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An Expert System for Automated Essay Scoring (AES) in Computing using Shallow NLP Techniques for Inferencing

by Abejide Olu Ade-ibijola, Ibiba Wakama, Juliet Chioma Amadi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 51 - Number 10
Year of Publication: 2012
Authors: Abejide Olu Ade-ibijola, Ibiba Wakama, Juliet Chioma Amadi
10.5120/8080-1480

Abejide Olu Ade-ibijola, Ibiba Wakama, Juliet Chioma Amadi . An Expert System for Automated Essay Scoring (AES) in Computing using Shallow NLP Techniques for Inferencing. International Journal of Computer Applications. 51, 10 ( August 2012), 37-45. DOI=10.5120/8080-1480

@article{ 10.5120/8080-1480,
author = { Abejide Olu Ade-ibijola, Ibiba Wakama, Juliet Chioma Amadi },
title = { An Expert System for Automated Essay Scoring (AES) in Computing using Shallow NLP Techniques for Inferencing },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 51 },
number = { 10 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 37-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume51/number10/8080-1480/ },
doi = { 10.5120/8080-1480 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:50:04.221673+05:30
%A Abejide Olu Ade-ibijola
%A Ibiba Wakama
%A Juliet Chioma Amadi
%T An Expert System for Automated Essay Scoring (AES) in Computing using Shallow NLP Techniques for Inferencing
%J International Journal of Computer Applications
%@ 0975-8887
%V 51
%N 10
%P 37-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present the report of the development of an Expert System (ES) that; acquires the knowledge of Subject Matter Experts (SMEs) in a specific computing field, "Software Engineering", uses a built-in Inference Engine designed with Shallow Natural Language Processing Techniques (Information Extraction using Tokenization, Statistical Keyword Analysis and Domain-Specific Dictionary) and a Fuzzy-Scoring Model to assess Students' Free-Text Answers to Open-Ended Questions and hence, computes the correctness of students' answers with respect to lecturers' underlying model answers or templates. The newly developed ES was adapted to an academic course in the University System and its performance was evaluated using certain Statistical Metrics. The results from the evaluation were compared with existing Automated Essay Scoring Systems (AESs) using certain thresholds and conclusions were drawn.

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Index Terms

Computer Science
Information Sciences

Keywords

Expert System Automated Essay Scoring (AES) Free Text Answers Open-Ended Questions Fuzzy-Scoring Model

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