In our new playbook, “The AI Educator: Using artificial intelligence to transform manager development,” we share best practices for using AI tools for learning, with a focus on manager development. Through our conversations with researchers, practitioners, and other experts, we identified key areas within learning and development (L&D) that are ripe for organization-wide AI adoption:
- Curriculum development
- Skills practice
- AI tutor and content enhancement
- Mentorship and connection
- Skills assessment
For Matt Beane, an assistant professor of technology management at University of California, Santa Barbara, bringing novices and experts together has always been at the center of learning, as far back as early civilizations inventing the bow and arrow. “That bond is the thing that allowed us to create the bow, the first stored-energy weapon in the history of humanity,” says Beane. “There’s archeological evidence that shows that people worked across the expert-novice divide to do that.” Within the study of organizational learning, much of the research on the novice-expert connection focuses on cognitive apprenticeship, a mental model that undergirds both formal apprenticeship programs and more informal coaching relationships.
Early research on apprenticeship identified three main components of an apprenticeship relationship that produces effective learning:
- Modeling: An expert demonstrates a skill or task for the novice to observe.
- Coaching: The novice attempts the skill, and the expert offers guidance and feedback based on their observations.
- Scaffolding: The expert scales up challenges as novices become more proficient, assigning more and more difficult assignments and and/or slowly reducing the level of structured guidance to encourage independent work and mastery on the part of the novice.
While traditional apprenticeship has been an effective way to learn physical skills and processes throughout history, researchers note that there are three additional steps for cognitive apprenticeship, a process for learning more abstract skills:
- Articulation: An expert or coach prompts the novice to verbalize their thinking process, from their understanding of basic concepts to their problem-solving process while practicing the skill.
- Reflection: The expert encourages the learner to compare their work to that of peers, mentors, or the expert themself.
- Exploration: The expert leaves the learner to independently apply their skills to new situations.
The key to cognitive apprenticeship is to slowly build proficiency and independence over time while providing consistent support, says Laura Ball, director of learning science at apprenticeship platform Multiverse. From traditional instructional models, it requires “a real shift in instructors or coaches moving from that ‘sage on the stage’ to ‘guide on the side.’”
For example, a more experienced manager might help a new manager learn how to give better feedback using the cognitive mentorship model:
- Modeling: The senior manager gives the first-time manager examples of what good feedback looks like, based on best practices and existing scripts.
- Coaching: The two managers practice the skill through role-playing opportunities or by brainstorming how to phrase feedback for the more junior manager’s reports together.
- Scaffolding: The more experienced manager encourages the first-time manager to move from role-playing to giving feedback to reports in real time, slowly scaling up from in-the-moment feedback on small projects and behaviors to more intensive feedback conversations, like performance reviews.
- Articulation: The mentor encourages the new manager to discuss their experiences giving feedback: What was your goal for this feedback conversation? What went well? What would you do differently next time?
- Reflection: The mentor might offer their recommendations for how they might structure feedback conversations, or examples of how other managers have approached feedback conversations in their organization.
- Exploration: The senior manager continues to check in with the new manager in one-on-one meetings, encouraging them to apply their new skills to give continuous feedback to their reports.
With new AI learning tools, organizations have an opportunity to strengthen novice-expert bonds, whether they help learners engage and connect with human experts or serve as the experts themselves. See the chart below for how our five areas of AI adoption in L&D relate to the framework of cognitive apprenticeship described above.
| Areas for AI implementation in learning | Steps of cognitive apprenticeship | |
| Curriculum development | AI-powered curriculum development can help L&D managers model new skills using existing content that guides learners through new processes or frameworks. | Modeling Coaching Scaffolding Articulation Reflection Exploration |
| Skills practice | The best AI coaches mimic the most adept human managers. They can model an example of a skill or process, coach the user by providing feedback in the moment, scaffold learning with new challenges and guidance. They can also prompt users to think about their own learning by asking them to articulate the steps of their problem-solving process, reflect on their work in comparison to peers or other experts, or assign additional assignments for independent exploration. | Modeling Coaching Scaffolding Articulation Reflection Exploration |
| AI tutor and content enhancement | An AI tutor can enhance content-based strategies by scaffolding individual learning, whether through in-the-moment guidance to better understand a lesson or by assigning additional exercises that gradually build challenges. | Modeling Coaching Scaffolding Articulation Reflection Exploration |
| Mentorship and connection | AI tools can strengthen novice-expert connections by matching workers to potential mentors or providing AI-generated summaries and action items based on in-person sessions. | Modeling Coaching Scaffolding Articulation Reflection Exploration |
| Skills assessment | When integrated into a larger learning strategy, AI skills assessment provides a foundation for learners to articulate what they’ve learned and reflect on their progress and competency levels. | Modeling Coaching Scaffolding Articulation Reflection Exploration |
Coaching
Scaffolding
Articulation
Reflection
Exploration
Coaching
Scaffolding
Articulation
Reflection
Exploration
Coaching
Scaffolding
Articulation
Reflection
Exploration
Coaching
Scaffolding
Articulation
Reflection
Exploration
Coaching
Scaffolding
Articulation
Reflection
Exploration
Download the full playbook here for examples and case studies for each of the five areas on our L&D menu, as well as a deep dive into our original survey data and best practices for rolling out AI-powered learning tools.
Thank you to Valence, the sponsor of this playbook, for making this work possible.
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