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April 5, 20260 citationsOpen Access

An AI-Driven, Survey-Based Machine Learning Study on Employability Stress Among IT Students in Experience-Centric Job Markets.

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DVDevakar Vijay

Key Points

  • The research aims to analyze employability stress and challenges faced by IT students in job markets using AI.
  • Conducted a survey to collect data on skills, academic background, and career readiness
  • Applied machine learning models to identify patterns in employability and career risk levels
  • Developed a framework to provide insights for educational institutions and career advisors
  • Identified key factors influencing employability stress among IT students
  • Demonstrated the efficacy of machine learning in uncovering employment patterns
  • Provided actionable insights for designing skill development strategies

Abstract

This research proposes an AI and Machine Learning–based framework to analyze student employability challenges and career stress in the IT sector. A survey-based dataset was collected to evaluate skills, academic background, and career readiness of students. Machine learning models were applied to identify patterns influencing employment opportunities and career risk levels. The proposed system provides practical insights that can help educational institutions and career advisors design targeted skill development and support strategies for students entering the workforce.

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Cite This Study

Devakar Vijay (2026) studied this question.

synapsesocial.com/papers/69d1fe07a79560c99a0a476bhttps://doi.org/10.5281/zenodo.19397936
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An AI-Driven, Survey-Based Machine Learning Study on Employability Stress Among IT Students in Experience-Centric Job Markets.2026
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