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Internship Portals: A Systematic Review of Current Platforms and Future Directions

Authors

Pranali Chipade

Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagur (IN)

Himanshu Taiwade

Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagur (IN)

Disha Channawar

Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagur (IN)

Isha Baghele

Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagur (IN)

Payal Gautam

Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagur (IN)

Article Information

DOI: 10.51583/IJLTEMAS.2026.150100002

Subject Category: Online internship portals , Web-based systems , Intelligent matching (AI/ML concepts), Educational platforms

Volume/Issue: 15/1 | Page No: 9-14

Publication Timeline

Submitted: 2026-01-22

Published: 2026-01-21

Abstract

This review's main contribution is the identification of research gaps and new trends, such as virtual internship models, secure verification frameworks, and AI-driven recommendation systems.by giving students, employers, and educational institutions a common digital platform, internship portals are crucial in bridging the gap between academic learning and real world industry experience. Online internship platforms have received a lot of attention lately due to the growing need for remote internship opportunities and skill-based employability. The functionality, efficacy, and limitations of online internship portals are the main topics of this paper's systematic review of the literature. The review examines research papers from academic databases like IEEE Xplore, Scopus, and Google Scholar that were published between 2020 and 2024. This review offers a comprehensive analysis of platform features, security and verification issues, and the function of intelligent matching mechanisms, in contrast to previous surveys that primarily concentrate on usability or employability outcomes. Common drawbacks identified by the study include limited integration with academic institutions, inadequate verification of internship postings, a lack of personalized recommendations, and data privacy issues.

Keywords

Internship portals, systematic review, online internships, employability, AI-based recommendations, virtual internships

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References

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