Designing AI-Integrated Website for Self-Directed Learners

Overview

This ongoing research project focuses on integrating artificial intelligence into learning platforms to enhance self-directed learning experiences. The project aims to create personalized learning pathways using AI algorithms that adapt to individual learning styles and preferences.

Objectives

• Develop an AI-powered platform that adapts to individual learning styles
• Provide personalized recommendations based on learning patterns
• Support autonomous learning processes through intelligent content curation
• Create adaptive assessments that adjust to learner progress

Methodology

The project employs a design-based research approach that combines:

• User experience design principles
• Machine learning algorithms for personalization
• Educational psychology frameworks
• Iterative testing and refinement processes

Current Progress

• Literature review completed on AI in education (✓)
• User needs analysis in progress (🔄)
• Prototype development phase (🔄)
• Initial user testing planned for Q3 2025

Expected Impact

The platform is expected to improve learning outcomes for self-directed learners by providing:

• Personalized learning experiences
• Adaptive content delivery
• Real-time feedback and assessment
• Enhanced learner engagement and motivation

Technologies Used

• Machine Learning: Python, TensorFlow, scikit-learn
• Natural Language Processing: NLTK, spaCy
• Web Development: React, Node.js, MongoDB
• Learning Analytics: D3.js, Learning Record Store (LRS)

Publications & Presentations

• Northwestern University Learning Sciences Symposium 2024 (Poster Presentation)
• Manuscript in preparation for submission to Computers & Education

Collaborators

• Dr. [Name], Northwestern University School of Education
• Graduate Research Team, Learning Sciences Program
• Industry Partners (EdTech Companies)