Training design

Traditionally, instructional design models have a strong focus on part task training in early phases of a learning process, but the 4C/ID model advocates a structured combination of both. The sequence of learning tasks (whole tasks) is the backbone of training, while part task practice supports learning or refreshes the highly routinised skillset at the time at which it is needed most in the sequence of learning tasks. The design of a training session is a detailed process with careful considerations. The TNA focused mainly on broad lines and high-level competencies. A training design investigates small operational details and outlines the training in the form of blueprints. At first, blueprints are designed without limitations to prevent constraints-driven training. If limitations in a new training design are too decisive, there is risk of constraints-driven training. This can potentially result in inefficient and/or ineffective training.

The design is afterwards adjusted to meet the present limitations.

A blueprint will contain:

Learning tasks within a module (whole- and part tasks)

NLR uses an approach that consists of whole task learning (1) and part task practice (2). The approach uses experience-based learning, which means that learning occurs in the full context of the operation. Therefore, the learning tasks are called whole tasks. Additionally, parts of the whole tasks can be selected and practiced separately from the whole task. This promotes automation of the skill or can be an opportunity to train the competency in isolation. The blueprint presents a structure of whole tasks and part tasks, divided into modules and increasing in complexity.

Complexity factors

Operational conditions are translated into complexity factors, which can be used to tune the complexity of whole tasks in accordance with the progress of the trainee. The weather during flight is an example of a complexity factor. However, the weather cannot be changed. A complexity factor that is easily variable is the support of an instructor. Therefore complexity factors needs to be adjusted on each other to reach a complexity level that is suitable to the competence of the trainee.

Supporting knowledge, just-in-time knowledge and the level of instructional support

The complexity of the whole tasks increases between the modules. And within each module the level of instructor support declines (represented in blue within each whole task) .Supportive information (3) and Just-In-Time (JIT) information (4) are provided to support the whole task performance along the different scenarios. Supportive information is presented at the start of a module, which is often core information. Just-In-Time information is presented right before it is needed. This information is often very specific.


Use cases

Chinook helicopter
Training and Simulation

12 January 2022

R&D case: Redesign of helicopter training

A common, modernised approach for platform qualification training The challenge The Defence Helicopter Command of the Royal Netherlands Airforce expressed a need for a common, modernised approach for qualification training on all of their platforms. The solution The project produced actual MQT for AH-64 and CH-47 crews. Additionally, user requirements, a system concept and a […]
Replacement of initial training capacity
Training and Simulation

05 April 2022

R&D case: Flexible and scalable future training

The challenge The PC-7 training aircraft of the Royal Netherlands Air Force (RNLAF) needs to be replaced. A Training Needs Analysis (TNA) and Training Media Analysis (TMA) were therefore done, aiming to provide a solution for the replacement of the entire initial training capacity. This training capacity needs to be flexible and scalable to meet […]
Competency-based maintenance training
Training and Simulation

23 September 2022

R&D case: Competency-based maintenance training

Development of maintenance training as a result of changed regulations The challenge The development of the European Military Aviation Regulations (EMAR) resulted in changes in the Dutch military aviation regulations. The content and levels of the maintenance type training for the F-16, AH-64D, CH-47D/F and the NH-90NFH therefore needed to be updated. Moreover, the training […]
Training and Simulation

17 September 2022

R&D case: Augmented reality for maintenance training

Problem-based training with increased trainee activity The challenge KLM expressed the need for more innovative training media to modernize and improve maintenance training. The solution The result of the project is a modernised, problem-based maintenance training design that enhances understanding of the systems and system interaction. This design comprises less traditional instruction and more trainee […]
LVC for Joint and Combined Air Power
Training and Simulation

26 October 2022

R&D case: LVC for Joint and Combined Air Power

Live, Virtual and Constructive elements in one training environment The challenge LVC incorporates Live, Virtual and Constructive elements into a single training environment. Conducting seamless LVC exercises remains one of the most challenging issues in modelling and simulation for modern air forces. There is insufficient interoperability, limited reuse and loose integration between the Live, Virtual […]