Relative Grading: A True Representation of Student Performance
Every institution will seek to evaluate students in a manner that is fair, equitable, and based upon their representative performance.
While the concept of Absolute Grading is relevant and easily applicable when assessing a single examination, it becomes increasingly difficult to do so for multiple examinations.
This is simply because raw scores may not always be an accurate depiction of a student’s true performance.
Here is an example to illustrate our point:
Say that an Engineering student scores 69 on a science paper, 75 on a language paper, and 72 on a mathematics paper.
The class averages for each are 45, 70, and 85 respectively.
The question arises – which is the best score?
Is it the higher numerical score or the relatively higher performance?
If the university were to set its evaluation criteria as a ‘performance measure’, then the score indicating higher performance would be science – ‘69’.
This is because the student’s performance is being measured against the whole class.
But in order to get to such a conclusion, both exams need to be converted into a common denomination or placed upon a standard scale for comparison.
This is where normalizing the scores, and utilizing Relative Grading, comes in!
What is Relative Grading?
Ideally, the distribution of an individual student’s performance for all examinations should be equal.
Only then can evaluations be considered to be comparable.
Relative grading is a system of assessment where evaluators determine student grades by comparing them against those of their peers.
In this approach, the grades of an assessment are plotted on a ‘bell curve”.Camu can help you generate and do multiple iterations of the bell curve to achieve the desired output.
The examiner considers the highest score as the baseline and computes the other grades on the basis of this score.
How is Normalization leveraged?
As the discrepancies in performance evaluation increase, so does the impact on the student’s final grade or ranking.
So, it is critical that the distribution of individual student performance for all exams be equal, irrespective of differences in duration, faculty, teaching assistant, or other factors.
Normalization is a process to adjust values that are measured on different scales, to a notionally common scale.
It requires adjusting the examination means to be equal as well as their variances.
Below is one among the multiple ways we can achieve normalization in Camu
Camu provides a simple, straightforward, and seamless way of leveraging Normalization using the formulae:
Z = (X-M)/S
Z refers to the Z score (an individual’s performance relative to the population’s mean and variance).
M is the estimate of the population’s mean.
S is the estimate of the population’s standard deviation.
X is an individual score within the distribution having mean M and Variance S.
The designated user must simply follow a series of steps to convert raw scores into normal scores:
- Select ‘Normalization Type’
- Select ‘Normalization Value’
- Click on ‘Apply Normalization’
- View Relative Grading Curve
As you can see, the software guides users in a natural sequence.
With the help of Camu’s Relative Grading system, institutions can easily and quickly combat the challenge of disparity in grading assignments and examinations.
So, to summarise:
- Normalization is used to adjust values that are measured on different scales to a notionally common scale, in order to create parity between two or more examinations.
- Normalization uses a fool-proof formula for evaluating the score.
- Camu enables users to leverage Normalization, and generate detailed reports, in a speedy, convenient, and reliable manner.
To know about this grading system, and how it can specifically benefit your institute, do reach out to our customer service team at [email protected]
