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Adaptive Learning to Ignite Your L&D Program

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Adaptive Learning to Ignite Your L&D Program

Learning and Development (L&D) is a major responsibility of HR departments around the globe. Employees new and old need to be continually trained for onboarding, upskilling, and compliance to perform well in their roles. An employee’s opportunity for success is contingent on their ability to continually broaden their skillset.

Most L&D strategies are old and outdated. They fail to take advantage of modern technology to deliver high-quality, personalized learning to employees. Instead, they adopt a one-size-fits-all framework that is slow and expensive.

Personalization, by way of adaptive learning, is a winning strategy for L&D. AI and machine learning platforms can now enable learners to chart their own paths through their customized learning experiences. The result is faster, more accurate, and more relevant, personalized training. This L&D strategy works to create overall better business outcomes.

Top L&D Needs

Learning and Development is one of several factors that enable organizations to achieve their business objectives. The most important is to establish business value. High-performing employees give organizations the best chance for success, but L&D also helps employees reach their career aspirations while their employer reaches its own aspirations.

There is no doubt that L&D needs vary across various industries and disciplines, but there are several data points tied to a company’s L&D strategy. 

A Brandon Hall Group survey recorded how much different needs were valued:

  • 77% of companies emphasized learning effectiveness.
  • 67% of companies linked L&D to organizational performance.
  • 65% of companies linked L&D to individual performance.
  • 76% of companies rated learning as high in importance.

A personalized learning model based on adaptive learning can help improve L&D along all of these factors.

Traditional L&D is no longer effective

Traditional L&D often fails to meet the needs listed above, with more and more challenges becoming evident. Legacy models do not put the learner first, but also create a cumbersome experience in many ways:

  • Is time-consuming
  • Is not “in-the-flow”
  • Is not personalized
  • Is not tied to performance
  • Is not data-driven
  • Is not relevant
  • Offers poor speed to competence
  • Offers poor assessments
  • Offers poor training materials
  • Focuses on completion, not mastery

A good, modern L&D strategy should address all of these issues. It should be fast, personalized, tied to performance, relevant, and more. The goal should be mastery, not completion.

The Solution: Personalization through Adaptive Learning

Personalization is widely recognized as a way to improve learning performance. The Brandon Hall Group estimates that 93% of businesses believe this to be true.

The case for personalized learning is strong. It improves company outcomes across the board. There is a reason that your Barista at Starbucks asks you for your name, Spotify serves up ‘Daily Mix’ suggestions and Coca-Cola ran a campaign personalizing cans with a wide array of names. 

People respond to things that are made for them. This is no difference in business. SaaS models are becoming increasingly more difficult to sell because prospects and clients need to understand why they are buying something. Personalized learning gets right to the heart of what an individual learner needs (and wants) to know. 

Personalized learning can build a learning culture for today’s environment. It promotes a culture of investment, equity, and inclusivity by providing just what you need, just when you need it.

Personalized learning can increase employee engagement. A miserable 36% of American workers report being engaged at work, which is actually higher than the global 20%. Workers want work experiences that are meaningful, relevant, efficient, and respectful of their time.

Personalized learning can impact performance by increasing knowledge and skill retention. This affects both individual and organizational performance.

But What is Personalization?

Personalization is for you. Right time, right place, right context, and right impact. 

Personalization is something that you know when you see it, but can be difficult to define precisely. It’s what you have on Duolingo or Rosetta Stone, for example.

More specifically, the language(s) offered on Rosetta Stone haven’t changed for centuries, but your experience and pace of learning will be precisely connected to you. Your experience will be different than the next person, despite baseline modules being the same. 

Although no single property defines personalization, any worthwhile personalized learning experience will offer the intelligence to curate an experience based on real-time assessments and adaptivity. 

It’s the difference between focusing on basic Spanish vocabulary, and complex conjugations depending on your proficiency. ¿Claro que sí? 

person holding mobile phone with notifications showing progress

Personalization knows what you know, and what you don’t. It flexes to the moment, adjusting behavior to match your needs. It gives you exactly what you need, when you need it. It is relevant to your role, and it identifies and fixes weak spots. Personalization helps with building critical digital skills by adapting to your own learning process and providing relevant feedback.

Obstacles to Adoption: You can’t personalize what you can’t measure

Modern personalized learning programs are built on AI and ML. They need vast quantities of data to work, and without making measurements, you will not have a functioning system.

This is one of the biggest obstacles to adopting a personalized learning experience for most businesses. A Brandon Hall survey recorded the obstacles to adoption:

  • 42% of businesses said they don’t have the metrics.
  • 42% said they don’t have the time.
  • 36% said they don’t have the technology.
  • 35% said they don’t know how to link.
  • 31% said they don’t know how to assess well.

Only 31% of companies said their learning strategy includes a method for measuring success. The ability to gather data and measure success is the main factor in what we call “Learning Measurement Maturity”.

Learning Measurement Maturity

There are many ways to measure learning outcomes, from the most basic, to the most mature, complex, AI-driven solutions.

Bar graph visualization of the different levels of learning measurement maturity

At Level 0, where far too many businesses are, there is no attempt to measure learning success at all.

At Level 1, lagging maturity, businesses just do some basic measurements about learner satisfaction. This includes documents like “smile sheets.”

At Level 2, emerging maturity, businesses collect an array of metrics. They don’t measure all of their intended learning outcomes, but they do run basic reports.

At Level 3, developing maturity, businesses measure a majority of their learning across a wide variety of metrics. They use this data to improve learning strategy and delivery.

At Level 4, leading maturity, businesses gather data for metrics across all types of learning. This includes formal, informal, and experiential learning. They can use this data in conjunction with other data across the business to measure the impact on performance and business results.

Our job, as providers of a personalized learning system, is to help businesses move into level 4. In doing so, they can deliver a personalized L&D strategy that improves outcomes across the board.

Making the leap to personalized learning with adaptive learning.

There is a gap between traditional L&D and personalized L&D. Companies with traditional programs simply cannot keep up: their training takes longer, and is less efficient and less relevant. 

Adaptive Learning is what takes you from legacy training programs to the personalized training of the future. It is the driving force and technological advantage behind programs like Rosetta Stone and Duo Lingo.

Adaptive learning is a personalized approach to learning that makes use of modern technology. It is optimized learning, tailored to the unique needs of every individual. Adaptive learning works by using human and artificial intelligence to observe, measure, make decisions, and calibrate actions.

In any case, adaptive learning uses multiple data to help each learner on their own unique path. These data include factors such as the learner’s proficiency, their learning context, their language and location, and their level of engagement.

The way forward: L&D with Adaptive Learning

Linking training to performance is key to L&D effectiveness. Personalization is the enabling strategy.

Adaptive learning makes personalization at scale possible. It unlocks the full value of organizations and employees.

Realizeit’s mission is to transform workforce training and learning through personalization to drive performance. If you would like to start a conversation, learn more about  Realizeit’s solutions, or hear about how other organizations use Realizeit's adaptive learning program, feel free to reach out to connect with a solutions-driven expert. 

We hope to help you make personalized learning a key component of your organization’s training strategy! 

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