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The Concept of Deep Processing in Learning

The Concept of Deep Processing in Learning

Whether you are learning how to code or learning how to cook, the way you learn can be as important for retaining and accessing information when you need it as the person that teaches you. For decades, academic researchers have studied the methods of effective learners to try and “crack the code” for successful achievement and knowledge attention. While there are plenty of factors that contribute to learning efficiently and effectively, one of the most important recent discoveries is the idea of deep learning.

Deep processing is, at its essence, the idea that people learn and retain information better when they are actively interested and engaged in content matter. While this seems like common sense, there are a surprisingly large number of variables that contribute to whether you are truly engaged in deep processing. Fortunately, learning science has started to isolate some of the factors that any student can control to access deep processing and make the most of a coding class, or any academic program.

So how do you transition from shallow to deep processing, to truly get the most out of any academic program you enroll in? Are there techniques to make deep processing more likely? Let’s take a deeper dive into deep processing, and talk about some of the principles that can help you master the technique for yourself.


Where Does The Concept Of Deep Processing Come From? 

The concept of deep processing was actually born out of research decades ago, as psychologists began to study brain function and processing to improve attention span in a variety of areas. One of the essential findings of these early psychological experiments was the importance of “meaning” -- the value a particular learner ascribes to content and whether it is important to them or affects them personally.

Psychologists found that deeper levels of analysis are consistently associated with more elaborate, longer lasting and stronger memories. These processing levels can be viewed as a continuum: at one extreme, some brief sensory input like a sight or a sound will lead to memory traces that are transient and easily disrupted. Conversely, at the other end of the continuum, the process of deep semantic analysis can lead to a more permanent memory that is more easily accessed later or when needed. 

This 'levels' approach assumes that data or info that seems immediately meaningful to an individual is more easily remembered because it is compatible with previously existing thoughts or beliefs (i.e. it is easier for a student to make a connection to previous understandings or beliefs). Because of the ease of this connection, such material will be easier to process to deep levels. 

But what if you are learning something new, such as a new programming language or algorithm to develop a piece of software? Depth of processing is actually affected by several things: the amount of attention given, the relation to existing cognitive structures, and the amount of time available for analysis. By creating a learning environment that combines these factors, you can better access deep processing in any content environment.

Deep Processing Strategies You Can Use

Now that you know the concept of deep processing, the next question is -- how can you use specific strategies to achieve it for yourself? Fortunately, there are a number of concrete steps you can take when learning a subject to access deep processing and retain information. Here are just a few:

Elaborate the Information 

The idea behind using the elaboration technique is to create meaningful associations between different concepts you’ve studied, no matter what the subject. When you are given new information, begin by asking yourself in what ways this relates to information you already know. 

This helps your brain construct pathways where new information can “live” within your brain. For example, even if you are learning fundamental coding techniques like arrays or libraries, always try to find analogies to concepts you are familiar with (for example, a programming library is similar to a physical repository of information). This can make the information “match” existing information in your brain more easily.

Make Distinctions 

Distinction involves finding ways to create a clear contrast between other concepts and the concepts you are currently learning and studying. Another way to think of distinction is the traditional high school essay model of “compare and contrast” -- evaluate two concepts side by side, and consider areas of similarity but more importantly, areas of difference. This can help your brain categorize new information and effectively store it in a unique location, making recall and application of that information at a later date easier.


For general content information, application involves finding ways to actually use and employ content you have learned in real-life settings. In coding, this is most often done by actually applying concepts you have learned in a coding class to build a particular project or solve a particular coding challenge. SoloLearn, for example, offers code challenges and a code playground specifically to allow those learning to program the opportunity to actually build things and see fundamental coding concepts (like algorithms or data structures) at work. 

By actually using the information, not only do you see the value behind it, but you can also translate textbook concepts into real-world situations that help prove the meaning behind it. And remember, meaning is everything when it comes to achieving deep processing.

Explore the Information 

In modern education, the drive toward “project-based learning” is actually a reflection of the importance of allowing students to explore information that is presented in a classroom setting. Exploring involves taking ownership over concepts you have learned about, and digging deeper into potential new understandings or applications of that information. Exploring is also tied to the idea of experiential learning - that you may make more interesting discoveries around class concepts by removing yourself from a structured learning environment and playing around with the concept yourself. Another benefit of this approach is that it helps learners figure out what they don’t know or need more help with, which lets you develop questions to bring to a teacher or mentor for more guidance.

How Should Deep Processing Inform How You Learn To Code? 

Since there are dozens of options for learning to code, knowing the value of deep processing can help you narrow down which coding academy or academic course program will give you the most fulfilling learning experience. While there are plenty of successful code-learning programs of all types, some of the best ones (the ones that keep deep processing front and center in their teaching) will usually include:

  • A focus on teaching information in easy-to-understand modules or chunks, to give learners time to process each important chunk of information at a deeper level
  • A mix of traditional instruction and hands-on experience, to allow you to progress from finding meaning yourself to discovering value from the application and exploration methods
  • Unstructured “play spaces” like code playgrounds that allow coding learners to experiment and think for themselves, without the stress of a structured learning environment
  • A focus on teaching the applications and practical use of different coding concepts, to avoid simply lecturing students and simply engaging at a shallow processing level