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Product 06Teaching Tool

LOGEN AI

An AI-powered instructional design tool for educators.

Status
Live
Category
Teaching Tool
Built for
Teaching & learning
LOGEN AIProduct view
LOGEN AI

Overview

About LOGEN AI

Writing good learning objectives shouldn't feel like rocket science, but somehow it often does. LOGEN AI transforms this essential-yet-tricky task into something surprisingly straightforward and even enjoyable.

Developed with Johns Hopkins University and trusted by over 100+ educators and instructional designers across the United States, LOGEN AI understands the art and science of learning objectives. It knows that 'Students will understand photosynthesis' isn't quite right, but 'Students will explain the process of photosynthesis using correct scientific terminology' hits the sweet spot. The AI draws from extensive databases of educational standards and Bloom's Taxonomy to craft objectives that are both meaningful and measurable.

What we love most is how LOGEN AI works as a thoughtful instructional design partner. It doesn't just generate objectives—it explains why certain verbs work better than others, suggests improvements, and helps identify gaps in learning progressions. Whether you're a seasoned educator or just starting your teaching journey, LOGEN AI makes the complex art of instructional design accessible and, dare we say, fun.

Capabilities

What LOGEN AI offers

  1. 01Bloom's Taxonomy alignment
  2. 02Multi-grade level support
  3. 03AI-powered objective generation
  4. 04Export and sharing capabilities

Research

Research connected to LOGEN AI

Selected academic work associated with the design, development, or study of this product.

Conference presentation2025

LOGEN AI: Implementing a Transparent Human-AI Collaborative Tool for Enhanced Instructional Design

Li, H.*, Zhang, S.*, Lee, S.*, Trexler, M.*, & Botelho, A. F.*

Association for Educational Communications and Technology (AECT) International Convention 2025

October 2025 · Las Vegas, NV, USA

Conference paper2025Spotlight PaperAwarded the iRAISE Travel Scholarship

ARCHED: A human-centered framework for transparent, responsible, and collaborative AI-assisted instructional design

Li, H.*, Fang, Y., Zhang, S., Lee, S., Wang, Y., Trexler, M., & Botelho, A. F.*

iRAISE 2025: Innovation and Responsibility for AI-Supported Education at the 39th AAAI Annual Conference on Artificial Intelligence (AAAI 2025)

March 2025 · Philadelphia, PA, USA

Proceedings of Machine Learning Research, 273: 4-104

Partnership & collaboration

Partners behind LOGEN AI