AUTOMATED PERSONALITY TESTING BASED ON JUNG’S AND REININ’S PSYCHOLOGICAL MODELS

 Introduction. Modern psychological assessment methods are essential tools in a wide range of fields, including education, recruitment, healthcare, military applications, and crisis management. One of the most prominent frameworks for personality typology is the model proposed by Carl Jung and later expanded by Aleksandr Reinin. These typologies offer a structured approach to understanding individual differences in cognition, behavior, and interpersonal interaction. However, the practical use of such methods often relies on manual processing and expert interpretation, which can be time-consuming and prone to subjectivity. As demand increases for rapid and accurate personality assessments in both individual and organizational contexts, automation presents a valuable solution for enhancing consistency, objectivity, and scalability.Objective. The primary objective of this study is to develop a comprehensive software system that automates the process of determining an individual’s psychological type based on the typologies of Jung and Reinin. The aim is to eliminate reliance on subjective evaluation by using deterministic algorithms and formalized mathematical models that interpret test responses with precision and repeatability.Methods. The methodology involves encoding psychological typologies into a set of quantifiable parameters. Each test question is mapped to specific personality traits and assigned numerical values representing the strength of the expressed feature. These values are then processed using weighted summation and normalized to ensure comparability across different traits and users. Reinin traits are derived through the application of logical functions that analyze complex patterns in user responses. The final personality profile is constructed as a multidimensional vector, which is then compared against a database of standardized type templates using Euclidean distance metrics to identify the closest match. The implementation was carried out in Python, employing the Tkinter library for the graphical user interface, SQLite for data management, and Openpyxl for exporting results in Excel format.Results. The developed system provides users with an intuitive interface for completing tests and receiving results. Automated analysis eliminates the need for manual intervention, ensuring reliability and consistency of outcomes. Throughout the development and testing phases, the system demonstrated high operational stability, classification accuracy and was positively received by users. The formalization of typological models ensures transparency in how results are generated and interpreted, which enhances the objectivity of the diagnostic process.Conclusion. The developed software system contributes to the modernization of psychological testing by introducing a deterministic and mathematically grounded approach to personality type assessment. It addresses key limitations of traditional manual testing and provides a robust platform for practical application in educational settings, professional counseling, personnel development, and beyond. By leveraging algorithmic processing and structured data analysis, the system delivers fast, reproducible, and interpretable results. Furthermore, future developments include the integration of Big Five-type models and the use of machine learning to enhance adaptability and personalization.Overall, the solution offers a reliable and efficient method for psychological diagnostics that aligns with contemporary demands for digital tools in human assessment.