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While academic metrics such as transcripts and GPA are commonly used toevaluate students' knowledge acquisition, there is a lack of comprehensivemetrics to measure their preparedness for the challenges of post-graduationlife. This research paper explores the impact of various factors on universitystudents' readiness for change and transition, with a focus on theirpreparedness for careers. The methodology employed in this study involvesdesigning a survey based on Paul J. Mayer's "The Balance Wheel" to capturestudents' sentiments on various life aspects, including satisfaction with theeducational process and expectations of salary. The collected data from a KBTUstudent survey (n=47) were processed through machine learning models: LinearRegression, Support Vector Regression (SVR), Random Forest Regression.Subsequently, an intelligent system was built using these models and fuzzysets. The system is capable of evaluating graduates' readiness for their futurecareers and demonstrates a high predictive power. The findings of this researchhave practical implications for educational institutions. Such an intelligentsystem can serve as a valuable tool for universities to assess and enhancestudents' preparedness for post-graduation challenges. By recognizing thefactors contributing to students' readiness for change, universities can refinecurricula and processes to better prepare students for their career journeys.

Intelligent System for Assessing University Student Personality Development and Career Readiness