction, Clustering, Relationship Mining, Distillation of Data for Human Judgment, Discovery with Models. The possibilities of using artificial neural networks, in particular, networks of Long-Short-Term Memory (LSTM), to predict the results of the educational process are described. The main methods of clustering and segmentation of educational data are considered. The basic methods of EDM are complemented by specialized methods of digital image pre-processing and methods of artificial intelligence, taking into account the peculiarities of the training of future specialists in engineering and pedagogical specialties. As specialized methods of digital image pre-processing, methods of filtering, contrast enhancement and contour selection are used. As specialized methods of artificial intelligence, methods of image segmentation, object detection on images, object detection using fuzzy logic were used. Methods of object detection on images using convolutional neural networks and using the Viola-Jones method are described. To process data with a certain degree of uncertainty, it is proposed to apply the methods of EDM and Fuzzy Logic in a integral manner. Ways of integrating Fuzzy Logic with methods of data clustering, image segmentation and object detection on images are considered. The possibilities of applying the developed complex of specialized methods of EDM in the educational process, in particular, when performing STEM (Science, Technology, Engineering and Mathematics) projects, are described.
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