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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| Main Authors: | , , |
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| Format: | Article |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/81133/ http://dx.doi.org/10.4314/jfas.v9i4S.34 |
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| Summary: | 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. |
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