A Personalized Learning Platform Based on Multi-Agent and Moodle

2009 ◽  
Author(s):  
Jian Li ◽  
Lulu Ding ◽  
Pengkun Li
Keyword(s):  
Personalized Learning ◽  
Learning Platform ◽  
Multi Agent

scholarly journals Multi-Agent System Observer: Intelligent Support for Engaged E-Learning

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1370
Author(s):  
Igor Vuković ◽  
Kristijan Kuk ◽  
Petar Čisar ◽  
Miloš Banđur ◽  
Đoko Banđur ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Intelligent Support ◽  
Course Success ◽  
States Of Emergency ◽  
Learning Platform ◽  
Rapid Spread ◽  
E Learning ◽  
Multi Agent ◽  
Observer System

Moodle is a widely deployed distance learning platform that provides numerous opportunities to enhance the learning process. Moodle’s importance in maintaining the continuity of education in states of emergency and other circumstances has been particularly demonstrated in the context of the COVID-19 virus’ rapid spread. However, there is a problem with personalizing the learning and monitoring of students’ work. There is room for upgrading the system by applying data mining and different machine-learning methods. The multi-agent Observer system proposed in our paper supports students engaged in learning by monitoring their work and making suggestions based on the prediction of their final course success, using indicators of engagement and machine-learning algorithms. A novelty is that Observer collects data independently of the Moodle database, autonomously creates a training set, and learns from gathered data. Since the data are anonymized, researchers and lecturers can freely use them for purposes broader than that specified for Observer. The paper shows how the methodology, technologies, and techniques used in Observer provide an autonomous system of personalized assistance for students within Moodle platforms.

scholarly journals The system of personalized instruction in school education: problems of implementation and adaptation

2020 ◽  
pp. 142-152
Author(s):  
Polina O. Kraynova ◽  
Alexey S. Obukhov
Keyword(s):  
General Education ◽  
Personal Characteristics ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning System ◽  
High Quality Research ◽  
Global Trends ◽  
Learning Platform ◽  
The Usa ◽  
The Individual

In the context of global trends in the humanization of education, issues of differentiation, individualization and personalization of education are actively discussed. At the same time, the key question remains – how to preserve the individual capabilities, interests and needs of each student while maintaining collective learning formats? How to take into account the personal characteristics and capabilities of each when passing and mastering general education programs? One such solution was the PCBL personalized learning platform developed in the USA. Currently, the Khoroshevskaya school is introducing and adapting this platform to the Russian conditions of education. The article examines the specific case of implementing a system of personalized competency-based education in a separate school – what problems, barriers and difficulties are encountered in its implementation. The study is built in the logic of qualitative research on the basis of high-quality research interviews with the main participants in the educational process in the context of introducing a personalized learning system.

scholarly journals Methodological aspects of the web course of chemical disciplines for non-chemical specialties in universities

2020 ◽  
Vol 1 (1) ◽  
pp. 37-42
Author(s):  
Naila Guliyeva ◽  
Keyword(s):  
Inorganic Chemistry ◽  
Online Training ◽  
Personalized Learning ◽  
Learning System ◽  
Learning Platform ◽  
Web Course ◽  
Effective Use ◽  
Methodological Aspects ◽  
Theoretical Foundations ◽  
The Web

The article analyzes the possibilities of effective use of interactive learning elements, which is a learning platform designed to provide teachers, administrators and students with a reliable, safe and comprehensive learning system to create a personalized learning environment. It is acknowledged that the utilization of online training tools has shown to be effective for studying the “Theoretical Foundations of Chemistry” and “Inorganic Chemistry” disciplines.

