Is L&D still stuck in the 20th century?

Change may be constant, but not its application

The "change is constant" narrative is a tricky one. On one side of the change spectrum are sectors like ‘Tech’ with product or feature launches every month or quarter. On the other end are sectors such as Energy or Drug production, where it takes decades (e.g Ozempic – the ‘miracle’ diabetic drug ~30yrs) for a product to hit the market. But I have often wondered about certain ideas, frameworks and models developed in the people & psychology domain that have been around for 50+ yrs. with hardly any innovation or update. These seem to be immune to change, even though we know they don't work as they were originally intended.

One argument is, ideas linked to ‘psychology’ are much more subjective, compared to an external product – like an ‘app’. Therefore, it depends on the person using the tool or model. Two weeks back I wrote about the ‘forgetting curve and its relevance today’ and I learnt a lot about how various people felt about its utility today.

Lack of process innovation in HR & Training

But, what about people & project management ideas from the 1970s & 80s. Everybody knows 'performance management' ideas like GE's infamous 9-blocker, create unsustainable incentives and unhealthy environemnts at work, but many organizations continue to use variation of the idea.

Of the many, one model I want to dive deeper today is the ADDIE (Analyze > Design > Develop > Implement > Evaluate) model extensively used, trained and sworn by many L&D professionals. ADDIE was originally developed in the 70s by the US military, aimed at managing their training projects. While quite a few attempts have been made over the years to come up with innovative training design methodologies, ADDIE persists, for better or worse. And this is what I worry about.

On one front, L&D continues to struggle with gaining higher levels of ‘stakeholder approval’ and ‘perception of impact’ (just attend any training-industry event and look at some of the popular topics), yet some of L&D’s mainstream models and frameworks stem from (once great) ideas meant for a world we left 5o years ago.

Let’s analyse and contrast ADDIE's origin and current contexts.

Time and Context:

• Developed in the 70s: ADDIE aimed for military training, emphasizing standardization and linear progression. It doesn't fully adapt to today's diverse learning needs and agile environments.
• Information scarcity: Back then, knowledge access was limited. ADDIE's controlled approach ensured thoroughness, but today's information abundance demands adaptability and quicker content creation, consumption and even quicker life-cycle.

Technological Disruption:

• Limited technology: ADDIE focused on physical materials and classroom settings. Today's eLearning tools, adaptive learning, and microlearning demand more flexible and iterative design processes.
• Linear vs. non-linear learning: ADDIE's linear progression clashes with modern learners' preference for exploration and self-directed learning. Technology enables non-linear pathways and personalized learning journeys.

Shifting Work and Learning Paradigms:

• Static jobs and skills: ADDIE assumed relatively fixed job roles and skills. Today's dynamic workplaces require continuous learning and upskilling, necessitating more agile training approaches.
• Collaboration and social learning: ADDIE prioritizes individual instruction, while modern learning embraces collaboration and peer-to-peer learning facilitated by technology and social platforms.

Advances User Experience and Complexity Sciences:

• Design thinking emphasizes user-centricity, iteration, and prototyping, contrasting with ADDIE's analysis-driven, linear approach.
• Complexity thinking acknowledges interconnectedness and emergent learning, demanding more flexible and responsive training models.

Additional factors:

• Learner expectations: Today's learners expect engaging, interactive experiences beyond traditional lecture-based models.
• Content consumption: Attention spans are shorter, necessitating bite-sized learning formats instead of lengthy modules.
• Data-driven insights: Learning analytics and tech allows for real-time feedback and course adjustments, challenging ADDIE's static evaluation phase.

So, how do we move on?

A model like ADDIE is just a starting point, not the end. The specific design of our learning experience should depend on our business's unique context, audience, and learning objectives. Point to remember is, we must work backwards from our customers & learner’s needs to solve for their problems. We don’t have to be stuck to ‘a framework’ just because industry-bodies recommend it.

While ADDIE has limitations in today's context, its strengths can still serve as a foundation for a more adaptable model. Here are attributes to consider when designing your developmental experience journey.

Focus on Rapid Iterations, Chunks and Sustainment:

Iterative design: Abandon the linear ADDIE sequence in favor of cycles of design, development, implementation, and feedback. Continuously improve based on real-time data and learner feedback.

Microlearning: Break down content into bite-sized, easily consumable modules that adapt to diverse learning styles and preferences.

Agile development: Embrace rapid prototyping and testing to quickly deliver relevant learning experiences without sacrificing quality.

Prioritize Learner Centeredness:

Design thinking principles: Involve learners in the design process to understand their needs, preferences, and challenges. Create personalized learning journeys and cater to diverse learning styles.

Social and collaborative learning: Integrate opportunities for peer-to-peer interaction, knowledge sharing, and collaborative problem-solving. Utilize social learning platforms and tools.

Engagement / Game Mechanics: Incorporate engagement and game elements like points, badges, and leaderboards to increase engagement and motivation.

Leverage Technology and Data:

Adaptive learning: Use AI-powered platforms to personalize learning paths based on individual learner progress, strengths, and weaknesses.

Immersive technologies: Integrate AR, VR, and other immersive tools to create engaging and interactive learning experiences.

Data-driven insights: Utilize learning analytics to track learner progress, identify knowledge gaps, and measure the effectiveness of training interventions.

Embrace Complexity and Systems Thinking:

Design for interconnectedness: Recognize that training needs are often intertwined with organizational processes, culture, and technology. Design holistic solutions that address the bigger picture.

Design for continuous learning: Foster a culture of continuous learning and upskilling, encouraging learners to seek knowledge and adapt to changing environments.

Design for resilience: Equip learners with the skills and knowledge to navigate uncertainty and thrive in complex environments.

Its a brand new world

We are at the dawn of the AI age, where we must reimagine knowledge, information, learning and skills related models and frameworks. We must question the origin contexts and if they are still relevant. This is reskilling and upskilling in action for Training & Education professionals. The bad and the good news is, we don’t have any precedence, but we can figure it out, if we choose to.