University Research Project AI • IoT • Accessibility

Personalized Learning Hub for Students with Special Needs

A lightweight, accessible learning platform that adapts to individual needs using AI-driven personalization, assistive interaction, and IoT-based feedback.

Abstract learning illustration

Abstract

Students with special needs often require tailored content delivery, alternative interaction methods, and supportive feedback mechanisms. This project proposes a Personalized Learning Hub combining accessible user interfaces, AI-based adaptation, and IoT-assisted learning tools.

The solution focuses on improving engagement and comprehension through voice-based learning, haptic guidance, adaptive learning paths, and object recognition activities — designed to be fast-loading, mobile responsive, and friendly for evaluators, lecturers, students, and parents.

Key Features

Voice-based Learning System

Accessibility

A voice-first learning assistant supports navigation, instructions, and interactive learning using speech recognition and text-to-speech, reducing barriers for learners who benefit from auditory guidance.

IoT Smart Glove (Haptic Feedback)

IoT • BLE

A wearable smart glove provides tactile cues and feedback through BLE-connected haptics to support guided practice, step-by-step tasks, and safe interaction.

Smart Learning Adaptation System

AI Personalization

Adaptive learning paths personalize content difficulty and pacing based on learner interactions, progress, and performance indicators.

Object Recognition Learning Tool

Computer Vision

Learners explore real-world objects through camera-based recognition and guided prompts, connecting visual learning to everyday contexts.