Intelligent Agents for Dynamic Optimization of Learner Performances in an Online System

Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environme...

Full description

Saved in:
Bibliographic Details
Published in:Journal of information technology education 2017, Vol.16, p.31-45
Main Authors: Kamsa, Imane, Elouahbi, Rachid, El Khoukhi, Fatima
Format: Article
Language:English
Subjects:
Abstract Reasoning
Cognitive Processes
Educational Benefits
Electronic Learning
Foreign Countries
Graduate Students
Identification
Intelligent Tutoring Systems
Language Proficiency
Language Skills
Learning Disabilities
Logical Thinking
Masters Programs
Memorization
Memory
Online Courses
Problem Solving
Simulation
Skill Development
Statistical Analysis
Student Improvement
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these vulnerabilities due to the lack of direct contact with the teacher, who would be able to point out the learner's difficulties and help to rectify them. Methodology: The research sample was 49 learners enrolled in an online course. We focused on three cognitive factors: language, memory, and reasoning. We propose an approach to optimize learners' performances based on two intelligent agents that model the role of a teacher: the "detector agent" and the "rectifier agent". Contribution: The intelligent agents beneficially contribute to e-learning enrichment and the development of cognitive skills and solidification of knowledge acquisition. This is achieved by strengthening the memory, the assimilation of lessons by improving language skills, and the reinforcement of problem solving by developing reasoning and analysis capacity. Findings: The results show that the proposed approach efficiently detects the weaknesses of learners and resolves them intelligently. Future Research: The approach toward e-learning performance can be improved by focusing on other factors and intelligent agents that can improve the yield for learners and more effectively optimize system operation for their perceived needs.
ISSN:1547-9714
1539-3585
DOI:10.28945/3627