In this competetive world, students need to keep pace with the current education system. Parents/Teachers keep an intervention of students after seeing the results mainly during the parent teachers meet. Many a times these manual intervenetions can become unnecessary if the elders only focus on absolute performance , whereas maybe the child might have done pretty well relatively. Also the socio-economic factors of the child plays a lot of role on his/her performance. The parents might not consider the childs overall emotional state and might set up an intervention straight up on analysing the poor results.
Our ML model considers various socio-economic factors for predicting the child's final sem grades namely : Family size, Father's job, Drug/Alcohol intake, Freetime, Health Status among various other 31 parameters. The predicted score is then compared with the original score of the student as evaluated by the fuzzy inference system. The fuzzy expert system was carefully designed by doing simulations for a wide variety of data in matlab and was implemented in software using Java. The predicted score and the fuzzy score is actually compared to assess the students final performance.
- ML Model - Keras API (tensorflow Backend) , Anaconda Environment
- Matlab , j-Fuzzy Logic
- JSP(Java Server Pages), Flask for Rest API