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Shvoong Home>Science>Statistical Approach on Grading the Student Achievement via Mixture Modeling Summary

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Statistical Approach on Grading the Student Achievement via Mixture Modeling

Article Abstract by: fadzlina    

Original Authors: Zainul Nor Deana Md. Desa; Ismail Mohamad; Zarina Mohd. Khalid; Md. Hanafiah Mad Zin
The purpose of this study is to compare result obtained from three methods of assigning letter grades to students’ achievement. 
The conventional and the most popular to assign grades is the Straight Scale method (SS).  Statistical approaches which used the Standard Deviation (GC) and conditional Bayesian method are considered to assign the grades.  In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution.  The problem lies in estimating the posterior density of the parameters which is analytically intractable.  A solution to this problem is using the Markov Chain Monte Carlo approach namely Gibbs sampler algorithm.  The Straight Scale, Standard Deviation and Conditional Bayesian methods are applied to the examination raw scores of two sets of students.  The results showed that Conditional Bayesian out performed the Conventional Methods of assigning grades.
Published: April 13, 2007
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