Informatics Publishing Limited

V. Maria Antoniate Martin ¹, M. Edison ², George Gabriel Richard Roy ¹

Affiliations
1 Department of Information Technology, St. Joseph's College (Autonomous), Tiruchirappalli, Tamil Nadu, IN
2 Department of Computer Science, St. Joseph's College (Autonomous), Tiruchirappalli, Tamil Nadu, IN

Abstract

Data mining is used to extract meaningful patterns, interesting patterns from databases or repositories. The aim of this study is to find the relation between the personality of an individual and the trait emotional intelligence ('trait EI') based on the academic performance of the individual, this study also involves of how a student will perform academically in accordance to the factors like locality and gender. Using the Trait Emotional Intelligence Questionnaire (TEIQue) the students were divided into five trait emotional intelligence (EI) variables (wellbeing, self-control, emotionality, sociability, and global trait EI), then their personalities were categorized under extraversion, neuroticism and psychoticism using the Eynseck Personality Questionnaire (EPQ). Data mining techniques, Association Rule Mining and Multilayer Perceptron were applied to the resultant data set. This study was conducted to provideinsight of how the students will perform academically and non-academically, based on their TEI and Personality Traits. This analysis can be used to help the students know about their standing and what could be done to improve themselves. It was found that students who scored high in trait EI and those who had high personality trait scores performed well academically, like wise students from rural areas and male students who had high Trait EI scores achieved well academically.

Keywords

Data Mining, Association Rule Mining, TEI, Personality, Multilayer Perceptron, EPQ, TEIQue.

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A. Aloysius ¹, M. Edison ²

Affiliations
1 St. Joseph’s College (Autonomous), Tiruchirappalli, Tamilnadu, IN
2 Department of Computer Science, St. Joseph’s College (Autonomous), Tiruchirappalli, Tamilnadu, IN

Abstract

There is a lack of measuring techniques in the field of software engineering when compared to the other engineering disciplines. The core focus of the software developers is to reduce the complexity of the software developed. The interest in cognitive methods and techniques has grown to be a great aid in software development. The aim of this paper is to perform a study on a set of students to test/measure their debugging capabilities based on their emotional quotient. These innovative techniques are on the verge of becoming main stream to adapt to measure newer technologies, while newer technologies emerge researchers invent newer methods to measure the complexity of software development. The Pearson correlation statistical method is used to analyze the outcome pertaining to the EQ of the students and their debugging capabilities to derive the result. Debugging capabilities of programmers tend to differ according to their emotional levels, debugging of programs using Component Based Systems and the Emotional Quotient’s (EQ) relation is studied and experiments are conducted to evaluate various emotional and stress levels in correspondence to specific debugging capabilities of the programmer in subject to different technologies. From this study it is found that the student’s ability to debug a piece of code drastically differs based on his/her emotional quotient.

Keywords

Cognitive Science, Eq, Debugging, Statistical Test, Component Based Programming.

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