Using Data Mining Techniques to Develop an Automated Personality Classification Based System for Assisting in Choosing a Career path
Personality is defined as the characteristics that make a person unique in terms of their way of thoughts, emotions, behaviours, habits and interests while influencing how one makes decisions in life. His personality determines every element of one’s career. Fundamental career decisions such as occupational choice, early-career socialization, job performance, career satisfaction and career changes are affected by one’s personality. Our personality influences our human relation skills which in turn allow us to better deal with situations and other people. According to Daniel (2004), Human relations and emotional intelligence, which are a corresponding part of one’s personality, determine excellent performance at work. In the workplace, one is likely to come across difficult bosses and colleagues who don’t enjoy working with or even turbulent personal relationships. The ability to handle these challenging situations will highly depend on one’s personality (Daniel, 2004). Even though choosing a career can prove to be a daunting task, having self-awareness can help one choose the occupation in which they best fit concerning their strengths and weaknesses. After one gets into the right job where they can blend well with the environment, they can improve their innate strengths.
John Holland’s theory is a prime example of person-occupation fit research; this theory examines the congruence between people’s career interests and occupational environments. People search for careers that match their interests; such a fit result in vocational stability, satisfaction, and high achievement. Poor fit results in the opposite patterns. Holland believes that these professional interests are a fundamental component of one’s personality (BROWN & LENT, 2005). One can only choose the right career if they can understand their personality and the work environment where they best fit.
Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information, which is collected and assembled in common areas for efficient analysis for purposes of decision making (Techopedia, 2017). Data mining techniques are classification, clustering, Regression, Association Rules, outer detection, sequential patterns and prediction. By grouping the different traits of persons from their behavioural data, I will be able to classify persons into different career groups based on their resultant personality. This will be achieved by the use of learning algorithms along with advanced data mining to mine user characteristics data and learn from the patterns. This learning can now be used to classify/predict user personality based on past classifications and point them towards the right career fit. The system will analyze vast user characteristics and behaviours, and based on the patterns observed, store its user characteristics patterns in a database. The system will then predict a new user personality based on personality data stored by classification of previous user data.
Objectives
- To analyze the relationship between personality and career success
- To review existing career recommendation systems and models
- To develop an automated personality classification system that can match given personality traits with a given vocation
- To validate the developed system
Research Questions
- How does personality influence career success?
- How do existing career recommendation systems perform?
- How can an automated personality classification system that can match given personality traits with a given vocation be developed?
- How can the developed system be validated?
References
- Goleman, D. (2004, January). What makes a leader? Harvard Business Review, accessed June 06, 2020, http://hbr.org/2004/01/what-makes-a-leader/ar/1
- BROWN, S. D., & LENT, R. W. (2005). CAREER DEVELOPMENT AND COUNSELING Putting Theory and Research to Work. Hoboken, New Jersey: John Wiley & Sons, Inc.,
- (2017, August 18). Retrieved from www.techopedia.com: https://www.techopedia.com/definition/1181/data-mining
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