An Automated personality classification based system for assisting in choosing a career using data mining techniques

Abstract

For successful career development in today’s world of work, the empowerment of individuals as autonomous decision-makers is fundamental. This empowerment aims to help individuals in the acquisition of decision-making skills when making transition decisions. A lack of self-awareness is a contributing factor as to why people land in the wrong career. After in-depth research, the researcher found out that deliberating individuals encounter countless challenges in the process of career decision making. After establishing that one’s personality can influence how one performs in the work place depending on the career they are in, the researcher sought to create self-awareness to individuals faced with the dilemma of choosing a career that they can thrive in best. To achieve this, the researcher has developed a web application that can automatically classify a person’s personality and recommend a career that fits their personality. To achieve its purpose, this study assumed a purposive sampling technique that drew at least 70 respondents based on two classes of participants. One class was composed of high school students and persons considering changing careers. To develop the web application, the researcher used Web Development Life Cycle (WDLC) methodology which combines the components of both Systems Development Life Cycle (SDLC) and Prototyping. WDLC contains two iterative steps of graphical development and functional development. This methodology was found efficient in reducing development time, accords more structure to the research problem and ensures user involvement throughout the development life cycle. From the study findings, it is evident that there is a strong relationship between personality and career choice and that a career recommendation system based on one’s personality can make career decision process manageable. This system will be helpful to learning institutions when advising students on career paths to pursue based on their personality type. The prediction of personality is based on MBTI 16 personality types and the data mining algorithm used for classification is K- Nearest Neighbour.