PAPPL: Personalized AI-Powered Progressive Learning Platform
Shayan Bafandkar, Sungyong Chung, Homa Khosravian, Alireza Talebpour

TL;DR
PAPPL is an innovative AI-driven platform that personalizes engineering education by adapting to individual student needs through advanced tutoring and analytics, leveraging GPT-4o to enhance learning outcomes.
Contribution
The paper introduces a scalable, data-driven ITS for engineering education that uniquely integrates GPT-4o for personalized, context-sensitive feedback and detailed student analytics.
Findings
Enhanced personalized feedback based on student interactions
Detection of recurring misconceptions for targeted assistance
Provision of detailed analytics for instructors
Abstract
Engineering education has historically been constrained by rigid, standardized frameworks, often neglecting students' diverse learning needs and interests. While significant advancements have been made in online and personalized education within K-12 and foundational sciences, engineering education at both undergraduate and graduate levels continues to lag in adopting similar innovations. Traditional evaluation methods, such as exams and homework assignments, frequently overlook individual student requirements, impeding personalized educational experiences. To address these limitations, this paper introduces the Personalized AI-Powered Progressive Learning (PAPPL) platform, an advanced Intelligent Tutoring System (ITS) designed specifically for engineering education. It highlights the development of a scalable, data-driven tutoring environment leveraging cutting-edge AI technology to…
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Taxonomy
TopicsOnline Learning and Analytics · Robotics and Automated Systems
