Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc
Data pre-processing is a crucial phase prior to analytic task and yet rarely been discussed especially for e-learning data which has multilevel data. Providing a reliable data pre-processing is important to provide quality dataset. Therefore, this study investigates the problems arise in data pre-pr...
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my.utm.811332019-07-24T03:34:40Z http://eprints.utm.my/id/eprint/81133/ Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc Mohamad, N. Ahmad, N. B. Sulaiman, S. QA75 Electronic computers. Computer science Data pre-processing is a crucial phase prior to analytic task and yet rarely been discussed especially for e-learning data which has multilevel data. Providing a reliable data pre-processing is important to provide quality dataset. Therefore, this study investigates the problems arise in data pre-processing and in this case, for identifying the significant factors to implement prediction task. A MOOC dataset is selected for the data pre-processing task. The process in generating the summary of dataset is explained and the ultimate aim is to produce a dataset with features that are ready for data mining task. The study also proposed a process model and suggestions, which can be applied to support more comprehensible tools for educational domain who is the end user. Subsequently, the data pre-processing become more efficient for predicting student’s retention in MOOC. 2017 Article PeerReviewed Mohamad, N. and Ahmad, N. B. and Sulaiman, S. (2017) Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc. Journal of Fundamental and Applied Sciences, 9 . pp. 598-613. ISSN 1112-9867 http://dx.doi.org/10.4314/jfas.v9i4S.34 DOI:10.4314/jfas.v9i4S.34 |
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QA75 Electronic computers. Computer science Mohamad, N. Ahmad, N. B. Sulaiman, S. Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
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Data pre-processing is a crucial phase prior to analytic task and yet rarely been discussed especially for e-learning data which has multilevel data. Providing a reliable data pre-processing is important to provide quality dataset. Therefore, this study investigates the problems arise in data pre-processing and in this case, for identifying the significant factors to implement prediction task. A MOOC dataset is selected for the data pre-processing task. The process in generating the summary of dataset is explained and the ultimate aim is to produce a dataset with features that are ready for data mining task. The study also proposed a process model and suggestions, which can be applied to support more comprehensible tools for educational domain who is the end user. Subsequently, the data pre-processing become more efficient for predicting student’s retention in MOOC. |
format |
Article |
author |
Mohamad, N. Ahmad, N. B. Sulaiman, S. |
author_facet |
Mohamad, N. Ahmad, N. B. Sulaiman, S. |
author_sort |
Mohamad, N. |
title |
Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
title_short |
Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
title_full |
Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
title_fullStr |
Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
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Data Pre-Processing: a Case Study in Predicting Student's Retention in Mooc |
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data pre-processing: a case study in predicting student's retention in mooc |
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2017 |
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http://eprints.utm.my/id/eprint/81133/ http://dx.doi.org/10.4314/jfas.v9i4S.34 |
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1643658620243542016 |
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