Embedding Knowledge Management into Business Logic of E-learning Platform for Obtaining Adaptivity

2009 ◽  
pp. 859-865
Author(s):  
Dumitru Dan Burdescu ◽  
Marian Cristian Mihaescu ◽  
Bogdan Logofatu
Keyword(s):  
Knowledge Management ◽  
Business Logic ◽  
Learning Platform ◽  
E Learning

Learning objects management and evaluatio in an e-learning environment

1970 ◽  
Vol 6 (2) ◽  
Author(s):  
Hugo Rego ◽  
Tiago Moreira ◽  
Francisco José García-Peñalvo
Keyword(s):  
Knowledge Management ◽  
Learning Environment ◽  
Learning Process ◽  
Group Learning ◽  
Learning Objects ◽  
Authoring Tools ◽  
Learning Platform ◽  
E Learning ◽  
Teaching Learning ◽  
Educational Contents

The main aim of the AHKME e-learning platform is to provide a system with adaptive and knowledge management abilities for students and teachers. This system is based on the IMS specifications representing information through metadata, granting semantics to all contents in the platform, giving them meaning. In this platform, metadata is used to satisfy requirements like reusability, interoperability and multipurpose. The system provides authoring tools to define learning methods with adaptive characteristics, and tools to create courses allowing users with different roles, promoting several types of collaborative and group learning. It is also endowed with tools to retrieve, import and evaluate learning objects based on metadata, where students can use quality educational contents fitting their characteristics, and teachers have the possibility of using quality educational contents to structure their courses. The learning objects management and evaluation play an important role in order to get the best results in the teaching/learning process.

Improvement of Self-Assessment Effectiveness by Activity Monitoring and Analysis

2012 ◽  
pp. 1779-1798
Author(s):  
Dumitru Dan Burdescu ◽  
Marian Cristian Mihaescu
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Input Data ◽  
Software System ◽  
Business Logic ◽  
Self Assessment ◽  
Student Activities ◽  
Learning Platform ◽  
Engineering Department ◽  
E Learning

Self-assessment is one of the crucial activities within e-learning environments that provide learners with feedback regarding their level of accumulated knowledge. From this point of view, the authors think that guidance of learners in self-assessment activity must be an important goal of e-learning environment developers. The scope of the chapter is to present a recommender software system that runs along the e-learning platform. The recommender software system improves the effectiveness of self-assessment activities. The activities performed by learners represent the input data and the machine learning algorithms are used within the business logic of the recommender software system that runs along the e-learning platform. The output of the recommender software system is represented by advice given to learners in order to improve the effectiveness of self-assessment process. The methodology for obtaining improvement of self-assessment is based on embedding knowledge management into the business logic of the e-learning platform. Naive Bayes Classifier is used as machine learning algorithm for obtaining the resources (e.g., questions, chapters, and concepts) that need to be further accessed by learners. The analysis is accomplished for disciplines that are well structured according to a concept map. The input data set for the recommender software system is represented by student activities that are monitored within Tesys e-learning platform. This platform has been designed and implemented within Multimedia Applications Development Research Center at Software Engineering Department, University of Craiova. Monitoring student activities is accomplished through various techniques like creating log files or adding records into a table from a database. The logging facilities are embedded in the business logic of the e-learning platform. The e-learning platform is based on a software development framework that uses only open source software. The software architecture of the e-learning platform is based on MVC (model-view-controller) model that ensures the independence between the model (represented by MySQL database), the controller (represented by the business logic of the platform implemented in Java) and the view (represented by WebMacro which is a 100% Java open-source template language).

scholarly journals Extract Tacit Knowledge in the Learner Model of the Smart Tutoring System

2020 ◽  
Vol 15 (04) ◽  
pp. 235
Author(s):  
Fatima-Zohra Hibbi ◽  
Otman Abdoun ◽  
Haimoudi El Khatir
Keyword(s):  
Knowledge Management ◽  
Tacit Knowledge ◽  
Explicit Knowledge ◽  
Conversion Process ◽  
Tutoring System ◽  
Learner Model ◽  
Knowledge Conversion ◽  
Learning Platform ◽  
E Learning ◽  
Main Factors

Knowledge management (KM) is one of the main factors that have become extremely popular in recent years. KM is the processes which people explain information data using scientific and technological media and summarize it into concepts and rules to generate knowledge. This later can be implicit or explicit one. The aim of this contribution is to convert the tacit knowledge into explicit using Metaheuristics techniques. This paper aims to develop a model for converting tacit knowledge into explicit knowledge, using the Metaheuristics algorithm for the E-learning platform. For that purpose, the knowledge conversion process will respect the following steps: define the source of tacit knowledge and their methods, classify the tacit knowledge, then we evaluate the implicit knowledge conversion.

