Workplace learning often faces a persistent challenge: employees complete training, pass assessments, yet return to their roles continuing old habits. This disconnect between knowledge and action is a core issue explored in a recent episode of the "Future of Learning" podcast from Open eLMS. The discussion featured host Andy Howie and guest Julie Dirksen, founder of Usable Learning and author of "Design for How People Learn" and "Talk to the Elephant." Dirksen’s work centres on a fundamental truth: learning only truly matters if it changes what people do.
With artificial intelligence (AI) now making content creation faster and more affordable than ever, the focus for Learning and Development (L&D) professionals must shift. If content was never the primary problem, then faster content alone will not resolve the behavioural gaps. The conversation delved into why behaviour is so difficult to shift, how to diagnose underlying issues, and the implications for learning designers working with AI.
Here are the key takeaways from the discussion:
- The "Elephant and Rider" Metaphor: Human behaviour is often a tug-of-war between our rational, planning mind (the rider) and our automatic, emotional, comfort-seeking impulses (the elephant).
- The Power of Immediate Feedback: The most common reason for a knowledge-behaviour gap is delayed or absent feedback, which diminishes the perceived value of an action.
- Diagnosing the Root Cause: L&D teams must move beyond assuming a knowledge deficit and instead diagnose problems using frameworks like COM-B (Capability, Opportunity, Motivation for Behaviour).
- The Overlooked Role of Practice: Effective skill development requires a structured continuum from initial learning through dedicated practice, leading to sustained performance.
- Transforming Compliance Training: To be effective, compliance and risk training must move beyond tick-box exercises and engage learners by making the consequences and relevance tangible.
- Purpose-Driven Evaluation: L&D should measure impact with a clear purpose, ensuring data directly informs future decisions and actions, rather than merely collecting metrics.
- Navigating AI's Impact: AI introduces varying levels of risk and requires new skills like "trust calibration" and "vigilance decrement" to manage outputs effectively and ethically.
The "Elephant and Rider" in Workplace Learning
Julie Dirksen introduced a powerful metaphor from Jonathan Haidt's "The Happiness Hypothesis": the brain as a rider and an elephant. The 'rider' represents our conscious, logical, and planning brain – the part that knows what we should do. In contrast, the 'elephant' symbolises our automatic, emotional, and visceral brain – the part that seeks immediate comfort and follows established habits. This 'elephant' often exhibits a "present bias," prioritising what feels good now over future benefits.
This internal conflict is central to many workplace challenges. For instance, an employee's 'rider' knows the importance of documenting client calls for future reference, but their 'elephant' urges them to move immediately to the next task, which offers a more immediate sense of accomplishment. Understanding this dynamic helps L&D professionals recognise that simply providing information to the 'rider' is often insufficient to influence the 'elephant's' deeply ingrained preferences. It is important to note that the elephant is not inherently 'lazy'; it serves vital functions for comfort, safety, and efficiency, and only becomes a 'problem' when its automatic responses conflict with desired outcomes.
The Power of Immediate Feedback: Why Timing is Everything
Perhaps the single most common element in behavioural challenges, as Dirksen highlighted, is delayed or absent feedback. This concept is underpinned by "hyperbolic discounting," a principle from behavioural economics which states that rewards are most meaningful when immediate, with their perceived value decreasing hyperbolically over time.
For L&D, this means that learning content is most compelling when it can be applied and reinforced immediately. If the benefit of a new behaviour is far in the future, the motivation to adopt it wanes. Consider the salesperson who knows detailed notes are beneficial but only sees the payoff months later; the immediate reward of moving to the next client often wins. Open eLMS understands this need for immediacy, offering solutions that allow for practical application and immediate feedback, helping to bridge the gap between learning and doing.
Diagnosing the Real Problem: Capability, Opportunity, Motivation (COM-B)
To effectively shift from merely delivering content to changing behaviour, L&D teams must first accurately diagnose the problem. Dirksen advocates for models like COM-B (Capability, Opportunity, Motivation for Behaviour) from University College London.
- Capability: Does the individual possess the necessary knowledge, skills, and even psychological stamina? In the age of AI, this extends to the "verification burden" – the mental energy required to proofread and validate AI-generated outputs. As AI takes over low-level tasks, new employees may lack the foundational experience needed to develop critical judgment, posing a significant challenge for future corporate training and skills management.
- Opportunity: This encompasses both physical and social factors. Physical opportunity refers to whether the environment supports the desired behaviour (e.g., easily accessible hand sanitiser in a healthcare setting). Social opportunity involves whether the behaviour is modelled and supported by peers and leadership. Tacit organisational rules, such as senior staff not asking for help, can powerfully undermine formal training. Open eLMS LMS offers robust personnel management and custom roles & permissions to help L&D identify and address structural and environmental barriers.
- Motivation: This can be reflective (aligning with values and goals) or automatic (driven by habits and biases). Understanding these drivers is crucial for designing interventions that resonate deeply with learners.
