SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility
Jason Jabbour, Kai Kleinbard, Olivia Miller, Robert Haussman, Vijay, Janapa Reddi

TL;DR
SocratiQ is an AI-powered educational assistant that uses generative AI and the Socratic method to create personalized, adaptive learning experiences, aiming to improve accessibility and engagement in education.
Contribution
This paper introduces a novel generative AI framework for personalized education, detailing its system architecture, integration methodology, and evaluation, with a focus on machine learning education.
Findings
Effective personalized learning pathways generated dynamically
Successful integration of generative AI in educational systems
Addressed technical and pedagogical challenges in implementation
Abstract
Traditional educational approaches often struggle to provide personalized and interactive learning experiences on a scale. In this paper, we present SocratiQ, an AI-powered educational assistant that addresses this challenge by implementing the Socratic method through adaptive learning technologies. The system employs a novel Generative AI-based learning framework that dynamically creates personalized learning pathways based on student responses and comprehension patterns. We provide an account of our integration methodology, system architecture, and evaluation framework, along with the technical and pedagogical challenges encountered during implementation and our solutions. Although our implementation focuses on machine learning systems education, the integration approaches we present can inform similar efforts across STEM fields. Through this work, our goal is to advance the…
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Taxonomy
TopicsOnline Learning and Analytics
