Training technology personalization

4 Innovative Training Technology Tips for Personalization

Michelle Bodkins Corporate Training Leave a Comment

In traditional instructor-led training, verbal learning styles tend to be more successful. But that doesn’t account for all of your learners. There is a diversity of learning styles among individuals that can be difficult to overcome. However, advances in training technology make that challenge more manageable. By using various digital learning modalities and creating a more personalized learning experience you can help your visual, aural, physical, logical, social, and solitary learners to retain vital information.

Training Technology for Personalization

Learning Portals

One of the more common training technology platforms that learning consultants will suggest to enable personalization is a learning portal or learning management system. While the use of learning portals has become fairly common, organizations often fail to use them effectively. When fully integrated into an organization’s processes, it can create a cohesive learning experience that spans employee onboarding, daily work challenges, and continuous learning.

The learning journey for different departments and individual roles can vary. So, your learning portal should support these differences. For instance, create a dashboard for each role type. This can be as simple as having meters for the unique skills relevant to their role that show their progress through a course. Ideally, this would also be paired with a role-specific learning path, skills maps, leaderboards, and social cohorts to round out the learning experience.

Adaptive Learning

Adaptive learning is a more recent innovation in training technology. This method of personalization builds courses around a learner’s unique needs. Not everyone absorbs information the same way. However, this technology takes that into account by measuring how long it takes students to complete assignments, how they perform on assessments, and how well they retain the information, then presenting training assets based on their performance. Essentially, the course builds itself around the learner.

As a result, adaptive learning technology gathers critical information about your digital learning course in key areas including:

  • Learner preferences
  • Content consumption
  • Efficacy of content
  • Speed to Competency on individual skills

Adaptive learning tailors the presentation of training assets based on the measurement of factors like those above. Consequently, this method can increase engagement by reducing learning activities around information your learners already understand well.

Complex Decision-Making Paths

Similar to the personalization you get with adaptive learning, building eLearning activities with complex decision-making paths can be effective for learners navigating a difficult subject. These scenarios allow your employees to sharpen their skills while gaining applicable experience to what they will be doing in the real world. Branching scenarios recreate key processes, enabling learners to explore different solutions.

This method will take employees down a pathway based on their current knowledge and allow them to see the consequences (good or bad) of how they choose to handle something. This program is designed to lead employees to a resolution, but there are different routes to get there. Consider what else you might accomplish with individual user data. For instance, comparing decisions within a cohort supports the detailed discussions between peers that drive critical thinking.

Real-Time Performance Analytics

As digital learning assets become more diverse, tracking performance and usage data becomes more difficult, so it’s important to have a learning portal with custom data-tracking and performance-analytics. Generally, performance data is used to measure completion rates, completion times, and performance on assessments. Then, that information is used to improve upon learning assets and activities that weren’t as effective. Most training technology has some data-tracking function, but personalization platforms often use this information in real-time to create a more personalized experience.

Conclusion

Utilizing training technology for personalization creates a more engaging learning experience. It can tailor course navigation to the unique needs of individuals, driving performance through methods that aren’t scalable in instructor-led training. No one likes spending time going over the information they already know or trying to fight through a learning method that doesn’t jive with how they take in information. However, that same data can be used to improve upon eLearning activities and training assets So, as you consider training technology for personalization, also keep in mind the benefits of detailed individual performance data. That data is vital for increasing engagement, improving learner experience, and driving learning outcomes.

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