DATA CLEANING FOR THE EVALUATION OF VIRTUAL LEARNING ENVIRONMENT SUCCESS AMONG TEACHERS

Authors

  • Hapini Awang Universiti Utara Malaysia (UUM)
  • Zahurin Mat Aji Universiti Utara Malaysia (UUM)
  • Wan Rozaini Sheik Osman Universiti Utara Malaysia (UUM)

Keywords:

Data Cleaning, Data Preparation, Data Screening, E-Learning, Information System Success, Virtual Learning Environments

Abstract

This article explains the data cleaning procedures for the evaluation of Virtual Learning Environment (VLE) success among Malaysian teachers. Data cleaning is essential step in any research to ensure that the produced data is usable, valid and reliable for testing the research framework. The data collection of this study was done among the teachers across four states of Perlis, Kedah, Penang and Perak. During the data cleaning procedures, seven main issues have been considered which include missing data, outliers, linearity, normality, homoscedasticity, multicollinearity and common method variance. As a result, a dataset consists of 643 good attributes’ cases were produced. All the assumptions for multivariate analysis had been met. Besides, this dataset has been proved to be robust and ready for further statistical examinations

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Published

2018-07-02

How to Cite

Hapini Awang, Zahurin Mat Aji, & Wan Rozaini Sheik Osman. (2018). DATA CLEANING FOR THE EVALUATION OF VIRTUAL LEARNING ENVIRONMENT SUCCESS AMONG TEACHERS. JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM), 3(8), 57–66. Retrieved from https://gaexcellence.com/jistm/article/view/1043

Issue

Vol. 3 No. 8 (2018): Volume_ 3 Issues_ 8 [June, 2018]

Section

Articles