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 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 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&amp;rsquo; 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 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>

scholarly journals Behavioral Patterns for Automatic Detection of Learning Styles in Learning Management Systems: a Case Study

2015 ◽  
Vol 106 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Guillermo Salazar Lugo ◽  
Luis-Felipe Rodríguez ◽  
Ramona Imelda García López ◽  
Adrián Macías Estrada ◽  
Moisés Rodríguez Echeverría
Keyword(s):  
Learning Styles ◽  
Automatic Detection ◽  
Learning Management Systems ◽  
Management Systems ◽  
Behavioral Patterns ◽  
Learning Management

Role of Indian Print and Digital Media in Learning Analytics

2022 ◽  
pp. 199-218
Author(s):  
Chandana Aditya
Keyword(s):  
Data Mining ◽  
Digital Media ◽  
News Media ◽  
Learning Analytics ◽  
Educational Data Mining ◽  
Learning Management Systems ◽  
Educational Programs ◽  
Mass Scale ◽  
Management Systems ◽  
Learning Management

There is a pressing need for data management and learning management systems. Educational data mining and learning analytics are two related aspects of educational technology that promote an overall effective teaching-learning system. The news media has the potential to act as a tool of learning analytics since they can easily access information at a mass scale. There are instances of leading newspapers organizing different educational programs where students from all the social layers have an opportunity to participate. A review of the programs reveals that all the programs collect and analyze educational data, which can form a research base of learning analytics. This chapter presents the description of three such educational programs organized by the leading media houses of India. This chapter also reflects on the contribution to learning management systems and educational data mining for the improvement of the overall educational system.

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