Grading in academics
Over my past three years of academic life at IIT Kharagpur, I have observed that, for any particular subject, following parameters are considered.
- Theory Component (60%)
- Mid-Term Examination (30%)
- End-Term Examination (50%)
- Class Tests (10%)
- Teacher’s Assessment (10%)
- Laboratory Component(40%)
- Weekly Laboratory Assignments (60%)
- Experimental Examination (20%)
- Viva Voce (20%)
Following the above pattern, a student’s total score is calculated on a scale of 0-100, and based on this score, the following grades are alloted.
- Ex (90-100)
- A (80 – 89)
- B (70 – 79)
- C (60 – 69)
- D (50 – 59)
- P (35 – 49)
- F (<35)
- I (Incomplete)
To be honest, it feels bad when you get 89 and miss ‘Ex’ by just 1. But in reality, an 89 is as good as a 90. Isn’t it?
In this post, I present a fuzzy based grading system which I believe is quite logical and realistic.
For those of you who do not know what fuzzy logic is, here is an example. Suppose you are driving a car at 40 KMPH. You are driving neither fast nor slow. But you can give a rough estimate that the relationship of the speed of the car to the set ’slow speeds’ is around 30% and the speed of the car to the set ‘fast speeds’ is 40%. This estimate is called as “Association”. In this example, “the speed of the car” is considered to be a fuzzy variable and the sets “slow speeds” and “fast speeds” are the fuzzy sets.
Now you can construct some rules like:
- If the speed of the car is fast, then slow down.
- If the speed of the car is medium, then take no action.
- If the speed of the care is slow, then accelerate.
Hence, for a particular speed of the car, the truthness of all the above rules can be computed, and the rule which has the maximum truthness values is executed.
In the present context, I think that fuzzy logic can also be applied considering the fuzzy variables as “performance in examinations”, “attendance in classes”, “participation in group activities” etc. This might be a more rational system of grading.
Just a thought. 
