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Faculty of Computing and Information Technology
Document Details
Document Type
:
Article In Conference
Document Title
:
AACWELS: Automated “Adaptive Content” Web Based E-learning System For Teaching AI
نظام تعليم الكتروني عبر الإنترنت لتعليم الذكاء الإصطناعي يتميز بأتمتة المحتوى التكيفي
Subject
:
Web Adaptive E-learning
Document Language
:
English
Abstract
:
Nowadays, web-based education is reaching a large number of learners through the internet. It poses a valuable advantage over traditional classroom teaching. Recently however, many researchers agree on the fact that learning materials shouldn’t just reflect the teacher’s style only, but they should also be designed to satisfy learning needs for all kinds of students and all kind of learning styles. This process still raises, some problems need to be solved, among which matching suitable teaching contents with the student's learning style. In this paper, we propose a design and implementation of an Automated Adaptive Content Web based E-Learning System (AACWELS) for teaching AI subjects. The system uses an adaptive course content taxonomy based on a modified Felder's questionnaire depending on the learning styles properties used by Honey and Mumford. The proposed model tends to pursue adaptation according to obtained user profile. The lesson content is tailored to individual users, taking into consideration a specific learning style and subject matter learning motivation. These guidelines are based on pedagogical strategy and motivation factor with a strong psychological background. A demonstration of this system is available at the site http://www.aicurriculum.org. System performance results show that the system is scalable, and students are able to learn and to efficiently improve their learning process with such methodology, hence improving their learning gain.
Conference Name
:
Econf3
Publishing Year
:
1431 AH
2010 AD
Article Type
:
Article
Conference Place
:
Bahrain
Added Date
:
Monday, May 30, 2011
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
عبد الحميد رجب
Ragab, Abdul Hamid
Researcher
Doctorate
أبو بكر باجنيد
Bajnaid, Abubakr
Researcher
Doctorate
Files
File Name
Type
Description
29815.docx
docx
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