Prediction of Association among Numerical Aptitude, Programming Skills, Trait Emotional Intelligence on Students Performance

Identifying variables that predict programming skill may help educators and employers. The employer may select potential students as employees. These variables are influenced by various factors. This paper is an attempt to find these variables. The study evaluated the students on Numerical Aptitude, Object Oriented Programming skills and Trait Emotional Intelligence (TEI). This study also engages the factors like academics, locality and gender to find the skill set of the students in programming. The students were divided into five groups based on trait emotional intelligence variables using the Trait Emotional Intelligence Questionnaire (TEIQue). These variables are wellbeing, self-control, emotionality, sociability and global trait EI. Likert scale was used to measure the TEI factors. In order to explore the relation between these parameters two Data mining techniques (i) Association Rule Mining and (ii) Multilayer Perceptron were applied in the resultant data set. It was found that Strong Numerical knowledge helped the students to achieve higher scores in Programming. This analysis can be used by the educators to improve the students programming skills by improving their numerical ability. KeywordsAssociation Rule Mining, Multilayer Perceptron, TEI, Programming skills, Numerical aptitude.