How to Use Adaptive Microlearning for Your Frontline Workforce

Marketing MaxLearn

Marketing MaxLearn

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Are You Struggling with Microlearning That Fails to Deliver?

[ Learn more through our Webinar]
Are You Struggling with Microlearning That Fails to Deliver?

Adaptive microlearning

Frontline employees can make or break companies. They need to be trained continuously to perform efficiently and effectively on their job,

But as we know, no two human beings are alike. Their learning needs, comprehension levels, and learning styles and preferences vary, a lot! And that’s something we all struggle with.

In a microlearning context, the real question is: Will a standardized microlearning approach work for your entire frontline staff? Well, a one-size-fits all approach doesn’t always work!

The good news is that microlearning lessons can be personalized for each learner. That’s known as Adaptive Microlearning. And results are inevitably superior with personalized learning!

Let’s now look into how adaptive microlearning works, and how it can help you.

Adaptive Microlearning: An Overview

Adaptive Microlearning applies the principles of how the brain works using Artificial Intelligence (AI) driven data analytics. Using Artificial Intelligence with microlearning initiatives results in adaptive learning solutions.

A platform with AI-enabled adaptive learning capabilities helps personalize your microlearning lessons. An adaptive microlearning platform applies algorithms to create adaptive microlearning experiences and helps keep the learner’s brain in a ‘ready-to-learn’ mode. It also allows access to learning on different devices including laptops, tablets, POS systems, or smart phones.

The platform’s features also help you measure the baseline of the learning needs and the capabilities and knowledge levels of each learner. Baselining makes training modules relevant to each learner.

The Science Behind Adaptive Microlearning

The concept of Adaptive Microlearning is based on the fact that that each person is unique in the way he or she learns, retains, and applies information. It uses cognitive principles to make learning easy to grasp.

Adaptive microlearning modules uses three key techniques based on how the brain works:

  • Spaced repetition – We learn faster and more easily when the given information is short, spaced over time, and is actively tested. Adaptive learning solutions deliver information repeatedly over time, reinforcing learning before the learner forgets it. Customized information is delivered intelligently to each learner at regular intervals. This spaced repetition makes information ‘stick’ resulting in better memory, recall, and application at work!
  • Retrieval practice – Quizzing the learner with questions of increasing levels of difficulty help in the retrieval of information. When the difficulty level of questions keeps increasing, the brain actively tries to retrieve the answers from the learned information. Such questions during a lesson promote deeper memory and superior retention. Here are some examples of question formats used for retrieval practice.
  • Confidence-based assessments – Confidence-based assessments help assess the learner’s trust or belief in his or her answers to a question. In other words, how sure they are of their own answers. This helps check their mastery, and identifies mistakes or hesitation on lessons learned. For instance, after the learner chooses a response to a question, he or she is asked, ‘How confident are you about your answer? ‘High, Medium, Low’? This is done to differentiate between what a learner thinks they know and what they actually know. The surer the employee are about the answers they choose, the more quick, confident, and reliable they are on the job. James E. Bruno explained this masterfully.

10 Ways Adaptive Microlearning Helps Learning

Adaptive Learning:

  1. Considers the learner’s training history, current knowledge level, and preferences
  2. Fills knowledge gaps through reinforcement questions
  3. Helps identify topics where a learner is weak or needs support
  4. Uses multiple formats – questions, videos, infographics, simulations, podcasts, and gamification
  5. Uses assessments and retrieval questions based on a learner’s opportunity areas
  6. Poses questions on a topic the learner needs most help with. Wrong responses are corrected immediately, along with reasons why
  7. Allows the learner to either complete or skip sections or activities (free navigation)
  8. Informs the learner about the topics learned, the question history, strengths and weaknesses (based on confidence assessment), and knowledge growth
  9. Recommends relevant learning material and resources needed by the learner
  10. Keeps learners updated on new upcoming training, what’s been scheduled, and what’s already accomplished.

On top of it all, Adaptive Microlearning makes learning exciting.

For example, on day 1, the learner gets a piece of new information; on day 2 it could be compliance training; and on day 3 it could be a refresher. It all depends on what your learner needs to learn on any given day. These exciting daily bursts of learning could go on each day throughout the month!

AI-enabled Adaptive Microlearning platforms let you tie learning with rewards.

For example, you could have redeemable rewards points, exciting offers, freebies, prizes, etc., that allow you to highlight events, additional training programs, and activities.

The dashboards highlight individual knowledge progress and actionable analytics.

For example, how your teams are performing; who are the experts, who needs help; who is compliant (demonstrating the right behaviors), and who is not.

An Adaptive Microlearning platform provides immediate value through its self-learning options. It improves learning outcomes, reduces training time and cost, and boosts revenues.

To quote Winston Churchill, “Personally, I am always ready to learn; although I don’t always like being taught”. Adaptive Microlearning makes the being taught factor far more acceptable and enjoyable to individual learners.

Are You Struggling with Microlearning That Fails to Deliver?

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