A Readiness-Aware Internship Recommendation and Skill-Gap Analysis System for Students

Students today have access to so many internship listings than ever, spread across various internship-search platforms, college placement portals, company career pages, government-run schemes.Yet most of these platforms focus primarily on matching and ranking opportunities, while providing limited support for understanding whether a student is actually eligible, which specific requirements they do not satisfy, and what skills they could improve.This paper proposes a conceptual architecture for a readiness-aware internship recommendation and skill-gap analysis system for students.The proposed design compares a student's education, skills, experience, and preferences against internship requirements and extends conventional matching by identifying satisfied and unsatisfied eligibility conditions and highlighting specific skill gaps.Rather than presenting a system that has already been implemented and empirically validated, this paper defines its conceptual architecture, data flow, processing stages, and reasoning logic as a theoretical foundation for future implementation and empirical evaluation.The proposed framework is situated within gaps identified across internship recommendation, explainable matching, and skill-gap analysis research.The architecture therefore provides a basis for future investigation into whether presenting readiness and skillgap information alongside internship recommendations can help students better understand requirements and make more informed application decisions.