Skillforge: Skill-Based Adaptive Learning

Sandip Shinde; Rudra Mondal; Swami Patil; Anshu Pariharand; Swarup Patil

doi:10.2991/978-94-6463-858-5_89

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Skillforge: Skill-Based Adaptive Learning

Authors

Sandip Shinde¹^{, *}, Rudra Mondal¹, Swami Patil¹, Anshu Pariharand¹, Swarup Patil¹

¹Vishwakarma Institute of Technology, Upper Indiranagar, Bibwewadi, Pune, India

^*Corresponding author. Email: sandeep.shinde@vit.edu

Corresponding Author

Sandip Shinde

Available Online 4 November 2025.

DOI: 10.2991/978-94-6463-858-5_89 How to use a DOI?
Keywords: Personalized learning; skill assessment; course recommendation; AI-driven education; adaptive learning systems; interest-based learning; educational technology; domain-specific learning; knowledge evaluation; e-learning platforms
Abstract: Personalized learning is a critical need in today’s dynamic educational landscape, where learners require tailored pathways to develop skills effectively. This paper presents a web-based platform designed to assess users’ current skills and recommend courses aligned with their interests and career aspirations. The system utilizes an AI-driven skill evaluation mechanism to gauge users’ knowledge levels and maps their strengths and weaknesses to relevant domains. A recommendation engine then suggests targeted courses, ensuring the content matches the user’s skill level and future goals. By integrating user-provided skills, interests, and domain preferences, the platform enhances the learning experience and bridges skill gaps effectively. This system demonstrates significant potential to revolutionize skill-based learning and foster career development through adaptive, interest-driven education pathways.
Copyright: © 2025 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series: Advances in Computer Science Research
Publication Date: 4 November 2025
ISBN: 978-94-6463-858-5
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-858-5_89 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Sandip Shinde
AU  - Rudra Mondal
AU  - Swami Patil
AU  - Anshu Pariharand
AU  - Swarup Patil
PY  - 2025
DA  - 2025/11/04
TI  - Skillforge: Skill-Based Adaptive Learning
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1073
EP  - 1085
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_89
DO  - 10.2991/978-94-6463-858-5_89
ID  - Shinde2025
ER  -

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