adaptive learning

The current buzz around adaptive learning is fueled by our collective fascination with algorithms, big data, and machine learning. The idea of creating a totally personalized, totally relevant experience for our learners is quite seductive. But before we dive headlong into an adaptive learning lovefest, let’s take a step back. There are a number of key needs that drive most learning professional’s interest in adaptive learning.

Here are a few:

  1. Provide each individual with learning opportunities that are relevant and useful to them.
  2. Reduce time spent by learners on irrelevant training.
  3. Help individual learners improve in their weaker areas.
  4. Find and address knowledge gaps and identify coaching opportunities.

A well-planned and implemented adaptive learning solution can solve these needs. The trick is to determine just how adaptive you really need your training to be.

What is adaptive learning?

Essentially, adaptive learning uses learner data to tailor training content to each individual’s specific needs. The content learners see over time changes based on data points such as performance, self-reported confidence, or other demographic data. Adaptive learning allows you to spot strong and weak performers, and identify coaching opportunities. It ensures each individual receives learning content that is most suited to their needs.

Adaptive learning varies greatly in scale and complexity, and the right adaptive learning solution depends on your need. In some cases, a fully adaptive solution might be overkill and some simple personalization, which is far less complex and costly to create, will do. In other situations, a standalone adaptive learning tool is ideal for growing or reinforcing knowledge for a single topic or training initiative. Some organizations seek to ditch their LMS entirely and switch all learning content over to an adaptive learning ecosystem. 

Below, I’ll outline three different types of “adaptive learning” solutions commonly found in the market today: the pseudo-adaptive solution, the standalone adaptive solution, and the adaptive learning ecosystem.

Level 1: The Pseudo-Adaptive Solution

At level one, we have solutions that aren’t actually adaptive learning, yet accomplish many of the same things that a truly adaptive solution can.

Personalized Learning

Instructional designers frequently personalize learning content, both within a larger curriculum of solutions and even within a single eLearning course. For example, the scenario you use to teach physical security to your office staff is not the same scenario you might use with your field technicians. Within a single course, personalization can be as simple as prompting learners to select their role at the beginning of a course and then displaying personalized content for that role.

Branching Scenarios

Branching scenarios are also a frequently-used instructional design strategy that accomplishes some of the goals of truly adaptive learning. They provide a safe environment for learners to practice new skills.

In a branching scenario, learners progress based on the choices they make. Branching can range from simple (the learner makes a bad choice, sees the outcome, and goes back to the beginning) to highly complex (the learner reaches three or four decision points, each with unique outcomes that lead to even more decisions). The more scenario branches, the more content you need to write.

Level 2: The Standalone Adaptive Learning Solution

For organizations that are ready for true adaptive learning, a standalone adaptive solution is likely the most practical and attainable. These solutions provide a fully adaptive experience and provide robust analytics, but the experience centers around a single training topic. There’s no need to convert all of your training modules to an adaptive approach in order to take advantage of adaptive learning and see some of its benefits.

This type of solution is ideal if:

  • You don’t want to put all of your training into an entirely adaptive system.
  • You don’t want to replace your LMS.
  • There isn’t enough demographic data on your learners accessible to create a robust, fully adaptive system.
  • You want to focus on a specific training initiative (like a product launch or a process roll out to improve the learning experience and collect data).

Our Knowledge Guru ‘Drive’ app is an example of a standalone adaptive solution. It continuously adjusts the content served to each learner based on their self-reported confidence levels for each learning objective and their actual performance on the minigames. Trainers can use the analytics dashboard to spot trends and identify coaching opportunities.

Level 3: The Adaptive Learning Ecosystem

At level 3, an organization is all in – everything they use for training is contained in an “adaptive ecosystem.” This ecosystem is a comprehensive structure that uses performance and demographic data to adapt content to each learner. This ecosystem is either a total LMS replacement or a technology tool that is layered on top of the LMS. If you can feed your ecosystem with the right data and set it up the right way, you are more likely to create an experience that truly optimizes everyone’s individual learning needs.

A full-fledged adaptive learning ecosystem is a big commitment. It often means sifting through a mountain of old training content to determine what the ideal learning paths are, who should receive what, and what needs to be updated. A well-conducted analysis can help greatly in this endeavor.

Which level is right for your organization?

Many organizations will get the most benefit from simply increasing the number of training initiatives that include “pseudo-adaptive” elements such as personalization. This is a simple change that can make a big difference in your learning outcomes.

Others are ready to integrate standalone adaptive solutions, such as Knowledge Guru, into learners’ workflows. Standalone adaptive tools are excellent ways to reinforce knowledge and gather rich data on the knowledge transfer from a larger training event.

Others are on a quest to replace their entire LMS with a totally adaptive system. The level of “adaptive” that’s right for you depends greatly on your organization’s needs and technology constraints.