ABSTRACT
The process of career choice is a critical task with substantial consequences for individuals' future career paths. The conventional career counseling process consists of meetings with counselors, tests of abilities, and hand-evaluation, and may be cumbersome, biased, and not feasible for a large proportion of jobseekers and students. With the growth of artificial intelligence (AI) in the last few years, computer-aided career counseling systems with machine learning and data-driven methods have been established, leveraging data and machine learning for individualized career suggestions.
This research effort targets the establishment of a career counseling tool with recommendations made via artificial intelligence. The tool will aggregate user data including academic history, personality, likes, and values of parents and use them for generating personalized career recommendations. Using machine learning methods and real-time data, the system provides precise, unbiased, and real-time career counseling. The tool also has real-time human counselor consultations, therefore, integrating a hybrid strategy for career decision.
The research process will be conducted with the use of HTML, CSS, PHP and other related technologies for the front-end, and AI algorithmic techniques will be employed for evaluating user input and suggesting career recommendations. The performance of the system will be gauged on its accuracy, user satisfaction, and its overall effectiveness in assisting career choice.
This study contributes to the burgeoning research on the use of AI in career and study counseling with its presentation of a data-driven, scalable, and user-centered solution for career counseling. The research will inform career and study counseling with data-driven, scalable, and user-centered solutions and, in the process, decrease reliance on traditional career counseling practices.