An Approach to Knowledge Management With an E-Learning Platform

2018 ◽  
pp. 668-684
Author(s):  
Henrique S. Mamede
Keyword(s):  
Knowledge Management ◽  
Tacit Knowledge ◽  
Explicit Knowledge ◽  
Organizational Knowledge ◽  
Management Process ◽  
Learning Platform ◽  
Working Solution ◽  
E Learning ◽  
Different Levels

Knowledge management is still a problem for many organizations and at two different levels: tacit knowledge, which typically resides in the head of each individual and gets lost for the organizations when a person goes to work with a different company; and explicit knowledge, which presents growing costs for its dissemination in the organization. In the chapter, the author proposes a model to address those problems, taking for base the SECI (socialization, externalization, combination, and internalization) model, originally developed for knowledge management, together with an e-learning platform and a set of activities as tools to implement a working solution. Such models have the ability to solve organizational knowledge problems, implementing a knowledge management process, allowing the transformation of tacit knowledge into explicit knowledge.

Improvement of Self-Assessment Effectiveness by Activity Monitoring and Analysis

2010 ◽  
pp. 198-217
Author(s):  
Dumitru Dan Burdescu ◽  
Marian Cristian Mihaescu
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Input Data ◽  
Software System ◽  
Business Logic ◽  
Self Assessment ◽  
Student Activities ◽  
Learning Platform ◽  
Engineering Department ◽  
E Learning

Self-assessment is one of the crucial activities within e-learning environments that provide learners with feedback regarding their level of accumulated knowledge. From this point of view, the authors think that guidance of learners in self-assessment activity must be an important goal of e-learning environment developers. The scope of the chapter is to present a recommender software system that runs along the e-learning platform. The recommender software system improves the effectiveness of self-assessment activities. The activities performed by learners represent the input data and the machine learning algorithms are used within the business logic of the recommender software system that runs along the e-learning platform. The output of the recommender software system is represented by advice given to learners in order to improve the effectiveness of self-assessment process. The methodology for obtaining improvement of self-assessment is based on embedding knowledge management into the business logic of the e-learning platform. Naive Bayes Classifier is used as machine learning algorithm for obtaining the resources (e.g., questions, chapters, and concepts) that need to be further accessed by learners. The analysis is accomplished for disciplines that are well structured according to a concept map. The input data set for the recommender software system is represented by student activities that are monitored within Tesys e-learning platform. This platform has been designed and implemented within Multimedia Applications Development Research Center at Software Engineering Department, University of Craiova. Monitoring student activities is accomplished through various techniques like creating log files or adding records into a table from a database. The logging facilities are embedded in the business logic of the e-learning platform. The e-learning platform is based on a software development framework that uses only open source software. The software architecture of the e-learning platform is based on MVC (model-view-controller) model that ensures the independence between the model (represented by MySQL database), the controller (represented by the business logic of the platform implemented in Java) and the view (represented by WebMacro which is a 100% Java open-source template language).

The IntelCities Community of Practice

2010 ◽  
pp. 263-284 ◽  
Author(s):  
Mark Deakin
Keyword(s):  
Information Technology ◽  
Knowledge Management ◽  
Community Of Practice ◽  
Digital Library ◽  
Integrated Model ◽  
Knowledge Management System ◽  
Learning Platform ◽  
Front End ◽  
E Learning ◽  
Back Office

The chapter examines the IntelCities Community of Practice (CoP) supporting the development of the organization’s e-Learning platform, knowledge management system (KMS) and digital library for eGov services. It begins by outlining the IntelCities CoP and goes on to set out the integrated model of electronically enhanced government (eGov) services developed by the CoP to meet the front-end needs, middleware requirements and back-office commitments of the IntelCities e-Learning platform, KMS and digital library. The chapter goes on to examine the information technology (IT) adopted by the CoP to develop the IntelCities e-Learning platform, KMS and digital library as a set of semanticallyinteroperable eGov services supporting the crime, safety and security initiatives of socially-inclusive and participatory urban regeneration programs.

The IntelCities Community of Practice

2009 ◽  
pp. 83-104 ◽  
Author(s):  
Mark Deakin
Keyword(s):  
Information Technology ◽  
Knowledge Management ◽  
Community Of Practice ◽  
Digital Library ◽  
Integrated Model ◽  
Knowledge Management System ◽  
Learning Platform ◽  
Front End ◽  
E Learning ◽  
Back Office

The chapter examines the IntelCities Community of Practice (CoP) supporting the development of the organization’s e-Learning platform, knowledge management system (KMS) and digital library for eGov services. It begins by outlining the IntelCities CoP and goes on to set out the integrated model of electronically enhanced government (eGov) services developed by the CoP to meet the front-end needs, middleware requirements and back-office commitments of the IntelCities e-Learning platform, KMS and digital library. The chapter goes on to examine the information technology (IT) adopted by the CoP to develop the IntelCities e-Learning platform, KMS and digital library as a set of semanticallyinteroperable eGov services supporting the crime, safety and security initiatives of socially-inclusive and participatory urban regeneration programs.

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