What is cognitive load?
Cognitive burden is the overload an individual experiences due to the amount of mental effort required to perform a task, such as solving complex problems or even making important decisions under pressure. When the demands of a person’s cognitive capacity exceed what can be handled normally, cognitive load can become burdensome and lead to a decrease in performance and an increase in stress. With heaps of technical tasks along with the ever-present issue of technical debt, tech teams are bound to get crushed under the cognitive burden.
Types of cognitive load
There are two types of cognitive loads:
Intrinsic cognitive load
Extraneous cognitive load
Intrinsic cognitive load
Intrinsic cognitive load is the mental effort inherently required to perform specific technical tasks. It is a measure of the amount of brainpower necessary for understanding and executing tasks efficiently. Since there’s a limit to how much cognitive load we can handle at any given time, more complex or mentally demanding tech projects carry a higher intrinsic cognitive load. For example, for software developers, working with a new programming language directly results in increased intrinsic cognitive load.
Extraneous cognitive load
Extraneous cognitive load is the type of cognitive burden that arises from the surrounding environment rather than from directly engaging in a task. This cognitive burden involves additional activities that support the main objectives, such as the logistical and operational aspects of software delivery. While these additional tasks might be necessary, they add an extra layer of cognitive load on tech teams.
Cognitive load and tech team performance
Flow state is a state of deep concentration where individuals are fully immersed in a single task. Tech teams, especially software developers, aim for a flow state for tasks that require undivided attention, such as coding. This intense focus is vital for tackling complex technical challenges along with bringing innovative designs to life. When tech teams are able to achieve the flow state during upskilling, they can make significant strides in their projects. However, due to workload and tight deadlines, the extra cognitive load can affect this flow state negatively, directly impacting tech team performance. In no time, the effects of cognitive load will start to appear in tech teams. Some of the effects of cognitive load are as follows:
Reduced developer productivity
Decrease in focus at work
Ways to reduce cognitive load
Upskilling programs are notorious for being challenging, so L&D teams need to employ techniques to lessen the cognitive load on their tech teams during their upskilling training program. Some of the techniques are as follows:
Prioritizing tasks
Avoiding technical jargon
AR and VR training
Prioritizing tasks
Engineering managers must assign tasks to their tech teams depending on their priority. The tasks that deliver the highest-level outcome must be on urgent calls, while other side projects that can be excused should be identified early on so that no time is wasted on them. Many teams have made use of the time management matrix to sort out their tasks that directly contribute to the overall upskilling’s main goals. For example, if a tech team is taking a course in mobile application development and the focus is on user experience, then only the features that serve the primary objective should be on top of the tasks. This strategic focus is key to delivering successful outcomes that meet the upskilling’s primary objectives.
Avoiding technical jargon
The tech industry is cluttered with specialized jargon. While those immersed in the field might be familiar with many of these terms, it’s important to remember that not everyone will have the same level of understanding. The pressure to learn new terminology can significantly increase the cognitive load on tech teams that already have a comprehensive list of terms to comprehend and then implement in their training. This heightened cognitive load can hinder their ability to grasp new concepts effectively and can lead to feelings of overwhelm and frustration. When explanations and instructions are given in clear, straightforward language, it reduces the mental effort required to understand new concepts. This approach doesn’t mean avoiding technical terms altogether but rather ensuring that they’re accompanied by clear explanations when they’re used.
AR and VR training
Visual aids play a crucial role in simplifying complex ideas. Technological concepts such as quantum computing are generally abstract, and trying to understand them through long texts can obstruct the purpose of upskilling. For this reason, L&D teams must make use of AR and VR training in their upskilling program because these methods engage multiple senses, thereby significantly enhancing memory retention. For example, when working on software architecture, software engineers would find it more feasible to immerse themselves in diagrams and take a closer look at them for examination. Similarly, when explaining the concept of a network protocol, instead of relying solely on textual definitions, a trainer might use a diagram to illustrate how data packets move within a network. Incorporating such methods into upskilling programs can transform the learning experience. It bridges the gap between theory and practice, making even the most daunting technical topics more accessible and easier to grasp, which leads to a reduction in cognitive load.
Final word
L&D teams must adopt an instructional design that aims at catering to the types of cognitive load of the tech teams during the upskilling program. For tech teams, balancing this load is crucial for optimizing team performance and fostering an environment conducive to creativity and innovation.
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