Multi-agent Based E-Learning Intelligent Tutoring System for Supporting Adaptive Learning

2013 ◽  
Author(s):  
Xu Daomin
Keyword(s):  
Adaptive Learning ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Tutoring System ◽  
Agent Based ◽  
E Learning ◽  
Multi Agent

scholarly journals Multi-Agent Based Intelligent Tutoring System Source Code Generation Using MASITS Tool

2010 ◽  
Vol 41 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Egons Lavendelis ◽  
Janis Grundspenkis
Keyword(s):  
Code Generation ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Source Code ◽  
Requirements Analysis ◽  
General Purpose ◽  
Tutoring System ◽  
Agent Based ◽  
Development Tools ◽  
Multi Agent

Multi-Agent Based Intelligent Tutoring System Source Code Generation Using MASITS ToolSeveral agent development tools have been proposed. At the same time, specific tools for agent based Intelligent Tutoring System (ITS) development do not exist. However, ITSs have some specific characteristics that must be taken into consideration during the development. General purpose Agent Oriented Software Engineering (AOSE) methodologies and therefore development tools do not sufficiently correspond to the characteristics of ITSs. Additionally, the general purpose AOSE methodologies and tools do not allow plugging in domain specific rules and diagrams. Thus, usage of knowledge gained in ITS research during the development process is limited. In the absence of general tools that allow plugging in knowledge from ITS research, a specific tool named MASITS has been developed. The tool supports a specific agent based ITS development methodology named MASITS which takes into consideration specific characteristics of ITSs and integrates knowledge from ITS research. The tool supports all phases of ITS development, starting from requirements analysis and ending with deployment. Requirements analysis and design phases are supported by appropriate diagram creation tools. Implementation is supported by source code generation from diagrams created during the design phase. JADE platform is used for agent implementation. Thus, Java classes for ontology, agents and behaviours are generated from the design diagrams. The paper includes a brief overview of diagrams used in the source code generation and detailed algorithms for source code generation from the diagrams.

The Study on the Multiple Agent-Based Independent and Collaborative Intelligent Tutoring System Model

2013 ◽  
Vol 846-847 ◽  
pp. 1885-1888
Author(s):  
Jian Hua Wang ◽  
Yan Yu ◽  
Jun Jie Guo
Keyword(s):  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
University Teaching ◽  
System Model ◽  
Computer Assisted ◽  
Intelligent Network ◽  
Tutoring System ◽  
Agent Based ◽  
Multiple Agent ◽  
Multi Agent

Over the years, the traditional computer-assisted teaching can not meet the needs of university teaching, the traditional teaching system software, most of the existence of low intelligence, lack of teaching strategies and other shortcomings.Multi-AGENT technology and intelligent tutoring systems is the current research focus in computer intelligence education. Integrating multi-Agent features and multi-Agent application theories in ITS, this paper proposes a multiple Agent-based intelligent network tutoring system design model, detailedly analyzes the functions of each layer in the system, and presents system database category design and system model features.

scholarly journals Intelligent Tutoring System

2020 ◽  
pp. 121-144
Author(s):  
Abhishek Singh Rathore ◽  
Siddhartha Kumar Arjaria
Keyword(s):  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
The Internet ◽  
Tutoring System ◽  
Time Data ◽  
Self Regulated Learning ◽  
Formal And Informal Learning ◽  
Real Time Data ◽  
E Learning ◽  
Teaching Learning

With digitization, a rapid growth is seen in educational technology. Different formal and informal learning contents are available on the internet. Intelligent tutoring system provides personalized e-learning to the learners. Different attributes like historical data, real-time data, behavioral, and cognitive are usually used for personalization. Based on the personalization, the intelligent tutoring system aims to provide easy and effective understanding. Recent research highlights the effect of learner's behavior and emotions on effective teaching-learning process. This chapter provides a brief description of the intelligent tutoring system, current developments, instructional techniques, proposed solution, and future recommendations. The emphasis of the study is to provide insights on self-regulated learning.

scholarly journals Mathtutor: A Multi-Agent Intelligent Tutoring System

2006 ◽  
pp. 231-242 ◽  
Author(s):  
Janétte Cardoso ◽  
Guilherme Bittencourt ◽  
Luciana B. Frigo ◽  
Eliane Pozzebon ◽  
Adriana Postal
Keyword(s):  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Tutoring System ◽  
Multi Agent
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