Adaptive Learning: Five Common Misconceptions

Employee capability is now THE differentiator in modernbusiness. Companies can no longer compete based solely on familiar factors,such as product or price. It takes skilled people to foster the innovations andexperiences that help your organization stand out in a crowded marketplace.But, in an environment where organizations are evolving constantly and employeeneeds are a moving target, how can L&D keep pace with the speed ofbusiness? This is why, as a modern L&D leader, you must begin to integrateadaptive learning principles into your workplace learning strategy.

Figure 1: Workplace learning can be a struggle between individualneeds and scalability—with scale often winning out (Pexels)

What is the true definition of adaptive learning?

Adaptive learning brings together the latest in learningscience, data, technology, and workplace principles. The concept is based onthe realization that people develop in their own unique ways and, therefore,require a more customized experience than an academic, one-to-many approachoffers. By using multidimensional data and cutting-edge technology, L&D candeliver the right information to the right person at the right time, therebypromoting value to the individual as well as the overall organization.

Adaptive learning is a bleeding-edge topic for corporateL&D. As such, there is plenty of room for misinterpretation andmisunderstanding about what it takes to deliver an adaptive experience. Inorder to shift your L&D team from a one-size-fits-all approach to aright-size-fits-one mentality, you must overcome these misconceptions andclearly articulate the value of adaptive learning within your organization.After all, your stakeholders don’t want to hear about learning strategy. Theyare focused on getting their employees to the desired level of capability asquickly as possible in order to drive business value.

Figure 2: Misconceptions—like the myth that the human attention span is shorter than a goldfish’s—can lead to serious missteps in workplace learning practices (Pixabay) 

Five misconceptions about adaptive learning

Here are five common misconceptions regarding adaptive learning,along with suggestions for how you can sidestep these fallacies and deliverright-fit learning experiences.

1. Personalized and adaptive learning are the same

This may seem like wordsmithing, but “personalized” is notthe same as “adaptive.” For example, you may buy your child a new pair of shoesthat fits their size, style, and interests perfectly. However, a year later youwill likely find that the child has changed in a variety of ways and now needsnew shoes. The shoes were super personalized, but they can’t adapt as the childgrows.

This is exactly how learning works! Personalized refers to“targeted” content offerings based on an employee’s attributes. For example, acourse may be assigned to cashiers who work in the North American retaildivision. That’s a personalized learning opportunity, but only to a point.Everyone who meets this criterion will receive the same experience. The contentcannot adapt to meet the less well-defined nuances of individual need. Forexample, it cannot determine how quickly I am picking up new information or whetherI retain it over the long term. And that means it can’t adjust content on thefly to focus on areas where I need more help, nor can it advance the content tochallenge my expertise.

Personalization is now a consumer expectation, and it’s agreat place to start when it comes to workplace learning. However, ultimately,it will not help L&D provide just-in-time support at enterprise scale. Whenexploring partners who promise to provide “adaptive learning,” dig in tounderstand how the learning experience grows with the individual over the longterm. If the platform is only able to push content at groups of people based onprofile attributes, the company is providing personalized—not adaptive—learning.

2. Branching content is adaptive learning

Most of the popular rapid development authoring tools foreLearning offer the option to branch content. This means that the employee willmove through a path based on his or her actions within the course. The employeemay have the option to skip activities or content items based on correctanswers, or to be posed scenario questions with unique, pre-programmedresponses to simulate real-world interaction. In many cases, this functionalitycan help instructional designers provide a better user experience than typical“click Next to continue” eLearning. It may also help the employee complete thecourse more quickly based on his or her existing knowledge. But it’s still notadaptive learning.

Branching is based on the idea that there are a set numberof paths the employee can take to get to a predetermined conclusion.Progression is based on decisions contained within the content, not provenreal-world knowledge or behavior. Therefore, it only “adapts” based on a singlemoment in time, which is likely to also include plenty of guessing as theemployee attempts to complete the course satisfactorily. Also, just as withpersonalization, branching content has a hard limit. While it provides a smallamount of user-specific flexibility, it cannot grow with the employee over timeand support his or her future needs.

Like personalization, branching is a great option for coursedevelopment—when a course is the right-fit learning solution. However, adaptivelearning is much more than an instructional design tactic. It must reach beyondthe course and support continuous learning that fits into the day-to-day. Whenyou escape the academic “place and time for learning” model, you open the doorto a plethora of new options. While courses may still play a small role, sharedknowing, coaching, communication, and reinforcement are now available aspowerful tactics to drive right-fit, continued development.

3. Adaptive learning is like Netflix

Self-directed learning is a growing conversation withinL&D, and for good reason. Informed choice is a great way to motivateemployees to learn and align development opportunities with individual value.As a result, people have started to compare self-directed learning with thepersonalized recommendations offered by platforms like Amazon and Netflix. Manylearning platforms now offer similar content recommendations based on whatyou’ve completed in the past or what your peers do or like. While this informedopportunity to consume more content is nice, it’s still not adaptive learning.

