Semantic Coding (Definition + Examples) - Practical Psychology (2023)

Encoding, the conversion of sensory information into memory, is an essential process that humans need for everyday tasks. Semantic encoding is one of the ways we assign meaning to the raw data around us, which can then be stored as memory and retrieved later.

Semantic encoding is a cognitive process in which we encode sensory input from our environment to give it meaning. Sensory information about our environment is converted into a meaningful way to remember. It is one of the first steps in memory encoding.

Semantic encoding is one of the best ways to remember things and retrieve them later. Several proposed models explain how concepts are organized in the brain and we use these structures to encode meaning.

What is semantic encoding?

Semantic encoding is when the braintakes information from our senses and encodes it into meaningful information🇧🇷 In this way, the perceptual aspects of the data obtained from our environment are not in the foreground.

The word encoding also needs an explanation. Encoding refers to converting sensory information into a form that can be processed and remembered. In semantic encoding, sensory information is converted into meaning that can be applied to a context.

Semantic encoding allows us to understand the world around us. It is a kind of cognitive coding that provides the experience of understanding the meaning of things we encounter in everyday life. Sensory information can come from any of our senses: touch, hearing, taste, sight, or smell.

An example is information about the meanings of words. When someone says the word /cat/ to you, you immediately know what they are referring to and can understand what it means in a given context. The meaning context of the information is essential for semantic encoding. It can affect the way we remember certain concepts.

Another meaning can be reading written information. For example, when reading the word /chá/, you can encode the meaning in the context in which it occurs, in this case a phrase or phrase. Tea refers to the context of drinking, pouring, brewing, etc.

How about a word with two different meanings like crane? It can refer to the bird or to the machinery used in construction. So if someone yells, "Look at that crane flying over there," you'll surely understand that it's the bird. Semantic encoding helps us encode what meaning is relevant using the given context.

Semantic encoding can also be linked to deep encoding, as it plays an important role in memory encoding, especially long-term memory.

Role of semantic encoding in memory

Semantic encoding is one of four types of encoding that fall under the main term: memory encoding. Memory encoding is when input from our environment is converted into a form that can be stored in the brain and retrieved in the short or long term.

Semantic encoding plays a crucial role in memory encoding, as it is the process of assigning meaning to certain items. ThisThe meaning can be stored in the brain to be remembered.whenever you need to use the information. The other three types of memory encoding are visual, auditory, and elaborate encoding.

Studies have shown that semantic encoding can make information easier to remember. Storing and retrieving memories is produced by making sense of things more easily than by not making sense of them.

Imagine reading a text message from a friend that says, "See you later." In that context, what do you know, then you meet your friend for tea. Semantic encoding ensures that, in this context, you remember the meaning of the written words, rather than just remembering the words themselves.

Another example of semantic encoding in memory is remembering a phone number based on an attribute of the person who obtained it, such as B. their name. In other words, certain associations are made between the sensory input (the phone number) and the meaning context (the person's name).

semantic coding models

Researchers have proposed some models of semantic coding to suggest how it works at the neurocognitive level.Collins and Quillian network modelit is a well-known model and can be considered one of the best understood.

Collins and Quillian network model

This model was developed around 1969, and the theory proposed a semantic network in the brain that closely resembles a spider's web. This network roughly represents information in the form of various concepts.

On the web, different nodes relate to key concepts (or meanings), and then some links between nodes make connections between concepts. For example, imagine that the central node (middle of the web) is a "mammal".

A mammal can link to various other pieces of information and receive links from other nodes. These connections are seen on the web as arrows pointing from one concept to another. For example, the mammal node may be connected to another node called "animal" with the connection between the two representing "is a" (mammal is an animal).

Another connection could be that a mammal has a vertebra. Thus, we can see that a node (mammal) can have multiple associations with other nodes (representing different meanings, such as animal or vertebra). As the web (the semantic web) continues to grow, more nodes are added and more connections are created between these nodes.

The connections between nodes are a way of organizing the network and making connections between different concepts. In a nutshell, this model proposes how meaning and information can be managed in our brain.

Furthermore, Collin and Quillian said that this semantic network works hierarchically based on linguistics (language). The central node (in this case, mammals) would be the simplest concept, leaving the web to make connections with more complex information (eddies).

Compare the model for semantic features

Un poco más tarde, en 1974, se propuso otro modelo de codificación semántica. El modelo de características semánticas sugirió que la jerarquía no es tan importante cuando queremos organizar conceptos en el cerebro, sino las características semánticas de los conceptos.

The model suggests that you compare these characteristics to determine the meaning of the information. In this model, different concepts are directly compared with each other, instead of assigning many features to one concept.

