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Data Mining and Prediction Tools (for Predicting Stndents' Success in Programming Course)

Che Nordin, Che Sarah (2011) Data Mining and Prediction Tools (for Predicting Stndents' Success in Programming Course). Universiti Teknologi Petronas. (Unpublished)

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Abstract

This project addresses the importance of extraction and analysis of data from different types of educational settings such as computer-based or web-based educational system (i.e. course management system), classroom environment factors as well as psychosocial factors in the university, which can affect the students and use these data to foresee students' learning patterns. The vast amount of data from different educational settings can be fully utilized to predict the students' performance or a particular course. However, there is no tool as such, that can automatically manage, extract and analyze this kind of information. Besides that, most of the current data mining tools are too complex for educators to use and their features go well beyond the scope of what an educator might require. This project will use the data mining approach and techniques in analyzing different types of data gathered from different educational settings. The project aims to develop a new data mining and prediction tools, which will analyze different types of data coming from different educational settings to assist lecturer to predict students' performance in a programming course. The scope of study for this project is one of the programming courses m the university, Advanced Business Application Programming (ABAP) and the university's E-Learning System. The main contribution of this project is the development of a new data mining and analysis tools, that can produce prediction output to assist the lecturer in his or her decision making activities to improve the learning process in a particular programming course.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: T Technology > T Technology (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Users 2053 not found.
Date Deposited: 30 Sep 2013 16:19
Last Modified: 25 Jan 2017 09:42
URI: http://utpedia.utp.edu.my/id/eprint/7129

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