A genetic algorithm for workload scheduling in cloud based e-learning

2012 ◽  
Author(s):  
Octavian Morariu ◽  
Cristina Morariu ◽  
Theodor Borangiu
Keyword(s):  
Genetic Algorithm ◽  
Workload Scheduling ◽  
E Learning

scholarly journals Adaptive e-learning using Genetic Algorithm and Sentiments Analysis in a Big Data System

2017 ◽  
Vol 8 (8) ◽  
Author(s):  
Youness MADANI ◽  
Jamaa BENGOURRAM ◽  
Mohammed ERRITALI ◽  
Badr HSSINA ◽  
Marouane Birjali
Keyword(s):  
Genetic Algorithm ◽  
Big Data ◽  
Data System ◽  
E Learning

scholarly journals Um sistema baseado em PLN e AG para apoiar a mediação pedagógica em fóruns de discussão

2018 ◽  
Vol 26 (3) ◽  
pp. 61
Author(s):  
Máverick André Dionísio Ferreira ◽  
Rafael Ferreira Leite Mello ◽  
Cícero Garrozi ◽  
Vitor Belarmino Rolim ◽  
Anderson Pinheiro Cavalcanti
Keyword(s):  
Genetic Algorithm ◽  
Confidence Interval ◽  
Language Processing ◽  
Teaching And Learning ◽  
Statistical Test ◽  
Teaching Performance ◽  
Discussion Forums ◽  
E Learning

With the growth of e-learning discussion forums have been widely used to promote interaction and collaboration between students and teachers asynchronously. Despite the benefits to the teaching and learning process the use of the forums in the e-learning can mean overload for the teachers/tutors given the large amount of information generated in the debates. Taking into consideration the importance of the teaching performance in the follow-up of the discussions and consequent help to the students of the e-learning, the teacher/tutor overload is considered a problem. Therefore, this study presents a system that integrates Natural Language Processing and Genetic Algorithm to classify postings from discussion forums such as Doubt, Neutral comment or Answer. As a way of evaluating the performance of the proposed system, experiments were conducted in three databases, with a total of 1769 posts, arriving at the average F-measures of 0.981, 0.997 and 0.988 in the classification of posts as Doubt, Neutral comment and Answer, respectively. After the experiments the results were analyzed by means of the z statistical test with a confidence interval of 95%. The results show the potential of the proposed system to identify post genres, from discussion forums, and the teacher/tutor can use it as a support to direct their efforts, for example, to students with any doubts in the current discussion.

scholarly journals A Personalized Web Based E-Learning Recommendation System To Enhance and User Learning Experience

2020 ◽  
Vol 9 (1) ◽  
pp. 1186-1195
Keyword(s):  
Data Mining ◽  
Genetic Algorithm ◽  
Clustering Algorithm ◽  
Recommendation System ◽  
User Behavior ◽  
Search Algorithm ◽  
Learning Experience ◽  
Research Work ◽  
Web Based ◽  
E Learning

The key aim of the data mining techniques is to help the user by reducing the effort for exploring the data, recovering the patterns, and implementing applications that help to find the knowledge specific contents, decision making, and predictions. This research work develops a recommendation system by using the merits of data mining algorithms. They are used for designing web-based e-learning recommendation systems. This model aims to understand the user behavior and contents requirements of the learner. This purpose is solved by obtaining the information from the data source and producing the suggestions of suitable content to the learner. The concept of web content mining and web usage mining has been combined together for performing the required work. This technique involves the genetic algorithm and k-means clustering algorithm for designing the presented model. In this work the k-means clustering algorithm has been used to track user behavior and the genetic algorithm has been used as a search algorithm to find the necessary resources in the database. Finally, the presented system is implemented and its performance is measured. The estimated results demonstrate that the presented model enhances the accuracy of recommendations and also speeds up the computations. A related performance calculation has also provided to justify this conclusion. The obtained results demonstrate that this technique is acceptable for new generation application designs

Sign in / Sign up

Export Citation Format

Share Document