In the semantic network proposed by Collins and Quillian, the concept of cat would be linked to other concepts such as fur, four legs, pet and ears to understand that it is part of the central concept of "mammal". In this semantic trait model, the concept of a cat would only be compared to other mammals, such as an elephant, where the traits could be four legs, a wild animal, and ears.

With this theory, we can use the similarities and differences between concepts to understand what they are and make sense of them. There is no linguistic hierarchy in which one concept is more complex than another.

Criticisms of semantic coding models

While there are other semantic coding theories, these two have received a lot of attention and criticism. First, the semantic network (Collins and Quillian) has been criticized by cognitive psychologists for being too simplistic.

The suggestion was that semantic coding is more complex in its organization than a hierarchical structure of concepts and associations. However, studies could show that the semantic network model was observed empirically.

One study presented research participants with two different statements: "dolphin is an animal" and "dolphin is a fish," and measured the seconds it took them to answer "yes." The results showed that people generally took longer to respond to the more complex statement further down the linguistic hierarchy.

Therefore, in this example, the participants took longer to respond to the statement “the dolphin is an animal”. The results of this experiment showed that people react differently to certain concepts, possibly pointing to a hierarchical system of concepts and associations.

On the other hand, the main criticism of the Semantic Features model is that it has not been empirically tested to the extent that semantic networks have been.

Ways to optimize semantic encoding

We do semantic coding several times a day, every day. It is a natural way of remembering information with meaningful associations. However, not all concepts are coded in the same way. Some of the information you may find is easy to code, others may be more difficult.

There are two main strategies that we can use to optimize semantic encoding. Why should we do this? When sensory input isn't encoded correctly, it becomes harder to remember later. These techniques can help you remember certain concepts, such as B. studying a challenging topic.

Mnemonics for semantic encoding

mnemonic is aspecific technique involving a device or strategy to aid memory, as acronyms or associations. For example, a popular one uses the acronym ROYGBIV to remember the colors of the rainbow.

Another popular system is the keyword system. This system is when you associate (link) a word that you need to remember with words that are easier to remember. Words usually start with the same letter. The following is an example of theadjustment systemused to aid memory of taxonomic categories in biology (Kingdom, Phylum, Class, Order, Family, Genus, Species) - King Phillip Came Over For Good Soup.

Mnemonic music is a subcategory of mnemonics that uses music and songs to remember concepts. Due to the overlap between music and speech, musical mnemonics are a great way to aid memory and semantic encoding.

Throughout your life, you have probably used musical mnemonics several times, perhaps without realizing it. Children learn their letters and other concepts through songs. Related to this technique is the mnemonic rhyme.

As the name suggests, rhymes are used to memorize information, just like music. The rhyme creates a pattern that can take on a sung structure, helping to solidify concepts in memory.

Chunking for semantic encoding

Chunking is another way to simplify our semantic coding systems. It is about breaking large pieces of information into smaller chunks (chunks). These smaller pieces are easier to remember and are still meaningful.

Fragmentation is a versatile strategy where you can find patterns in the smaller sections that make up the whole while organizing the units into a system. An easy way to think about this is to make a shopping list. The list can contain multiple items, which is too much to remember.

However, if you break it down into smaller sections and then organize it by food department or food category, it will be easier to remember.

A piece can be thought of as one of the puzzle pieces that help put the whole puzzle together. For example, memorizing a phone number can use grouping as a technique. Break the number into smaller parts, and once you memorize each one, it will be easier to put them together.

Where is the semantic encoding in the brain?

Different parts of the brain are responsible for different functions and encode information. Neuroimaging studies have examined where certain encodings and processes occur in the brain. Research is ongoing, but prefrontal cortical regions appear to be activated during tasks that require semantic encoding.

especially theleft inferior prefrontal cortex(including Brodmann areas 45, 46, and 47) was activated during semantic encoding. Furthermore, the left temporal regions are also involved in semantic encoding.

The medial temporal lobe is involved in semantic and perceptual encoding. Activation in temporal regions applies to both verbal and nonverbal stimuli. Depending on the type of sensory input, other areas of the brain are also activated before and during semantic encoding.

The hippocampus is another brain structure that may play a role in semantic encoding. It plays a role throughout the frontal cortex, helping to process and determine incoming sensory information.

Conclution

Semantic encoding is our ability to take sensory information and transform it in the brain to give it meaning. It plays an important role in memory, especially long-term memory. Several models have proposed how semantic encoding works in networks or by comparing semantic features.

references

https://dictionary.apa.org/codificación-semántica

https://www.coursehero.com/study-guides/boundless-psychology/step-1-memory-encoding/

https://www.chegg.com/learn/psychology/introduction-to-psychology/semantic-encoding

https://pubmed.ncbi.nlm.nih.gov/7666172/

https://zapier.com/blog/mejor-memoria/