A Personalized Learning Recommendation System Architecture for Learning Management System

2017 ◽  
Author(s):  
Thoufeeq Ahmed Syed ◽  
Vasile Palade ◽  
Rahat Iqbal ◽  
Smitha Sunil Kumaran Nair
Keyword(s):  
System Architecture ◽  
Management System ◽  
Recommendation System ◽  
Learning Management System ◽  
Personalized Learning ◽  
Learning Management

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 Software Agents for Managing Learning Plans

10.28945/2994 ◽  
2006 ◽  
Author(s):  
Igor Hawryszkiewycz
Keyword(s):  
Management System ◽  
Learning Management System ◽  
Software Agents ◽  
Personalized Learning ◽  
System Software ◽  
Learning Management ◽  
Pedagogical Function ◽  
Generic Agents ◽  
Learning Plans ◽  
Learner Needs

Support for personalized learning requires further assistance than currently available with most learning management system. Software agents have been proposed as one way of providing such assistance. The paper identifies three kinds of software agents, pedagogical, function and process agents. The paper then concentrates on process agents, which guide learners to develop personalized preferred learning plans that match learner needs and then manage progress through such plans. Agent support will only be practical if widely applicable generic agents, which can be reused in many plans, can be identified. Such agents can then be adapted to particular learner needs without extensive programming. The paper identifies some generic agents for this purpose and concentrate on agents that manage progress through the learning plans.

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