AI Foundations & Acceleration for Learning Designers

AI serves as a strategic tool for learning designers, drafting objectives and scenarios. Humans provide context, culture, and validation to ensure accuracy and emotional resonance.

Master prompt engineering with the rich model framework—define AI's role, input, context, and helpful action to produce precise, useful outputs for learning design tasks and lab work.

Learn to use AI in learning design responsibly, safely, and ethically, balancing speed with data privacy, bias and representation, intellectual property, and learner impact, guided by an ethical AI checklist.

Learn how an ethical ai-driven program for aml training scaled to 600 employees in four weeks through structured prompts, expert reviews, bias checks, data protection, and transparent disclosure.

Reflect on your values, biases, and intentions to shape ethical AI use in learning design. Identify boundaries, habits, and safeguards, and practice design with intention to preserve integrity.

Use AI to extract key findings from lengthy research and translate academic language into actionable insights for training design, guided by a research to practice flowchart.

Learn to turn dense research into clean, usable summaries in minutes with an AI-assisted, three-part worksheet. Master prompt setup, AI output review, and interpretation to extract practical training insights.

Identify learning gaps with AI tools by analyzing feedback, comparing role expectations with performance, and probing underlying learner needs. Use the template to map learner tasks, observations, and AI insights.

Turn theory into actionable learning content by applying retrieval practice and Bloom's taxonomy, guided by Kolb's experiential learning, with AI-assisted design prompts and an infection control example.

Create a prototype brief that unites learning needs, core ideas, and format into a clear plan. Use the prototype planning sheet to outline audience, theory, format, and content prompts.

Evaluate every AI-generated research summary using the research output evaluation checklist, ensuring accuracy, clarity, relevance, practicality, and ethics to create credible, transformative learning experiences.

Use AI to speed up scripting, storyboarding, and slide planning through a three-stage design process, while you stay in charge of alignment, tone, flow, and polish.

Learn how to use AI to create scenarios and case studies that activate emotion, curiosity, and empathy, provide safe failure, turning knowledge into experience across e-learning, classrooms, coaching, and assessments.

Design a complete microlearning module from idea to structure, script, and activity using AI, breaking content into 4–6 slides with a reinforcement activity and a feedback loop.

Design a four-hour AI-enhanced training program by outlining 3-4 digestible modules, scripting with AI, including scenarios, visuals, practice, and assessments, then use peer review for clarity.

Reflect on what you have learned about AI-generated content and your design process. Use the reflection journal to examine prompts, trust, rewriting, and shifts from hesitant to curious.

Onboard and support instructors with AI by creating facilitation guides, pre-session sheets, and prompts that improve confidence and delivery. Build enablement kits and blueprints to accelerate instructor readiness.

Empower instructors with AI to craft smarter prompts, facilitation guides, and immersive role plays that spark reflective discussion, dynamic scenarios, and engaging, adaptable learning experiences.

Assemble a practical instructor resource kit as a single source of truth with summaries, talking points, prompts, and facilitator notes, enhanced by AI for timing and case studies.

Finalize your AI-powered facilitation guide by integrating session flow, timing, prompts, activities, and debrief cues into a clear, practical delivery document.

Evaluate your AI-ready instructor toolkit for reusable prompts, editable materials, and a structured flow that AI can adapt, enabling scalable, versioned, and easily reusable sessions.

Use AI to reveal learner struggles and successes by analyzing behavioral and performance data beyond final scores. Identify patterns in pauses, rewinds, and open-ended responses to drive targeted improvements.

Learn to harness AI to analyze assessments and surveys, extract themes and sentiment, identify learning gaps, and drive improvements by reworking modules and explanations for learning designers.

Leverage predictive modeling with data and AI to identify at-risk learners and trigger proactive interventions. Use the Predictive Planning Canvas to shape metrics, patterns, and actions for real-world impact.

Design an AI-enabled data dashboard prototype to turn survey responses, quiz scores, completion rates, and feedback into clear, actionable insights for design and delivery decisions.

Explore ethical use of learner data by asking key questions about data collection, privacy, transparency, security, bias, and dignity, guiding designers to empower learners and build trust.

Design and implement a 30-60-90 day AI integration plan for learning designers, moving from exploration to pilots to scaling with concrete goals and ethical data use.

Embrace the AI revolution, stay curious, design with humanity, and map three next steps using the final self-assessment and action planner to strengthen your LED professional role.