Paper 1: Analyzing Personality Traits and External Factors for Stem Education Awareness using Machine Learning
Abstract: The purpose of the paper is to present the personality traits and the factors that influence a student to pursue STEM education using machine learning techniques. STEM courses have high regard because they play a vital role in global technology, inventions and the economy. Educational Data Mining helps us to identify patterns and relationships in a large educational database. On the other hand, Machine Learning facilitates decision making process by enabling learning from the dataset. A survey comprising of an extensive variety of questions regarding STEM education was conducted and the opinions of students from various backgrounds and disciplines were collected. A dataset was generated based on the responses from students. Machine Learning algorithms (one class-SVM and KNN) applied on this dataset emphasizes variety of courses offered, research-oriented learning, problem-solving approach, a good career with high paying job are some of the factors which may influence a student to choose STEM course.
Keywords: Educational Data Mining (EDM); Science Technology Engineering Management (STEM); Machine Learning (ML); K-Nearest Neighbor (KNN); One class–Support Vector Machine (one class - SVM)