COGNITIVE, AFFECTIVE AND CONATIVE MODEL FOR ANALYSING HIGHER EDUCATION STUDENTSq

2017 ◽  
Vol 10 (13) ◽  
pp. 133
Author(s):  
Priyaadharshini Manickavasag ◽  
Swati S Surwade
Keyword(s):  
Higher Education ◽  
Learning Environment ◽  
Student Performance ◽  
Learning Style ◽  
Management System ◽  
Research Work ◽  
Personalized Learning ◽  
Three Dimensions ◽  
Learning Abilities ◽  
Learning Platform

Many models are used in recent years to analyze behavior of the students in the higher education. Analyzing the learning style and student performance in academic studies are very essential to enhance their performance. This research work is focused on analyzing the learners behavior using three dimensions, i.e., cognitive, affective, and conative model. In this paper, we used Moodle learning management system which is a learning platform to create a personalized learning environment and to track learning abilities using activities. This model will be helpful to study the cognitive, conative, and emotions of students. 

scholarly journals Multi-Agent Adaptive e-Learning System Based on Learning Styles

2021 ◽  
Vol 4 (1) ◽  
pp. 1-12
Author(s):  
Faith Ngami Kivuva ◽  
Elizaphan Maina ◽  
Rhoda Gitonga
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Intelligent Agents ◽  
Personalized Learning ◽  
Learning Systems ◽  
Learning System ◽  
Personalized Recommendation ◽  
Information Agent ◽  
E Learning ◽  
Multi Agent

Most traditional e-learning system fails to provide the intelligence that a learner may require during their learning process. Different learners have different learning styles but the current e-learning systems are not able to provide personalized learning. In this paper, we discuss how intelligent agents can aid learners in their learning process. Three agents have been developed namely, learner agent, information agent, and tutor agents that will be integrated into a learning management system (Moodle). Learners are provided with a personalized recommendation based on the learning styles.

scholarly journals Design of an Adaptive e-Learning System based on Multi-Agent Approach and Reinforcement Learning

2021 ◽  
Vol 11 (1) ◽  
pp. 6637-6644
Author(s):  
H. El Fazazi ◽  
M. Elgarej ◽  
M. Qbadou ◽  
K. Mansouri
Keyword(s):  
Reinforcement Learning ◽  
Learning Style ◽  
Learning Process ◽  
Learning Experience ◽  
Personalized Learning ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
Multi Agent

Adaptive e-learning systems are created to facilitate the learning process. These systems are able to suggest the student the most suitable pedagogical strategy and to extract the information and characteristics of the learners. A multi-agent system is a collection of organized and independent agents that communicate with each other to resolve a problem or complete a well-defined objective. These agents are always in communication and they can be homogeneous or heterogeneous and may or may not have common objectives. The application of the multi-agent approach in adaptive e-learning systems can enhance the learning process quality by customizing the contents to students’ needs. The agents in these systems collaborate to provide a personalized learning experience. In this paper, a design of an adaptative e-learning system based on a multi-agent approach and reinforcement learning is presented. The main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the Q-learning algorithm. The proposed system is focused on three principal characteristics, the learning style according to the Felder-Silverman learning style model, the knowledge level, and the student's possible disabilities. Three types of disabilities were taken into account, namely hearing impairments, visual impairments, and dyslexia. The system will be able to provide the students with a sequence of learning objects that matches their profiles for a personalized learning experience.

scholarly journals An Adaptive Normative Multi Agent System using WEb 3.0 for e-Learning Platform

2013 ◽  
Vol 4 (12) ◽  
pp. 7-16
Author(s):  
Namrata DHANDA ◽  
Manuj DARBARİ ◽  
Neelu Jyoti AHUJA ◽  
Imran Ali SIDDIQU
Keyword(s):  
Multi Agent System ◽  
Community Based ◽  
Agent System ◽  
Web 3.0 ◽  
Learning Platform ◽  
E Learning ◽  
Multi Agent ◽  
Single User ◽  
Community Based Learning ◽  
User Learning

The growing concern for education and innovative technologies has led to a new dimension of learning. The paper proposes a new framework NormATel using the concept of Normative Multi-Agent system, Activity Theory and e-Learning. The basic idea of the paper is to make e-learning more user specific using the concept of Web 3.0, like its ability to work on two separate modes: single user learning and community based learning. The proposed framework is verified using Deontic Logic.

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