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The rapidly increasing use of information technologies in the educational process increases the need for automated tools and systems capable of objective, reliable and operational evaluation of students' knowledge. Computer-based testing is a technological and objective form of knowledge control. In this report, on the basis of evaluation criteria are analyzed and compared multilayer perceptron neural network and neural network with radial-basis activation function and is proposed a model to increase the accuracy and objectivity of evaluation for computer knowledge control.
Knowledge and achievement evaluation system MISKANTAS-22 based on density matrix and neural network methods were designed as an advisor to the lecturer for automated evaluation of open-type questions. New type of plugin for Moodle system Essay Plus was created, tested, and evaluated for grading purposes. New type of user-friendly interfaces for lecturer and for student in Moodle system was realized. New concept of test of Essay Plus type was created, tested, and realized. System allows to evaluate the student's answers in real time regime.
Proceedings of the International Scientific Conference - Sinteza 2019
The Principle of Constructing the Algorithm of the Functioning of the Neural Network - the Basis of the Exam System of Artificial Intelligence2019 •
IOSR Journal of Computer Engineering (IOSR-JCE)
Artificial Neural Network Analysis for Predicting the Performance of Students in an Examination2023 •
The academic performance of students in education is one of the important criteria for determining the quality of students going into the labor market. There are several factors affecting the academic performance of students in higher institutions of learning and these factors have seriously led to an increase in failure rates of students in their examinations. Some of the factors affecting the performance of students are the wrong time of giving orientation to students, poor guidance, poor communication skills, attitude and mentality of students towards their studies, joining of bad gangs, and wrong use of technology, just to mention a few. Academic performance of HND I students of Computer Science, Federal Polytechnic, (FEDPOFFA) were predicted using an artificial neural network model in terms of their total scores in the examination. Artificial neural networks are forecasting methods that are based on simple mathematical models of the brain. They allow complex nonlinear relationships between the response variable and its predictors. In this paper, the performance of students in the class of 183 students was analyzed using an artificial neural network model. The model was designed using their practical scores, continuous assessment score, and their exam scores that were collected in the Computer Architecture course. 70% of the data were used for training, 15% were used for validation, and the remaining 15% was used for testing. The performance of the students and the regression analysis of these students were carried out using an artificial neural network. The network model was then applied to a certain set of students and it was able to accurately predict the students' total scores.
African Journal of Business Management
Course performance evaluation based on neural network modeling2014 •
International Journal of Innovative Research in Computer and Communication Engineering
Calculating Student Performance of Jagannath University UsingArtificial Neural Network2017 •
In this paper an Artificial Neural Network (ANN) display, for estimating the execution of a sophomore understudy selected in designing majors in the Faculty of Science in Jagannath University of Bangladesh was created and tried. Various variables that may conceivably impact the execution of an understudy were illustrated. Such elements as higher secondary school score, score of subject, for example, Math I, Math II, Electrical Circuit I, and Electronics I taken amid the understudy first year, number of credits passed, understudy aggregate review point normal of first year, sorts of secondary school went to and gender orientation, among others, were then utilized as information factors for the ANN demonstrate. A model in light of the Multilayer Perceptron Topology was created and prepared utilizing information spreading over five eras of alumni from the Computer Science and Engineering Department of the Jagannath University, Dhaka Bangladesh. Test information assessment demonstrates ...
The goal of this study is the development of an assessment system with the support of a Neural Network approach optimized with the use of Genetic Programming. The data used as training data are real data derived from an educational project. The developed system is able to assess learners‟ answers through various criteria and has been proved capable of assessing data from both single select and multiple choice questions in an e-learning environment
As we know that in maximum university the evaluation of the student's performance I done manually by the faculties. This System of student performance evaluation is non-transparent and often leads to dissatisfaction among students. This project aims to solve the problem by designing a user interface which would work on supervised learning using Neural Network. Data mining techniques are widely used in educational field to find new hidden patterns from student's data. The hidden patterns that are discovered can be used to understand the problem arise in the educational field. Data Mining (DM), or Knowledge Discovery in Databases (KDD), is an approach to discover useful information from large amount of data. DM techniques apply various methods in order to discover and extract patterns from stored data. The pattern found will be used to solve a number of problems occurred in many fields such as education, economic, business, statistics, medicine, and sport. The large volume of data stored in those areas demands for DM approach because the resulting analysis is much more precise and accurate.
