STUDENT ACADEMIC SKILL AND CAREER PREDICTION USING MACHINE LEARNING

Abstract

An important aspect of any educational institution is the academic performance of the students. Various factors can affect the academic performance of students. Understanding the performance of a student is beneficial to both the student and the educational institution. Most educators know that grades are an important perfor mance indicator when it comes to monitoring the academic performance of students. Using artificial intelligence and machine learning, this work aims to predict students’ careers based on their academic data. In particular, it helps calculate students’ grades for their different skills by analysing patterns in the academic data of technical courses. In this work, the academic grades and career of different students/subjects are collected and using regression models, these grades are assigned to six skill sets such as analytical skills, design skills, memory skills, numerical skills, presentation skills and programming skills. Based on these skills, different classifiers is implemented to predict the students’ career. Linear Regression Regressor for skill prediction and Random Forest classifier for career prediction provide the best prediction performance, with accuracy scores of 0.999 and 0.962, respectively. So this work helps to calculate students’ career for their different skills by analysing trends in large academic data of technical courses using artificial intelligence and machine learning.