Implementation of Diagnostic Methods of Career Guidance in Computer Systems

The purpose of the study is to analyze existing methods and systems of career guidance, evaluate their advantages and disadvantages, and propose our own solution to this problem, taking into account existing developments in this subject area. For people choosing a job, the issue of career guidance remains relevant, problematic, and not fully resolved. Graduates of secondary educational institutions have particular difficulties in choosing a profession and in choosing an appropriate educational institution due to their little life experience. Currently, a significant number of methods and computer systems have been developed for career guidance purposes. However, the recommendations of a consulting psychologist are still considered preferable. Meanwhile, modern computers can store and process a huge amount of diverse information about the respondent and professions, analyze the trends of the profession market. Therefore, the improvement of career guidance systems, endowing them with artificial intelligence seems promising.

Materials and methods. Information on the subject area was collected by studying artifacts. During the analysis of existing methods and systems of career guidance, the methods of classification and systematization, induction and deduction were used. The method of describing the norms and requirements for a candidate-specialist were job descriptions and lists of necessary competencies and contraindications to the profession. To identify an individual’s predisposition to a specific type of activity, methods were used to diagnose the interests, inclinations, capabilities, psychophysiological abilities of respondents, testing attention, intelligence, creativity, temperament, etc. The comparison of personal characteristics and requirements in the created system is carried out by means of production rules and a genetic algorithm. Among the advantages of genetic algorithms are conceptual simplicity and wide applicability, resistance to dynamic changes in the environment and the ability to self-organization. The developed career guidance system was subjected to experimental studies.

Results. A genetic algorithm has been developed in which information about professions and information about the respondent are taken as the initial information for creating a new population: a) his knowledge, skills and abilities; b) his desires, inclinations, personal qualities. Based on these data, the initial population of professions is formed. As a result of crossing a pair of individuals from the parent population, a descendant is obtained whose chromosome consists of the genes of both parents. The selection of surviving specimens is based on the percentage of success in the development of each of the professions in the list and the fitness function. The developed algorithm was implemented in a software system. As experiments showed, the genetic algorithm successfully copes with the task of finding the optimal list of professions according to a given criterion.

Conclusion. The results of the study show that the use of genetic algorithms provides convenient mechanisms for introducing artificial intelligence methods into the field of career guidance, which improves the quality of recommendations for choosing a profession.

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