Personalization is firmly embedded within our daily technological lives. Facebook tells you who to be friends with based on who are you already friends with. Netflix tells you what you want to watch based on what you’ve already watched and what people who have also watched that also watched. Amazon tells you what to buy based on what you are thinking about buying and … You get my point.
Personalization can be great. No argument there. However, some of the more well-known approaches to personalization have clear limits, especially when you think about how they could be applied in the workplace. Netflix’s recommendation engine, for example, can only go so far. It knows what I’ve watched and how I’ve reacted within the system, but it doesn’t know much else about me RIGHT NOW. Therefore, the experience cannot adapt to match my true, immediate needs and preferences. Netflix would be much more powerful if the system knew how my day was going and could tailor my options accordingly. Recommendation gets you started, but its the ability to adapt that can make a real difference in our desire to meet a user’s timely, individual needs.
The ability to adapt to an individual employee has tremendous potential for strengthening the value of learning and support experiences. Rather than complete a course simply because everyone is expected to do so, what if an employee was only required to engage when the opportunity aligned to their specific knowledge and skill gaps – whenever they may appear? We would spend less money on training – development AND delivery. We could finally stop sacrificing individual needs to achieve scale. We would need less motivational gimmicks due to the clear value proposition to the employee. And we would more clearly respect and leverage the time and capabilities of our people.
Before we go any further, I want to reinforce the value of user choice. Imagine a world in which Netflix only allowed you to watch what it felt was the right content for you. I’d be stuck watching reruns of The Office and Parks and Recreation for the rest of my life. No one wants that, and the same idea applies to workplace learning. The ability to adapt should help L&D provide the most valuable content and experiences to the employee in order to maximize their time and effort. However, when the employee wants to go beyond their profile and explore new topics and interests, our strategies must be built to accommodate. So no, adaptive learning is not the performance version of Big Brother. It’s more akin to a virtual assistant who’s always looking out for you based on your needs and preferences, not just those of the organization.
How do we get beyond recommendation to truly personalize our support strategy? Here are 4 essential dimensions to consider when applying adaptive learning principles within your organization.
Adaptive learning is a data-driven concept. To provide a right-fit learning experience, I have to know as much about you as possible and make informed adjustments based on the data. The more inputs, the better!
As we already explored with Netflix, consumption data is just part of the adaptive learning formula. To identify the right content for the right person at the right time, an adaptive strategy must consider multiple data sources, including:
- Demographic: who is this person?
- Context: what is happening around this person that may have an impact on their performance?
- Consumption: what content/experiences is the person consuming and how do these activities potentially relate to their performance?
- Knowledge: what expressed knowledge growth/gaps have been identified at this time for the person?
- Behavior: what behaviors is the person demonstrating on the job and how do these decisions relate to expectations/knowledge?
- Outcome: what results is the person achieving and how do these outcomes relate to the other data categories?
- Feedback: what are this person’s preferences and opinions related to their performance?
By continuously pulling together comprehensive data on what someone consumes, knows, does and achieves, we can get pretty darn close to a 360 degree profile on the individual. We can then use this data to ask better questions and target the right support when appropriate.
Building content for an adaptive learning strategy requires an evolved design approach. To target an individual’s needs, L&D must break content down to focus on very specific problems. At the same time, these resources must fit together as part of a larger puzzle that can help the user grow at their own pace. Multi-day sessions and 30-minute eLearning modules may still play a part, but targeted content that can be pushed and/or pulled at the moment of need better align to an adaptive approach. Depending on the needs of the user, this content could include anything from brief videos and question/answer knowledge checks to interactive experiences and on-demand reference materials. This is why microlearning – aka learning that fits – is an effective starting point for designing adaptive experiences.
Technology enables the adaptive experience. Without modern tech, it’s near-to-impossible to scale personalized support. This is why L&D pushes so much generic content into the world – to make sure we’re “covered.” This devalues the learning experience for everyone.
Plenty of learning and workplace tech is “targeted” in that it can assign content to an individual based on profile attributes like location, job title and hierarchy. However, to be truly adaptive, the system must continuously ingest multi-dimensional data and adjust the user experience accordingly. Axonify (plug plug) is an example of truly adaptive learning technology because the system is always assessing and reacting to the data provided at an individual and organizational level.
To truly enable adaptive learning, we must empower the person. The sad fact is that many employees are used to the generic, spoon-fed, one-size-fits-all approach. Few have been empowered to drive their own improvement. Even if they have been handed the keys, they don’t have time to plan development activities among all of their other work responsibilities.
To maximize the potential of adaptive learning, employees must understand this approach and accept the extra layer of insight and feedback. They shouldn’t be shocked or confused by personalized recommendations and activities. We must help them realize they likely can’t see every knowledge and performance gap and therefore welcome the opportunity that adaptive learning represents. At the same time, we must enable workplace curiosity so employees can expand their interests and not become overly reliant on the adaptive experience for their long-term development. We must also remember that adaptive learning is not just about content. Human interaction, including reflection, coaching and collaboration, are integral parts of the experience.
Let’s wrap up our brief exploration of adaptive learning with a simple example story …
Bill works in a warehouse where safety is a HUGE concern. Bill receives continuous online reinforcement training on key safety principles, such as lifting procedures, to ensure his knowledge on the topic remains current. He is pushed videos and questions on topics that he struggles with more often than topics he has mastered. He is also provided with links to best practices and job aids.
Bill is regularly observed on the job by his manager and auditors, who record data on proper and improper lifting executions. Lately, Bill has been slacking on his lifting behaviors and has fallen below the required threshold. Bill’s manager receives a notification about Bill’s behavior gap. At the same time, Bill receives a refresher online training session during an upcoming shift. Between the additional training and coaching, Bill is able to close his behavior gap and prove his knowledge on the topic. However, the online reinforcement training and behavior observations continue to ensure sustained retention and execution.
While Bill is receiving his individual support, the organization is reviewing knowledge and behavior data for the entire warehouse team and comparing it with safety results, including OSHA-recordable injuries. The L&D team uses this data to continuously adjust their training resources and behavior observation process to focus on areas that are seeing real-world challenges rather than covering every possible safety behavior at the same time.
Are you leveraging adaptive learning within your organization? How do you get beyond content recommendations to offer truly personalized experiences? What challenges are you facing when introducing adaptive learning to your employees and stakeholders?