Intelligent System for Assessing University Student Personality Development and Career Readiness

TL;DR

This work addresses the lack of robust metrics for university students' career readiness by integrating Paul J. Meyer's Balance Wheel with a fuzzy-logic–augmented machine-learning pipeline. It collects survey data from 47 students, trains Linear Regression, SVR, and Random Forest models, and applies a fuzzy post-processing step to categorize readiness into qualitative levels, achieving an accuracy of 0.8125. The strongest performer was Linear Regression, indicating a reliable, interpretable link between selected Balance Wheel features and openness to new career opportunities. The study demonstrates a practical, scalable approach for universities to monitor and improve students' preparation for post-graduate life and career transitions, with plans to extend the dataset to larger cohorts.

Abstract

While academic metrics such as transcripts and GPA are commonly used to evaluate students' knowledge acquisition, there is a lack of comprehensive metrics to measure their preparedness for the challenges of post-graduation life. This research paper explores the impact of various factors on university students' readiness for change and transition, with a focus on their preparedness for careers. The methodology employed in this study involves designing a survey based on Paul J. Mayer's "The Balance Wheel" to capture students' sentiments on various life aspects, including satisfaction with the educational process and expectations of salary. The collected data from a KBTU student survey (n=47) were processed through machine learning models: Linear Regression, Support Vector Regression (SVR), Random Forest Regression. Subsequently, an intelligent system was built using these models and fuzzy sets. The system is capable of evaluating graduates' readiness for their future careers and demonstrates a high predictive power. The findings of this research have practical implications for educational institutions. Such an intelligent system can serve as a valuable tool for universities to assess and enhance students' preparedness for post-graduation challenges. By recognizing the factors contributing to students' readiness for change, universities can refine curricula and processes to better prepare students for their career journeys.

Figures (6)

• Figure 1: Paul J. Meyer's "Balance Wheel" technique results.
• Figure 2: Proposed Methodology
• Figure 3: Sorted by descending order
• Figure 4: Heatmap of correlation between data
• Figure 5: Overlay distribution plot of survey responses