Analytical Model for Developing Educational Programs Considering Kazakh IT Labour Demands and Student Performance Prediction

2025

Closed access Metadata (CSL-JSON)
DOI 10.1109/sist61657.2025.11139254
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This study proposes a method for developing IT education programs by integrating job market analysis with student performance prediction. Open-source tools collected and analyzed job postings from major Kazakh employment platforms, identifying in-demand skill and knowledge sets using fine-tuned a specialized LLM, that outperforms existing SOTA techniques. Predictive models assessed student performance to align curricula with both industry needs and learner capabilities. Based on this dual analysis, an educational program was designed for university students specializing in software development and system administration. By aligning coursework with labor market demands, the program enhances graduate employability and fosters career readiness in Kazakhstan’s evolving tech sector.