By systematically addressing these three components, L&D can move beyond generic e-learning and create targeted interventions that truly address the root cause of behavioural gaps.
Beyond Content: The Critical Role of Practice
A frequently overlooked aspect in learning design aimed at improving performance is the crucial role of practice. Dirksen outlined a continuum: learning, practice, and performance. While L&D often excels at the 'learning' phase – ensuring individuals can perform a skill accurately at a reasonable speed – it frequently fails to provide structured support for the 'practice' phase.
This gap is less common in fields with clear physical components, such as medical training for doctors or flight simulations for pilots, where structured practice is inherent. However, for cognitive skills like effective management feedback or complex problem-solving, organisations often expect immediate high-level performance after a short course, neglecting the necessary iterative practice to embed the skill and make it automatic. Open eLMS, with its AI-powered course generator, enables the rapid creation of varied practice scenarios, including gamification, to support learners through this critical phase.
Transforming Compliance Training from Tick-Box to True Engagement
Compliance and risk training often present a unique challenge. Organisations frequently view it as a "legal defensibility need" – a tick-box exercise to prove training occurred, rather than a genuine effort to change behaviour. This approach, as Christian Hunts noted in his book "Humanising Rules," teaches employees to ignore training, fostering a "muscle" for disengagement.
To counteract this, behavioural science offers compelling strategies. Instead of passively receiving information, learners can be placed in the role of an auditor, tasked with identifying compliance issues in realistic scenarios. This approach makes the learning tangible, immediate, and engaging, tapping into our natural inclination to be 'right' and to find solutions. The Open eLMS eLearning Store provides a library of over 600 CPD-accredited courses, many of which can be adapted or enhanced with interactive elements to foster genuine engagement. Furthermore, the Open eLMS Learning Generator can rapidly transform dry compliance material into interactive, scenario-based learning experiences, including videos and podcasts, making it far more impactful.
Measuring What Matters: Purpose-Driven Evaluation
The conversation also tackled the long-standing challenge of L&D evaluation. Despite the existence of models like Kirkpatrick's levels since the 1960s, L&D often defaults to measuring only learner reactions (Level 1) and knowledge acquisition (Level 2), neglecting behavioural change (Level 3) and business impact (Level 4). This phenomenon aligns with the principle that "every system is perfectly designed to get the result it gets." If L&D isn't incentivised or equipped to measure higher levels, the system will naturally produce lower-level metrics.
Dirksen argued that evaluation should never be conducted without a clear purpose and a specific question it aims to answer. Data collection should directly inform decisions, such as budget allocation or technology investment. Without this strategic intent, evaluation becomes "soft and squishy," failing to provide compelling insights for action. Open eLMS LMS provides robust learning tracking and custom reporting capabilities, including Power BI integration, enabling L&D leaders to gather meaningful data and demonstrate the tangible ROI of their employee training platform initiatives.
Navigating the AI Landscape: Risk, Trust, and the Need for New Skills
The advent of AI has introduced a new layer of complexity to workplace learning. Dirksen used the analogy of "scooters, stilts, and jetpacks" to describe AI's varied impact:
- Scooters: AI helps experts perform existing tasks faster, leading to productivity gains.
- Stilts: AI enables novices to operate at a higher level, but this carries significant risk as their judgment may not match the output.
- Jetpacks: AI allows for entirely new, complex tasks, but these ventures come with very high risk and require deep expertise for effective governance and liability management.
A critical challenge is "vigilance decrement" – the human tendency to reduce scrutiny when errors are infrequent. Unlike human interns, AI is inherently less predictable, meaning L&D must develop skills in "trust calibration" – understanding the appropriate level of vigilance for AI outputs based on risk. For instance, using AI for marketing copy carries a lower risk than for safety guidelines.
L&D professionals are uniquely positioned to define these guidelines, ensuring responsible AI integration. The Open eLMS Learning Generator, an AI-powered course creator, exemplifies how AI can enhance content creation, but it also underscores the need for L&D to equip employees with the critical thinking and evaluation skills required to leverage such tools effectively and ethically. This involves understanding the risk level of tasks, the user's ability to judge outputs, and the overall governance model.
Driving Impact with Open eLMS
The insights from Julie Dirksen on the "Future of Learning" podcast underscore a vital truth: effective L&D transcends mere content delivery. It requires a deep understanding of human behaviour, a commitment to strategic diagnosis, and a proactive approach to practice, evaluation, and the responsible integration of new technologies like AI.
Open eLMS stands as a one-supplier solution designed to empower L&D leaders to meet these evolving challenges. From the comprehensive Open eLMS LMS with its powerful skills monitoring and custom reporting to the revolutionary Open eLMS Learning Generator that creates e-learning courses, videos, and gamification in minutes, Open eLMS provides the tools to move beyond knowledge transfer and drive genuine, measurable behavioural change. The platform's extensive capabilities, including the Open eLMS OS for broader business management, ensure that organisations can centralise their learning and development efforts, optimise corporate training, and truly leverage AI to achieve their strategic goals.
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