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DEBII Candidacy Presentation by Anhar Fazal?

Digital Ecosystem and Business intelligence (DEBII)Institute

Master candidacy
A Robust Methodology for Automated Grading of Essays

Anhar Fazal?

Supervisor: Dr Maja Hadzic
Co-Supervisor: Dr Fedja Hadzic
Co- Supervisor Assistant: Dr Russel D’Souza
Chairperson: Professor Tharam Dillon

Venue and Time

Date: Tuesday, 22 June 2010
Time: 11:00 AM-12:00 PM (GMT+08:00) Perth.
Location: DEBII Board Room Enterprise Unit 4, De Laeter Way, Techpark
 

Abstract

The Aim of our research is to propose a Neural Network based Hybrid model of an Automated Essay Grading system that uses a combination of Natural Language Processing (NLP) techniques and intelligent techniques to grade essays.

Essay grading is an essential part of every teacher’s job and a time-consuming activity, proving to be an expensive task for the government. Given the increasing number of students every year, the essay grading process becomes monotonous and onerous for the teacher, resulting in inefficiency and inaccuracy during the grading process. An automatic essay grading (AEG) system will be most desirable in such a scenario to reduce the teacher’s marking time, thus improving efficiency and also, resulting in saving tax-payer’s money. For over forty years, several AEG systems have been proposed each with its own advantages and disadvantages. However all of these approaches fail to model an essential aspect of grading essays, that is to model the non-linear nature of relationship between the feature vector of the essay and the essay grade. To overcome this drawback, we propose an intelligent AEG system that will grade essays in real time.
 

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