Design and Analysis of a Multi-Agent E-Learning System Using Prometheus Design Tool

TL;DR

This paper details the design and analysis of a multi-agent e-learning pre-assessment system modeled with Prometheus AUML, including system design, domain knowledge organization, and predictive data analysis.

Contribution

It introduces a detailed AUML-based modeling approach for a multi-agent e-learning pre-assessment system and presents data analysis and prediction models for future assessments.

Findings

Effective multi-agent system design using Prometheus AUML

Domain knowledge abstraction enhances system clarity

Predictive models show promising assessment accuracy

Abstract

Agent unified modeling languages (AUML) are agent-oriented approaches that supports the specification, design, visualization and documentation of an agent-based system. This paper presents the use of Prometheus AUML approach for the modeling of a Pre-assessment System of five interactive agents. The Pre-assessment System, as previously reported, is a multi-agent based e-learning system that is developed to support the assessment of prior learning skills in students so as to classify their skills and make recommendation for their learning. This paper discusses the detailed design approach of the system in a step-by-step manner; and domain knowledge abstraction and organization in the system. In addition, the analysis of the data collated and models of prediction for future pre-assessment results are also presented.