scholarly journals Early Detection of Drop Outs in E-Learning Systems

2019 ◽  
Vol 2 (3) ◽  
pp. 1008-1015
Author(s):  
Neslihan Ademi ◽  
Suzana Loshkovska
Keyword(s):  
Data Mining ◽  
Early Detection ◽  
Learning Management Systems ◽  
Management Systems ◽  
Online Behavior ◽  
Event Logs ◽  
E Learning ◽  
Learning Management ◽  
Using Data ◽  
Drop Outs

After the popularity of Learning Management Systems, Data Mining and Learning Analytics have become emerging topics. Learning Management Systems such as Moodle, provide big amount of data to be used in analyzing students’ online behavior. This paper represents a method for early detection of drop outs from a Bachelor degree course using data mining methods. Data is collected through Moodle logs. For early detection, event logs till the first exam is taken into consideration. Decision Tree (DT) and Bayesian Network (BN) algorithms are used for the prediction. In the end it is shown that DT algorithm gives a higher over-all accuracy but BN is better for discovering fail cases as it has higher specificity.

scholarly journals Using Data Mining In Learning Management Systems Amidst Covid-19

2020 ◽  
Vol 6 (3) ◽  
pp. 213
Author(s):  
Froilan D Mobo
Keyword(s):  
Data Mining ◽  
Pattern Mining ◽  
Learning Management Systems ◽  
The Philippines ◽  
Management Systems ◽  
Official Gazette ◽  
Learning Management ◽  
The Republic ◽  
Using Data ◽  
The One

<p>The Second Semester of Academic Year 2019-2020 was temporarily suspended due to the widespread COVID-19 last March 16, 2020, forcing the President of the Republic of the Philippines, Hon. Rodrigo Roa Duterte imposed an Enhanced Community Quarantine in Luzon which is known as a lockdown closing all the border points of each town and provinces. One of the major problem encountered during the lockdown is the suspension of classes because as per IATF guidelines you need to stay home, the said Memorandum Order was posted in the official gazette, (Medialdea, 2020)</p><p>The dataset on the features of the Learning Management Systems using Moodle is that Professors will be the one who will set the topics, quizzes, and exercises for his class even the assessment methods on the system. To prevent from slowing down the network,  the Team of Seaversity the developer of the learning management systems headed by C/E Ephrem Dela Cernan conducts a ZOOM Training to all Faculty to be familiarized more on the Learning Management Systems of the Philippine Merchant Marine Academy. </p><p>The Moodle Learning Management Systems is a user-friendly environment because of its features and users can easily adjust from the traditional face to face teaching going to e-Learning approach because of it’s all capabilities as a data mining methods such as statistics, association rule mining, pattern mining visualization, categorization, clustering, and text mining., (AlAjmi &amp; Shakir, 2013)</p>

scholarly journals Detecting Learning Styles in Learning Management Systems Using Data Mining

2016 ◽  
Vol 24 (4) ◽  
pp. 740-749 ◽  
Author(s):  
Madura Prabhani Pitigala Liyanage ◽  
K.S. Lasith Gunawardena ◽  
Masahito Hirakawa
Keyword(s):  
Data Mining ◽  
Learning Styles ◽  
Learning Management Systems ◽  
Management Systems ◽  
Learning Management ◽  
Using Data

scholarly journals Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

2015 ◽  
Vol 67 (1) ◽  
pp. 99-104 ◽  
Author(s):  
Gabroveanu Mihai
Keyword(s):  
Association Rules ◽  
Management System ◽  
Recommendation System ◽  
Learning Management System ◽  
Distributed Learning ◽  
Learning Management Systems ◽  
Management Systems ◽  
User Data ◽  
E Learning ◽  
Learning Management

Abstract Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

scholarly journals Towards Model-Based User Interface Development of e-Learning Management Systems

2012 ◽  
Vol 47 (1) ◽  
pp. 59-71
Author(s):  
Josefina Guerrero-García ◽  
Juan Manuel González-Calleros ◽  
Jaime Muñoz-Arteaga ◽  
Miguel Ángel León-Chávez ◽  
Carlos Reyes-García
Keyword(s):  
User Interface ◽  
Learning Management Systems ◽  
Management Systems ◽  
Model Based ◽  
E Learning ◽  
Learning Management

scholarly journals From Cognitive Landscapes to Digital Hyperscapes

2003 ◽  
Vol 4 (2) ◽  
Author(s):  
Jose Bidarra ◽  
Ana Dias
Keyword(s):  
Learning Styles ◽  
Learning Management Systems ◽  
Learning Objects ◽  
Management Systems ◽  
Digital Information ◽  
Cognitive Profiles ◽  
E Learning ◽  
Learning Management ◽  
Key Terms ◽  
Massive Information

<P> The widespread diffusion of e-Learning in organizations has encouraged the discovery of more effective ways for conveying digital information to learners, for instance, via the commonly called Learning Management Systems (LMS). A problem that we have identified is that cognitive variables and pedagogical processes are rarely taken into consideration and sometimes are confused with the mere use by learners of “diversified” hypermedia resources. Within the context of widespread dissemination of multimedia content that has followed the emergence of massive information resources, we discuss the need for more powerful and effective learner-centered tools capable of handling all kinds of design configurations and learning objects. </p> <P class=abstract><B>Key Terms: </B>cognitive profiles, learning styles, mind mapping, multimedia and hypermedia content, hyperscapes, e-Learning, learning objects, Learning Management Systems (LMS).</P>

Major Trends, Issues, and Challenges with Learning Management Systems

2014 ◽  
pp. 318-331 ◽  
Author(s):  
Betul Özkan Czerkawski ◽  
Dawn Panagiota Gonzales
Keyword(s):  
Higher Education ◽  
Online Instruction ◽  
Management System ◽  
Teaching And Learning ◽  
Learning Management Systems ◽  
Management Systems ◽  
Profound Impact ◽  
Blended Courses ◽  
E Learning ◽  
Learning Management

A Learning Management System (LMS) offers a set of tools for e-learning delivery and management. For institutions offering online or blended courses, an LMS has a profound impact on teaching and learning because it is the main technology used in higher education e-learning courses. This chapter discusses major trends, issues, and challenges with the LMS in the context of online instruction for higher education. The chapter ends with a discussion of new trends with LMSs.

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