Analyzing Personality Traits and External Factors for Stem Education Awareness using Machine Learning

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.

@article{Suh2019,
  title     = {Analyzing Personality Traits and External Factors for Stem Education Awareness using Machine Learning},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {5},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Sang C Suh and Anusha Upadhyaya B.N and Ashwin Nadig N.V},
  doi       = {10.14569/IJACSA.2019.0100501},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100501}
}