Building AI Literacy and Skills in Teams

Welcome to the Trainer Track

You've completed the Practitioner Track and demonstrated mastery of AI strategy, governance, and operations. Now it's time to multiply your impact by developing others.

The Trainer Track prepares you to:

• Facilitate learning experiences for colleagues
• Coach emerging AI Champions
• Build sustainable communities of practice
• Measure and scale AI adoption

Let's begin with the foundation: understanding how adults learn.

Adult Learning Principles

Adults learn differently than children. Understanding these principles will make your training far more effective.

The Andragogy Framework

Malcolm Knowles identified five key principles of adult learning:

1. Self-Direction

Adults prefer to control their own learning journey.

Implications for AI Training:

• Offer learning paths, not mandated curricula
• Let learners choose focus areas based on their roles
• Provide resources for self-paced exploration
• Respect their time and autonomy

2. Experience as Foundation

Adults bring rich experience to connect new learning.

Implications for AI Training:

• Start with what they already know
• Connect AI concepts to familiar work contexts
• Use their domain expertise in exercises
• Acknowledge that they may know things you don't

3. Readiness to Learn

Adults learn best when they perceive immediate relevance.

Implications for AI Training:

• Begin with real problems they face
• Show immediate applicability
• Avoid theory-heavy introductions
• Get to hands-on quickly

4. Problem-Centered Orientation

Adults prefer learning that helps solve real problems.

Implications for AI Training:

• Frame content around use cases, not technology
• Use their actual work scenarios
• Focus on "how can I use this tomorrow?"
• Provide practical tools and templates

5. Internal Motivation

Adults are motivated by personal growth and meaning.

Implications for AI Training:

• Connect to their career development
• Highlight the significance of AI skills
• Celebrate achievements and progress
• Create safe spaces for experimentation

Instructional Design for AI

The ADDIE Framework

Setting Learning Objectives

Use the SMART framework:

• Specific: Clear, concrete outcomes
• Measurable: Observable evidence of learning
• Achievable: Realistic for the audience
• Relevant: Connected to real work
• Time-bound: When they'll achieve it

Example Objectives:

Content Sequencing

The 4-Part Structure:

1. Hook (5-10%): Engage with a relevant problem or question
2. Instruction (30-40%): Present concepts with examples
3. Practice (40-50%): Hands-on application
4. Wrap-up (10-15%): Summarize and connect to next steps

Progressive Complexity:

• Start with familiar concepts
• Build on prior knowledge
• Increase complexity gradually
• Provide scaffolding for difficult concepts

Multi-Modal Learning Design

Learning Preferences

People absorb information differently. Effective training uses multiple modalities:

The 70-20-10 Model

Research suggests learning happens through:

• 70%: On-the-job experience
• 20%: Social learning (peers, mentors)
• 10%: Formal training

Implications:

• Training is just the start
• Design for post-training application
• Create peer learning opportunities
• Provide ongoing support resources

Blended Learning Design

Hands-On Exercise Design

The Exercise Spectrum

Designing Effective Exercises

The ICARE Framework:

• Introduction: Set the scene and objective
• Connect: Link to their real work
• Apply: Provide the task
• Reflect: Debrief and discuss
• Extend: Suggest further exploration

Example Exercise Design:

01TITLE: First Prompt Engineering Session
02
03INTRODUCTION:
04"You'll practice writing effective prompts using
05the role-goal-constraints framework we just covered."
06
07CONNECT:
08"Think of a task you do at least weekly that
09involves writing, analysis, or summarization."
10
11APPLY:
121. Describe your task in 2-3 sentences
132. Write a prompt using role-goal-constraints
143. Test your prompt in the AI tool
154. Refine based on the output
16
17REFLECT:
18- What worked well?
19- What surprised you?
20- What would you change?
21
22EXTEND:
23"Try using this approach for 3 different tasks
24this week. Note what patterns emerge."

Managing Time and Energy

Session Pacing:

• Alternate instruction and practice
• Include breaks every 45-60 minutes
• Build energy early, allow for natural decline
• Save engaging activities for after lunch

Group Work Design:

• Clear instructions before forming groups
• Defined roles when appropriate
• Visible timers for time management
• Structured share-back process

Addressing Barriers and Resistance

Common Resistance Patterns

Strategies for Engagement

For Fearful Learners:

• Start with low-stakes exercises
• Emphasize that AI augments, not replaces
• Share stories of successful adoption
• Provide private practice opportunities

For Skeptical Learners:

• Acknowledge valid concerns
• Use data and case studies
• Invite them to test claims
• Leverage their expertise

For Overwhelmed Learners:

• Break into smaller chunks
• Provide checklists and templates
• Pair with supportive partners
• Offer additional support resources

For Disengaged Learners:

• Increase personal relevance
• Call on them specifically (gently)
• Use their expertise in examples
• Make it interactive

Practical Exercise: Design a Training Session

Design a 90-minute AI training session for your organization:

1. Audience Analysis: Who are they? What do they know? What do they need?

2. Learning Objectives: What will they be able to do after the session?

3. Content Outline: What topics will you cover? In what sequence?

4. Activity Design: What hands-on exercises will you include?

5. Assessment Plan: How will you know if learning occurred?

Key Takeaways

• Adult learners need relevance, autonomy, and connection to experience
• Effective training is mostly practice, not lecture
• Multiple modalities reach more learners
• Resistance is normal—address it with empathy and evidence
• Training is the beginning, not the end, of learning

Next Steps

In the next module, we'll explore Community of Practice and Prompt Jams—creating sustainable peer learning structures that extend beyond formal training.