Prediction of learning disorder: a-systematic review

Learning Disorder refers to a number of disorder which may influence the understanding or use of verbal or nonverbal information. The most well-known types of learning disorder involve an issue with reading, writing, listening, and speaking. When we talk about learning disorder, most people only...

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Main Authors: Jamhar, Mohammad Azli, Mat Surin, Ely Salwana, Zulkifli, Zahidah, Mat Nayan, Norshita, Abdullah, Noryusliza,
Format: Proceeding Paper
Language:English
English
Published: Springer Nature 2019
Subjects:
Online Access:http://irep.iium.edu.my/78332/
http://irep.iium.edu.my/78332/1/78332_Prediction%20of%20Learning%20Disorder_new.pdf
http://irep.iium.edu.my/78332/2/78332_Prediction%20of%20Learning%20Disorder_scopus.pdf
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author Jamhar, Mohammad Azli
Mat Surin, Ely Salwana
Zulkifli, Zahidah
Mat Nayan, Norshita
Abdullah, Noryusliza
,
author_facet Jamhar, Mohammad Azli
Mat Surin, Ely Salwana
Zulkifli, Zahidah
Mat Nayan, Norshita
Abdullah, Noryusliza
,
author_sort Jamhar, Mohammad Azli
building IIUM Repository
collection Online Access
description Learning Disorder refers to a number of disorder which may influence the understanding or use of verbal or nonverbal information. The most well-known types of learning disorder involve an issue with reading, writing, listening, and speaking. When we talk about learning disorder, most people only focusing on social development plan. Therefore, in this study, a systematic review was performed to identify, assess and aggregate on the prediction methods used for a predict learning disorder. The main objective of this paper is to, identify the most common prediction methods for learning disorder, in terms of accuracy by using the systematic review technique. From the main objective, we can define the research questions such as, which is the most common and the most accurate prediction methods used for learning disorder. In conclusion, the most common prediction methods for learning disorder which is Decision Tree and Support Vector Machine. For accuracy, Decision Tree, Linear Discriminant Analysis and K-Nearest Neighbor methods have the highest prediction accuracy for a learning disorder. From these findings, this paper can guide others to predict learning disorder by using the most common methods to get the best result in term of accuracy.
first_indexed 2025-11-14T17:43:15Z
format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T17:43:15Z
publishDate 2019
publisher Springer Nature
recordtype eprints
repository_type Digital Repository
spelling iium-783322020-07-14T01:24:17Z http://irep.iium.edu.my/78332/ Prediction of learning disorder: a-systematic review Jamhar, Mohammad Azli Mat Surin, Ely Salwana Zulkifli, Zahidah Mat Nayan, Norshita Abdullah, Noryusliza , T Technology (General) Learning Disorder refers to a number of disorder which may influence the understanding or use of verbal or nonverbal information. The most well-known types of learning disorder involve an issue with reading, writing, listening, and speaking. When we talk about learning disorder, most people only focusing on social development plan. Therefore, in this study, a systematic review was performed to identify, assess and aggregate on the prediction methods used for a predict learning disorder. The main objective of this paper is to, identify the most common prediction methods for learning disorder, in terms of accuracy by using the systematic review technique. From the main objective, we can define the research questions such as, which is the most common and the most accurate prediction methods used for learning disorder. In conclusion, the most common prediction methods for learning disorder which is Decision Tree and Support Vector Machine. For accuracy, Decision Tree, Linear Discriminant Analysis and K-Nearest Neighbor methods have the highest prediction accuracy for a learning disorder. From these findings, this paper can guide others to predict learning disorder by using the most common methods to get the best result in term of accuracy. Springer Nature 2019-11 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/78332/1/78332_Prediction%20of%20Learning%20Disorder_new.pdf application/pdf en http://irep.iium.edu.my/78332/2/78332_Prediction%20of%20Learning%20Disorder_scopus.pdf Jamhar, Mohammad Azli and Mat Surin, Ely Salwana and Zulkifli, Zahidah and Mat Nayan, Norshita and Abdullah, Noryusliza and UNSPECIFIED (2019) Prediction of learning disorder: a-systematic review. In: "6th International Conference on Advances in Visual Informatics, IVIC 2019", 19 - 21 Nov 2019, Bangi, Selangor. https://link.springer.com/chapter/10.1007%2F978-3-030-34032-2_38 10.1007/978-3-030-34032-2_38
spellingShingle T Technology (General)
Jamhar, Mohammad Azli
Mat Surin, Ely Salwana
Zulkifli, Zahidah
Mat Nayan, Norshita
Abdullah, Noryusliza
,
Prediction of learning disorder: a-systematic review
title Prediction of learning disorder: a-systematic review
title_full Prediction of learning disorder: a-systematic review
title_fullStr Prediction of learning disorder: a-systematic review
title_full_unstemmed Prediction of learning disorder: a-systematic review
title_short Prediction of learning disorder: a-systematic review
title_sort prediction of learning disorder: a-systematic review
topic T Technology (General)
url http://irep.iium.edu.my/78332/
http://irep.iium.edu.my/78332/
http://irep.iium.edu.my/78332/
http://irep.iium.edu.my/78332/1/78332_Prediction%20of%20Learning%20Disorder_new.pdf
http://irep.iium.edu.my/78332/2/78332_Prediction%20of%20Learning%20Disorder_scopus.pdf