What makes your top performers so effective? What sets them apart from average performers? The research on expertise has an answer, and the Skillgym method is built on it. This article walks through that research, from how experts think to how a practice program is designed to make others think the same way.
Experience and expertise
Experts possess highly organized mental models, built from extensive experience, that let them grasp and solve complex problems quickly (Hoffman et al., 2013). They excel in two ways:
- They handle familiar situations quickly and effortlessly. This is automaticity.
- They handle new or tricky situations with confidence. This is flexibility.
Experience shapes the mind in both directions: it builds a large library of models for common situations, and it teaches the eye to recognize the detail that matters in an unfamiliar one. Skillgym's purpose is to create scenarios that let people think and perform at the level of the company's best, in a fraction of the time it took the best to get there.
Eliciting the expert: the brief
The first step in building a Skillgym circuit is the brief. It is the moment when the client's subject-matter experts describe the situation, the counterpart and their own best practice, and it sets the performance level that the role play will then transfer to everyone through practice.
In the literature, step one of any accelerated-expertise program is Cognitive Task Analysis (CTA): a broad family of methods for eliciting, unpacking and representing what experts know (Klein and Militello, 2001). More than a hundred CTA techniques are documented. The Skillgym brief has its roots in that family, adapted to the product and to how organizations actually work: a proprietary blend of CTA techniques rather than any single standardized one.
The brief is designed to ask experts only what is strictly necessary. The rest of what a simulator needs is derived from it by a pipeline of agents working deductively, within the structure of hundreds of expert models mapped over the years. The result is faster elicitation, less burden on the expert, and a mental model that stays intact from the brief to the scenario. Where the materials leave a gap, the system asks a specific question rather than inventing.
Why flexibility matters
Hoffman and colleagues (2014), discussing what rapid training of expertise requires, bring together two theories: Cognitive Flexibility Theory (Spiro et al., 2013) and Cognitive Transformation Theory (Klein and Baxter, 2009).
Cognitive Flexibility Theory concerns learning in complex domains: many concepts interacting, high variability, constant novelty. Communication, negotiation and leadership are exactly that kind of domain. The theory's central claim is that knowledge from formal instruction transfers to real, dynamic cases only when it is learned flexibly, and it sets out the principles that make this possible. Here is how Skillgym applies them.
- Real-world complexity. Scenarios mirror real situations, with characters who react to what the trainee says and consequences that last for the whole conversation. No oversimplification.
- Case-based learning. A wide range of context-rich scenarios lets people experience the same skill in different situations.
- Multiple representations. The same skill is seen from several angles: different characters, different objectives, different levels of difficulty.
- Interconnected knowledge. Circuits (sets of related scenarios) and bootcamps (sequences of practice with a defined rhythm) show the connections between situations and prevent compartmentalized learning.
- Adaptive application. Practicing across scenarios builds the ability to apply a skill to a situation never seen before.
- Active construction. A free, dynamic conversation forces the trainee to build understanding rather than recall facts.
These principles are where the method's strength lies, and why it builds deep, flexible knowledge that can be applied directly at work.
Why feedback matters: learning involves unlearning
Learning from experience requires reflecting on one's own performance: understanding what led to success or failure, and why.
Cognitive Transformation Theory holds that people revise their mental models through experience, especially when a model proves inadequate. Models are extended, adjusted or rejected in a continuous process of elaboration and replacement. Learning therefore includes unlearning. In real life this takes a long time. The way to speed it up is effective feedback, and the mechanism the theory points to is sensemaking: how people make sense of their experience (Klein et al., 2006), which Klein and Baxter identify as essential in virtual environments for building more robust mental models.
Sensemaking is a large part of the Skillgym method, and it is what happens after the conversation. The trainee meets three kinds of feedback in sequence:
- Emotional feedback: the character tells the trainee, in first person, how they lived the conversation. The scenario determines the character's reactions, so this account is about the character's experience; the system never analyzes the trainee's emotions.
- Qualitative feedback: a review of the conversation with each turn explained, and an AI coach who knows that exact session and can replay its critical moment.
- Quantitative feedback: the Smart Debrief, with behavioral metrics against the client's competency model, plus knowledge and compliance checks.
The whole method is a cycle with a clear direction: preparation, guided conversation, self-assessment, the character's account, analysis, numbers. Then another conversation, with the new understanding applied. We believe this is one of Skillgym's strengths: practice, make sense of it, practice again.
How practice transfers to real life
What is the mechanism by which skills trained in Skillgym show up in real situations? The answer is transfer-appropriate processing (TAP), a body of research going back more than twenty years. TAP proposes that training is most effective when it engages the same mental processes used in the real situation. The training environment does not have to look identical to the workplace; it has to make the trainee process the situation the way they will have to process it for real.
Skillgym synchronizes the two from both sides: cognitive, through scenarios that require the same reading of the situation and the same decisions, and emotional, through characters who create the same pressure. This is what makes the experience valid as preparation, and a psychologically safe environment is what makes it possible to practice the hardest scenarios at all.
Conclusion
Skillgym is a training method rooted in cognitive science, in particular Cognitive Flexibility Theory and Cognitive Transformation Theory. It accelerates the development of expertise in complex domains through:
- expert task analysis to elicit and transfer the mental model;
- case-based scenarios, organized in circuits;
- guided practice, with a live coach and multiple valid paths;
- targeted feedback in three forms, built for sensemaking;
- a training protocol that keeps people practicing.
By aligning what happens in practice with what happens at work, the method maximizes transfer. That is the whole point.
If you want to go deeper
- Crandall, B., Klein, G., & Hoffman, R. (2006). Working Minds: A Practitioner's Guide to Cognitive Task Analysis. MIT Press. https://doi.org/10.7551/mitpress/7304.001.0001
- Hoffman, R. R., Ward, P., Feltovich, P. J., DiBello, L., Fiore, S. M., & Andrews, D. H. (2013). Accelerated expertise: Training for high proficiency in a complex world. Psychology Press.
- Klein, G., & Militello, L. (2001). Some guidelines for conducting a cognitive task analysis. In Advances in Human Performance and Cognitive Engineering Research, Vol. 1. https://doi.org/10.1016/S1479-3601(01)01006-2
- Klein, G., & Baxter, H. C. (2009). Cognitive transformation theory: Contrasting cognitive and behavioral learning. In The PSI Handbook of Virtual Environments for Training and Education, Vol. 1: Learning, Requirements, and Metrics.
- Klein, G., Moon, B., & Hoffman, R. R. (2006). Making sense of sensemaking 1: Alternative perspectives. IEEE Intelligent Systems, 21(4), 70–73.
- Spiro, R., Coulson, R., Feltovich, P., & Anderson, D. (2013). Cognitive Flexibility Theory: Advanced knowledge acquisition in ill-structured domains. In Theoretical Models and Processes of Reading (pp. 544–557). https://doi.org/10.1598/0710.22