IJARAI Vol. 3 Issue 5 (2014)

Open Access | | 3 papers

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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A Multi_Agent Advisor System for Maximizing E-Learning of an E-Course

Author 1: Khaled Nasser ElSayed

Web-based learning environments have become popular in e-teaching throw WWW as a distance learning. There is an urgent need to enhance e-learning to be suitable to the level of learner knowledge. The presented paper uses intelligent multi-agent technology to advise and help learners to maximize their learning of an offered e-course. It will build its advices on the performance and level of education of learners including past and current learning. Most of advices are to guide learner to make exercises as quizzes or passing tests in different level of difficulties.

AI Agent Multi_Agents distant learning e-Learning e-Teaching Education e-Course

Abstract doi.org/10.14569/IJARAI.2014.030501 PDF

Implementation of an Intelligent Course Advisory Expert System

Author 1: Olawande Daramola Author 2: Onyeka Emebo Author 3: Ibukun Afolabi Author 4: Charles Ayo

Academic advising of students is an expert task that requires a lot of time, and intellectual investments from the human agent saddled with such a responsibility. In addition, good quality academic advising is subject to availability of experienced and committed personnel to undertake the task. However, there are instances when there is paucity of capable human adviser, or where qualified persons are not readily available because of other pressing commitments, which will make system-based decision support desirable and useful. In this work, we present the design and implementation of an intelligent Course Advisory Expert System (CAES) that uses a combination of rule based reasoning (RBR) and case based reasoning (CBR) to recommend courses that a student should register in a specific semester, by making recommendation based on the student’s academic history. The evaluation of CAES yielded satisfactory performance in terms of credibility of its recommendations and usability.

Academic advising expert system case-based reasoning JESS rule-based reasoning evaluation

Abstract doi.org/10.14569/IJARAI.2014.030502 PDF

External analysis of strategic market management can be realized based upon different human mindset–A debate in the light of statistical perspective

Author 1: Prasun Chakrabarti Author 2: Prasant Kumar Sahoo

The paper entails the statistical correlation of the investigations carried out for the sales and profit prediction and analysis by persons of different mindsets in case of strategic uncertainty . The paper by virtue of statistical and fuzzy logic based justifications has pointed out certain discovered facts in this perspective. The normal , optimistic , pessimistic and fickle-minded based individual mindsets significantly contribute to varying external analysis of business statistics.

statistical correlation fuzzy logic optimistic pessimistic fickle-minded business statistics

Abstract doi.org/10.14569/IJARAI.2014.030503 PDF

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