Netflix does its best to help you sort through a massiveamount of content using what the platform knows about you—your viewing andrating data. However, there is one big piece of data Netflix is missing: howyou’re feeling right now. Netflix may be suggesting dramas based on my pastviewing habits, but I may be in the mood for a comedy because I’ve had a badday. Netflix cannot adapt on the fly when it doesn’t have a full picture of myindividual needs.

Providing recommendations for continued learning based onwhat an employee has done in the past or what people in similar jobs haveenjoyed is a step up from anonymized LMS content libraries. But it’s still arelatively one-dimensional approach to supporting employee capability. Moredata is needed to really get a sense of the individual and their timely needs.L&D can then use this data to better balance pull and push learningopportunities. When you explore adaptive learning approaches and technologies,ask questions about the data model used to drive the experience. If you findout that the provider relies solely on consumption and rating data, you’llprobably end up with the same limitations as Netflix. That may not hurt anentertainment experience, but the inability to adapt and grow will considerablydamage the learning experience.

4. Adaptive learning is just about assessment

Employees who are new in their roles come to the table witha mixed bag of capabilities based on experience. No two people have the exactsame needs from day one. Therefore, many L&D teams have adoptedpre-assessment to provide employees with the opportunity to “test out” oftypically required training activities. If they can show that they already knowwhat they are doing, they don’t have to waste time checking boxes in extracourses. This is certainly better than forcing everyone through the same pathregardless of experience, but it’s not adaptive learning.

Like many earlier examples, pre-assessment relies on limiteddata provided at a single moment in time to determine need. It also only actsto reduce the size of a one-size-fits-all training package rather than identifyand support true individual need. Adaptive learning requires ongoing dataregarding an employee’s content consumption, knowledge, behavior, andperformance in order to provide the optimal level of support. Yes, some of thisdata is best acquired through knowledge and practical assessment. However, thisdata must be collected continuously to account for growth and decline inemployee capability as well as the changing needs of the business. Whendesigning your adaptive learning model, focus on a continuous approach ratherthan content-specific or moment-in-time assessment. This is where right-fittechnology—platforms that don’t rely solely on test scores and completions—canhelp you bring adaptive learning to life.

5. Adaptive learning should replace all training

In a perfect world, L&D could provide a personal coachwho can step in when needed to guide every employee. This simply isn’t feasiblein a modern workplace. Adaptive learning leverages data and technology to helpL&D get as close as possible to a personal coach and just-in-time support.However, this doesn’t mean L&D pros should forgo everything else they doand rely solely on digital learning to take care of their people.

Adaptive learning is more than a platform or instructionaldesign strategy. It’s a fundamental reimagination of how L&D supports theorganization. By using the right combination of science, data, and technology,L&D can enable adaptive, continuous learning and support at enterprisescale. Rather than simply replace other tactics, such as instructor-led trainingand coaching, adaptive learning can strengthen these concepts by allowingL&D to apply them only when they are the absolute right fit. A continuousflow of multi-dimensional data can help L&D get proactive and identify theneed for more structured, in-depth training opportunities—before businessstakeholders start knocking at the door. The added focus on continual,individualized learning can also push L&D to create more focused, reusableassets rather than lengthy, single-use courses.

The fundamentals of how L&D approaches workplacelearning are typically not far off base. Adaptive learning provides a frameworkfor how to better apply familiar tactics in new ways in order to balanceindividual need with the priorities and scale of the entire business.

The principles of adaptive learning adoption

Adaptive learning may be a new concept within your L&Dteam, but it is based soundly in the practical realities of workplace learning.As you begin to explore the shift to adaptive learning with your L&D team,apply the following principles:

• The purpose of adaptive learning is to providethe right person with the right support at the right time, based on establishedindividual and business objectives
• Adaptive learning extends beyond the traditionalcourse to enable continuous learning that fits into the day-to-day employeeworkflow
• Adaptive learning requires an ongoing, multidimensionaldata profile, including what an employee does and doesn’t know (knowledge),what they are doing well and not so well on the job (behavior), and whatresults they are seeing as compared to their objectives (outcomes), in order tofind and support timely needs
• Adaptive learning takes advantage of a varietyof L&D methodologies, including questions, videos, on-demand resources, andcoaching, to provide individualized, timely support
• Selecting the right technology that can leveragemultidimensional data and drive continuous learning is a critical component ofa scalable adaptive learning strategy
• Adaptive learning balances push and pullresources that support both individual employee needs and organizationalpriorities

Like any business unit, L&D is under pressure to provideclear, measurable value to stakeholders across the organization—from theC-suite to the front line. Course completions and hours spent in training areno longer sufficient measures for success, and employees now have the resourcesto look elsewhere for development opportunities that meet their individualneeds. Adaptive learning can enable L&D to address these needs, articulatethe value of their work, and ultimately transform the business through rapidcapability growth.