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SAARTHIAI: An Generative AI-Driven Adaptive Learning System for Personalized Professional Learning Plans
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 101 |
| Year of Publication: 2026 |
| Authors: Ashim Saha, Anshuman Laskar, Mainak Saha, Soumyajit Das, Rituraj Bhattacharjee |
10.5120/ijca9bc102a2c9e3
|
Ashim Saha, Anshuman Laskar, Mainak Saha, Soumyajit Das, Rituraj Bhattacharjee . SAARTHIAI: An Generative AI-Driven Adaptive Learning System for Personalized Professional Learning Plans. International Journal of Computer Applications. 187, 101 ( May 2026), 11-16. DOI=10.5120/ijca9bc102a2c9e3
Abstract
In today's rapidly evolving professional landscape, individuals must continuously update their skills to remain competitive. However, traditional educational systems and static e-learning platforms often fail to provide personalized learning paths tailored to each professional's goals, background, and pace. To address this challenge, we present SaarthiAI, an AI-driven adaptive learning system designed to generate customized professional learning plans and deliver targeted, interactive instruction. SaarthiAI integrates a Roadmap Generator leveraging retrieval-augmented generation (RAG) and dense vector retrieval via FAISS to construct personalized learning roadmaps from a knowledge base of industry-relevant content. It incorporates adaptive assessments powered by large language models to evaluate proficiency and dynamically adjust content difficulty. An AI Tutor chatbot module provides real-time contextual assistance and guidance. The system is implemented using Python, utilizing the Hugging Face Transformers library, MongoDB for data storage, and a RESTful API for seamless integration. Our contributions include the novel integration of RAG for roadmap generation, dynamic assessment mechanisms, and an interactive AI Tutor, collectively advancing personalized professional education.
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