Development of a software and information system for testing the emotional sphere of a person

The purpose of the research is to develop a software and information system for automating the assessment of cognitive abilities of employees and candidates using scientifically validated testing methodologies in HR departments.

Methods. To implement the software system, the C# programming language was used with the ASP.NET Core framework, along with JavaScript and the React library. For storing data on users, testing results, and reports, the MSSQL database was utilized. The following scientifically validated methodologies were employed: "Schulte Tables" (G. Schulte) to measure attention concentration, "Pair Word Memorization Method" (H. Ebbinghaus) to assess shortterm memory, "Raven's Progressive Matrices" (J. Raven) to analyze logical thinking, "Holmes and Rahe Stress Scale" (T. Holmes, R. Rahe) to evaluate stress resilience, and "Belbin's Methodology" (R. M. Belbin) to determine team roles. The system uses test results as input data, which are subsequently analyzed to generate reports and provide recommendations.

Results. During the development, a software and information system was created to automate the process of assessing cognitive abilities of employees and candidates. Interfaces for users and HR specialists were implemented, providing access to tests, results, and analytics. Testing on a sample of company employees demonstrated a diagnostic accuracy level of 93%. The system offers personalized and group analysis capabilities, including generating recommendations for skill development and building summary reports, making it an effective tool for HR departments. The testing results showed that the developed software fully meets functional requirements and is ready for use.

Conclusion. The developed software and information system enables the automation of cognitive testing processes for employees and candidates, providing HR departments with a convenient tool for evaluating key skills and developing development plans. The system ensures high diagnostic accuracy and saves specialists’ time through automated data processing. Future development prospects include expanding functionality, adding new testing methodologies, implementing adaptive algorithms for dynamically adjusting task complexity, and integrating with HRM systems to optimize personnel management processes.

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