Development of an automated essay scoring system over the web
This report narrates the development of Automated Essay Scoring (AES) system over the web. AES is the use of specialized computer programs to recognize and grades to written essays in an educational setting. The criteria for an AES to be recognized as a valid system are the method of assessmen...
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Format: | Final Year Project |
Language: | English |
Published: |
2018
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Online Access: | http://hdl.handle.net/10356/74222 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | This report narrates the development of Automated Essay Scoring (AES)
system over the web. AES is the use of specialized computer programs to
recognize and grades to written essays in an educational setting. The criteria
for an AES to be recognized as a valid system are the method of assessment
must be judged on validity, fairness, and reliability.
There are many different approaches to design an AES model,
however among the variety of methods, there is an approach, namely Gated
Convolutional Neural Network (Gated-CNN) [1] which incorporates both
character and word information into neural-network model that outperform the
other state-of-the-art models on the Kaggle’s Automated Student Assessment
Prize (ASAP) dataset [2]. However, marking an essay usually consists of
different kinds of aspects, such as grammar usage, content relatedness,
vocabulary spelling and others. Thus, it is essential to investigate the
evaluation criteria of Gated-CNN. Experiments conducted and results are
reported in the early part of this report.
The details about the web AES system implementation are reported in
the latter part of this report. It describes the perspective, architecture, and
features of the web AES system. |
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