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April 14, 20260 citationsOpen Access

"An XAI-Powered System for Career Path Recommendation and Skill Gap Analysis"

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YMYasmine MohammadTBTarek Barhoum

Key Points

  • The aim is to create a decision-support system that connects educational outcomes with labor market requirements.
  • Developed a decision-support system using Explainable Artificial Intelligence (XAI) frameworks.
  • Utilized SHAP and LIME for transparent decision-making.
  • Employed a Flutter-based front-end and FastAPI for back-end functionalities.
  • Integrated an NLP-driven machine learning engine for multi-label classification.
  • Provided data-driven career path recommendations for students.
  • Identified skill gaps between academic curricula and industry requirements.
  • Mapped student profiles to evolving job market demands.

Abstract

This project introduces an intelligent decision-support system designed to bridge the gap between academic curricula and the evolving demands of the global labor market. Leveraging Explainable Artificial Intelligence (XAI) frameworks, specifically SHAP and LIME, the system provides transparent, data-driven career path recommendations. By analyzing skill gaps and mapping student profiles to industry requirements, the system ensures that graduates have a clear professional compass. The technical stack includes a Flutter-based front-end, FastAPI for the back-end, and a robust NLP-driven machine learning engine for multi-label classification. This work was conducted at Arab International University (AIU), Syria. The official website of the university is: https://www.aiu.edu.sy This work is licensed under CC BY 4.0

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Cite This Study

Mohammad et al. (2026) studied this question.

synapsesocial.com/papers/69ddda0de195c95cdefd78d0https://doi.org/10.5281/zenodo.19544766
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