PAL: Personal Adaptive Learner
2026-04-14 • Artificial Intelligence
Artificial IntelligenceHuman-Computer Interaction
AI summaryⓘ
The authors created a new AI system called PAL that makes learning from lecture videos more interactive and personalized in real time. Unlike typical platforms that only adapt in fixed ways, PAL watches and understands lectures, then asks learners questions that change based on how they answer. After each session, it gives a summary with examples tailored to the learner's interests. This approach helps learners by providing support that adjusts continuously instead of being static.
AI-driven educationpersonalizationmultimodal content analysisadaptive learningreal-time feedbackinteractive learninglecture videospersonalized summary
Authors
Megha Chakraborty, Darssan L. Eswaramoorthi, Madhur Thareja, Het Riteshkumar Shah, Finlay Palmer, Aryaman Bahl, Michelle A Ihetu, Amit Sheth
Abstract
AI-driven education platforms have made some progress in personalisation, yet most remain constrained to static adaptation--predefined quizzes, uniform pacing, or generic feedback--limiting their ability to respond to learners' evolving understanding. This shortfall highlights the need for systems that are both context-aware and adaptive in real time. We introduce PAL (Personal Adaptive Learner), an AI-powered platform that transforms lecture videos into interactive learning experiences. PAL continuously analyzes multimodal lecture content and dynamically engages learners through questions of varying difficulty, adjusting to their responses as the lesson unfolds. At the end of a session, PAL generates a personalized summary that reinforces key concepts while tailoring examples to the learner's interests. By uniting multimodal content analysis with adaptive decision-making, PAL contributes a novel framework for responsive digital learning. Our work demonstrates how AI can move beyond static personalization toward real-time, individualized support, addressing a core challenge in AI-enabled education.