Survey on different Machine Learning Techniques for Student Improvement using Psychometric Data

Abstract

Abstract: Student improvement aims in identifying student behavior traits and patterns using multiple psychometric tests followed by suggesting ways to improve areas of the subject’s interest along with overall psychological balance by continuous testing at constant intervals of time and suggesting the same. To identify the subject’s strengths, weaknesses, and behavioral interests, assessments are carried out on the principle of psychological assessments which aims to assess the students by making them imagine their reactions in various psychological situations. Each response to the question is evaluated with pre-decided scores. Psychometric tests are aimed at measuring a person’s traits, behavior, guidance, and placements/employment to match the person’s capabilities and features like cognitive ability, EQ, IQ, and the tendency to react to predefined situations. Psychometric tests have a huge role to play in the fields of career guidance and employability. These tests suggest your strengths, weaknesses, and imaginative abilities and hint if they suit the particular role. This paper provides a survey on different machine learning algorithms used over the years to recognize personality traits and learning styles which would further contribute to students’ overall improvement.