Table 1 Subject and question-category breakdown and accuracy measure using ChatGPT (C: Correct, T: Total, A: Accuracy (%)).
MCQ | Numerical | Theory | SW accuracy (%) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
Subject | C | T | A | C | T | A | C | T | A | |
Fluid mechanics | 38 | 75 | 50.61 | 15 | 75 | 20.00 | 15 | 18 | 83.33 | 40.48 |
Thermodynamics | 39 | 75 | 52.00 | 14 | 75 | 18.67 | 14 | 17 | 82.35 | 40.12 |
Heat transfer | 44 | 75 | 58.67 | 20 | 75 | 26.67 | 13 | 15 | 86.66 | 46.66 |
Production engineering | 27 | 57 | 47.37 | 8 | 21 | 38.10 | 18 | 22 | 81.81 | 53.00 |
Manufacturing processes | 25 | 60 | 41.67 | 2 | 19 | 10.52 | 18 | 21 | 85.71 | 45.00 |
Kinematics & dynamics of machines | 12 | 30 | 40.00 | 1 | 1 | 100 | 15 | 19 | 78.95 | 56.00 |
Statistical mechanics | 14 | 25 | 56.00 | 4 | 5 | 80.00 | 17 | 20 | 85.00 | 70.00 |
Category-wise accuracy (%) | 50.13 | 23.62 | 83.33 | 46.63 | ||||||