As we know that in maximum university the evaluation of the student's performance I done manually by the faculties. This System of student performance evaluation is non-transparent and often leads to dissatisfaction among students. This project aims to solve the problem by designing a user interface which would work on supervised learning using Neural Network. Data mining techniques are widely used in educational field to find new hidden patterns from student's data. The hidden patterns that are discovered can be used to understand the problem arise in the educational field. Data Mining (DM), or Knowledge Discovery in Databases (KDD), is an approach to discover useful information from large amount of data. DM techniques apply various methods in order to discover and extract patterns from stored data. The pattern found will be used to solve a number of problems occurred in many fields such as education, economic, business, statistics, medicine, and sport. The large volume of data stored in those areas demands for DM approach because the resulting analysis is much more precise and accurate.
Information and Knowledge Management
Cognitive Factors in Students' Academic Performance Evaluation using Artificial Neural Networks2018 •
Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient rating (IQR), Confidence Level (CoL) and Time Management ability gives an equal platform for better evaluation of students’ performance using Artificial Neural Network. Artificial Neural Networks (ANN) models, which has the advantage of being trained, offers a more robust methodology and tool for predicting, forecasting and modeling phenomena to ascertain conformance to desired standards as well as assist in decision making. This work employs Machine Learning and cognitive science which uses Artificial Neural networks (ANNs) to evaluated students’ academic performance in the Department of Computer Science, Akwa Ibom State University. It presents a survey of the design, building and functionalities of Artificial Neural Network for the evaluation of students’ academic performance using cognitive factors that could affect student’s performances. Keywords : Cognitive, Intelligent Quotient Ra...
The final scores of the students taking Fundamentals of Information Technologies I (BIL101U) course at Anadolu University Open Education Faculty were intended to be predicted in this study. Multilayer Perceptron (MLP) model as one of the Artificial Neural Networks and Radial Basis Function (RBF) were used. The analyses were carried out by using the data obtained from around 52 thousand students taking BIL101U course in 2014-2015 fall semester. Networks established by the MLP in the context of the data used make more accurate predictions compared to the ones established by RBF. Moreover, it has been observed that the most important variable in the prediction of final scores of the students was the midterm exam results, in other terms; it was the achievement during the term. The findings obtained as a result of this study are considered to shed light on the further studies to be conducted on developing particularly the support aspect of the learner-centered learning environments.
2023 •
Jurnal Studi Hadis Nusantara
Ziarah Kubur Perspektif Pendekatan Historis-Sosiologis dan Kontekstualisasinya dalam Kehidupan Kotemporer2021 •
Close to the bone: current studies in bone technologies
Bone and antler artefacts from an 8-5th century BC settlement at Grzybiany, South-Western PolandRodis. Journal of medieval and post-medieval archaeology
El recinte emmurallat de la vila d'Ullastret: anàlisi i evolució a partir de les darreres intervencionsEducação e Fronteiras
Direito à Educação: o desafio de melhorar a alfabetização nos anos iniciais do ensino fundamental no Brasil2018 •
Proceedings of the 3rd World Congress on Mechanical, Chemical, and Material Engineering
Diesel Particulate Matter Exposure to an Operator of LHD Loader Working in an Active Ore Heading Area2022 •
Molecular Biology and Evolution
Major-histocompatibility-complex DRB genes of a New-World monkey, the cottontop tamarin (Saguinus oedipus)1992 •
Archaeological and Anthropological Sciences
Intra-site spatial approaches based on taphonomic analyses to characterize assemblage formation at Pleistocene sites: a case study from Buena Pinta Cave (Pinilla del Valle, Madrid, Spain)2023 •
Curriculum Perspectives
The Australian Curriculum gambit: playing knowledge games with education policy2024 •
2024 •
bioRxiv (Cold Spring Harbor Laboratory)
Downscaling mutualistic networks from species to individuals reveals consistent interaction niches and roles within plant populations2024 •
Journal of Plant Pathology
First report of Diplodia seriata causing canker and dieback on hawthorn trees in Turkey