Data mining and discovery for structured English questions
The English Examination is one of the core subjects students must take in Singapore throughout their primary and secondary education. In an English examination, there are several topics including oral, situational writing, vocabulary, cloze passages, comprehension and many more. Besides English, pri...
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2014
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sg-ntu-dr.10356-589812023-03-03T20:39:31Z Data mining and discovery for structured English questions S Shalini Menon Hui Siu Cheung School of Computer Engineering DRNTU::Engineering::Computer science and engineering The English Examination is one of the core subjects students must take in Singapore throughout their primary and secondary education. In an English examination, there are several topics including oral, situational writing, vocabulary, cloze passages, comprehension and many more. Besides English, primary school students have three other core subjects to study for. Due to the limited time and with so many topics and subjects to focus on, students and educators are often trying to find faster and efficient ways to improve learning and to better prepare for the examinations. Even though there are many online learning sites and assessment books available, very few of these actually provide focus areas and help students and educators identify topic trends and important concepts to improve learning. Therefore, this project aims to build an online learning system called ‘English Analyzer’ that will aid students in the learning process and to help them prepare efficiently for the Primary School Leaving Examination in English. The system provides several features such Subtopic Trend, Subtopic Distribution, Concept Trend, Exercises, View Papers and many more. With these, students will be able to better use their time while revising smart. A user evaluation was carried out at the end to rate the usefulness of each feature and the system as a whole. Finally, the project was concluded with a discussion of the overall system as well as recommendations for future works in order to improve the system. Bachelor of Engineering (Computer Science) 2014-04-17T08:37:04Z 2014-04-17T08:37:04Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/58981 en Nanyang Technological University 169 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering S Shalini Menon Data mining and discovery for structured English questions |
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The English Examination is one of the core subjects students must take in Singapore throughout their primary and secondary education. In an English examination, there are several topics including oral, situational writing, vocabulary, cloze passages, comprehension and many more. Besides English, primary school students have three other core subjects to study for.
Due to the limited time and with so many topics and subjects to focus on, students and educators are often trying to find faster and efficient ways to improve learning and to better prepare for the examinations. Even though there are many online learning sites and assessment books available, very few of these actually provide focus areas and help students and educators identify topic trends and important concepts to improve learning.
Therefore, this project aims to build an online learning system called ‘English Analyzer’ that will aid students in the learning process and to help them prepare efficiently for the Primary School Leaving Examination in English. The system provides several features such Subtopic Trend, Subtopic Distribution, Concept Trend, Exercises, View Papers and many more. With these, students will be able to better use their time while revising smart.
A user evaluation was carried out at the end to rate the usefulness of each feature and the system as a whole. Finally, the project was concluded with a discussion of the overall system as well as recommendations for future works in order to improve the system. |
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Hui Siu Cheung |
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Hui Siu Cheung S Shalini Menon |
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Final Year Project |
author |
S Shalini Menon |
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S Shalini Menon |
title |
Data mining and discovery for structured English questions |
title_short |
Data mining and discovery for structured English questions |
title_full |
Data mining and discovery for structured English questions |
title_fullStr |
Data mining and discovery for structured English questions |
title_full_unstemmed |
Data mining and discovery for structured English questions |
title_sort |
data mining and discovery for structured english questions |
publishDate |
2014 |
url |
http://hdl.handle.net/10356/58981 |
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1759857616111009792 |