Blended Vs. Hybrid Learning: Which Type Of Training Content Is Better For Employee Development?

Blended VS Hybrid Learning: Which Type Of Training Content Is Better For Employee Development?
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Summary: By better understanding the best application of hybrid learning and blended learning, you will be better equipped to use either learning design in your training strategy.

How To Best Apply Hybrid Learning

Hybrid learning, which is often confused with blended learning, combines formal learning activities, informal learning, and experiential learning in the workflow. The key is to understand which strategy is better suited to your training content, technology, audience, and performance objectives. For example, blended learning may be more effective if the material is complex (e.g., highly technical skills) and the ideal behaviors require competency or knowledge around several subjects. On the other hand, if the ideal behaviors are composed of separate skills and can be applied individually, then hybrid learning may be a better option. While neither model is strictly better than the other, the context in which they are used may produce varying results. In that sense, the question is which method is better for employee development.

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Instead, you should ask which method is better for your specific training challenge and learning environment. So, to determine which strategy is best to drive the desired business goals, let’s start by understanding the best application of hybrid learning models.

Applying The Hybrid Learning Model

The continuous process of employee development can be considered as two separate phases: the training zone and the performance zone. Ideally, learning cycles between the two as employees acquire, apply, and maintain skills and knowledge. The training zone typically consists of formal training events and experiences in a controlled environment. The performance zone, on the other hand, entails on-the-job experiences, wherein hybrid learning is immediately applicable in real-world contexts.

The Role Of Continuous Learning

Hybrid learning models allow for an ongoing dialogue between the training zone and the performance zone. However, this is only the case when learning is continuous. Moreover, training is much less successful without continuous reinforcement. The wealth of research on reinforcement and repetition, like a recent study conducted at Duke University, finds reinforcement of a learned behavior improves the recurrence of that learned behavior and the application within other environments [1].

If employee development only consists of an initial training event followed by expectations of performance, then employee performance will surely suffer. Instead, design the learning experience as a cycle of learning, application, and maintenance. Maintenance is particularly important for employee performance when you consider the forgetting curve and other theories that describe the loss of skills and knowledge over time. So, create a curriculum that specifies maintenance activities as well. Best practices in performance consulting would suggest aligning those learning activities with related training content so that learners encode the new information in relation to their current knowledge.

Another approach to hybrid learning that utilizes the interplay between the learning and performance zones is to mix formal learning with informal and experiential learning activities. Switching between strategies like eLearning modules, on-the-job application, coaching, social reinforcement, stretch assignments, and formal refreshers, drives both engagement and knowledge retention. Essentially, give your learners the opportunity to apply their knowledge and skills throughout the learning experience and approach hybrid learning from all angles. For instance, you could plan practical applications of individual skills throughout employee onboarding, ending in a capstone that integrates and applies each skill.

Training Zone Strategies

Though the training modality that best fits your performance objectives may vary, the activities within the training zone should share a few common attributes:

  • Controlled
    Both the training content and the environment should be consistent among learners.
  • Scheduled
    Learning activities should follow a timeline based upon expectations along the learning path.
  • Applicable
    Learning should resemble the required tasks and offer realism.
  • Hosted
    All content should be easily accessible in an LMS or learning portal.

Performance Zone Strategies

The performance zone, on the other hand, should have different attributes based on the nature of work to achieve a successful hybrid learning implementation:

  • Supported
    Create learning assets catered to on-the-job success (e.g., SOPs and checklists) that align with specific duties and common challenges.
  • On-demand
    Make assets accessible at the point of need, which is typically when an employee comes across a new challenge.
  • Bite-sized
    Use microlearning tactics to parse learning content into its most basic functional components.
  • Integrated
    Align the functions of business operations platforms with training platforms to enable learning in the flow of work.

Building Better Employee Performance Programs

Employee performance depends on a number of factors, many of which can be controlled with careful Instructional Design strategy and performance consulting best practices. Whether you are using hybrid learning or blended learning, it will be important to promote continuous learning in your organization. Moreover, cycling between the training zone and the performance zone makes reinforcement and skills maintenance much easier to implement, consequently, improving upon learning outcomes and employee performance.

In case you want to discover how to transform your organization’s people and processes and drive both engagement and employee performance, download the eBook 8 Tips For Boosting Your eLearning With Performance Consulting. Also, join the webinar to find out additional information about virtual learning best practices and more.

References:

[1] Relating Reinforcement Learning Performance to Classification Performance