One question that most people have when first learning about visual memorization is how to get started. Because of the large number of options, one of the common answers is either to “use what I’m using” (the marketing approach) or to use the most recommended systems (the safe approach). This usually gives the impression that memorization systems are simple. I haven’t found that the choices are.
A useful analysis tool for me to understand the big picture of large systems has been a decision tree. There are various styles, but I’ll pose this in an outline type style first for discussion. This should help a person select the best system in my opinion for their needs but in all cases, you must know your problem first before you can answer the questions.
I’ve already made a metric-based summary of number pegs because of the needs of competitive athletes but will provide direction here more on experience and understanding. My experience is based on understanding and using the SEA-IT data types and the difference in associations between those types in a memory image or visual sentence and when used to form associations between multiple visual sentences.
SEA-IT is an acronym for the five main visual data types that create a complete visual sentence. They are:
- Subject (party, person, group, organization, role, living thing, fictional character)
- Enhancements to the subject (tools, costume, emotion, shape, size, body features, superpowers), the action (speed, scope, severity, associated emotion, associated item), the item (texture, size, color), or the terrain (weather, plants, animals, time, water and geologic features, domiciles).
- Action (a strong verb causing an effect on the item)
- Items being acted on, preferably animated but can be inanimate.
- Terrain or location.
A visual sentence is a group of associated visual images that allow the maximum amount of detail aiding recall. The basic visual sentence follows the English structure of subject-verb-object and includes enhancing detail for the subject, item and a terrain, also known as the SEA-IT data types.
(words, simple numbers, concepts, people’s names, landmarks)
You will be creating a visual sentence by associating the different types of SEA-IT data so that it becomes a sentence easily visualized. Sometimes this is called the link or chain system but would not be applied to a group of visual images. Each association within the sentence is independent of other visual images.
To remember things without a good image to remember, practice using your imagination to discover visual images for a word or words that sound similar or have a good relationship to the word or name.
Numbers up to three digits can be managed to be translated into sounds that then become a word of a memory image. The Major, Dominic, and the Ben system are popular translations of digits to sounds. The sounds are then translated into an image. Popular lists of these numbers are used as pegs so it’s good to learn the default one-digit number pegs. Two-digit number pegs are even more useful to create fewer complex images. Most styles translate to items with the decimal point being handled by design or an image like a pebble. If your number is long, such as pi, it is interpreted as an ordered set of two- or three-digit groups.
Another technique for up to two digits is to associate the shape of the number with an item. Other lesser techniques use associations with subjects, enhancements, actions, or even terrains.
An acronym may help by taking the first letters of each word of a group of words and remembering that. Another technique is to substitute words with the same first letter into a memorable phrase.
Some sequences of letters and symbols can be associated with a memorable phrase where each letter starts a word in the phrase.
Learn how to see a person’s or the landmark’s features as one data type and associate it to a memory image comprised of the other data types.
Learn about templates, which are a small set of pegs that represent consistent sets of data storage possibilities associated with any other piece of data to provide a familiar, easy to recall, group of associations.
(alphabetic, numeric, dates, positional)
You will be creating multiple visual sentences by first associating the different types of SEA-IT data so that it becomes a sentence easily visualized and then combining the sentences together by narrative or a rule-based system. The term link or chain system is also used to describe a narrative association of sentences. A peg system is when you use a rule-based system. And a method of loci system is when you use any kind a system based on terrain.
(lists of people, numbers, items, locations, words, names).
You will be using a rule-based system of some sort. Each visual sentence that is stored will have an accompanying image, called a peg, that will allow you to find the image you need. Pegs can be ordered sets of subjects (alphabetic lists of animals, birds, insects, names of people, roles of people, imaginary subjects), items (alphabetic lists of food, objects, shapes; Major/Ben ordered objects), and terrains (alphabetic or Major/Ben ordered lists of countries, states, cities; rooms, buildings, paths, complex objects, or film scenes ordered by position or time.
Pegs win over narratives for flexibility and reuse, but suffer slightly for speed in competition because they require an extra step of mental exertion to make another association.
You need to have one or more solid peg systems in place to help keep associations that should erode over time until you need it again.
A few good peg systems that are easily reused are essential. Numerically sorted items are important so start with some objects for number pegs. Then maybe a bestiary for alphabetically sorted lists. All sorting methods can use any data type so think about using others like a numerically sorted list of terrains. One of the most popular peg systems is room positions sorted by clockwise location.
A pattern, the synced peg, allows you to grab two or more of the five main data types. It is very helpful in quickly combining images for a visual sentence. The PAO is the most common form of the synced peg that usually is anchored on the subject so that other data types can be associated to it. But other forms of synced pegs could be formed from other anchors such as the number or letter of the row of data, the item, or the location. When remembering an item, the subject or location anchored PAO is best. The image is then stored by another peg system, usually a location peg.
The type of peg system you choose here will not be as generic and can be tailored to the information that you organize including special templates to group data before storing the images. Design time will increase your ability to recall and decrease the number of images you store.
Take your time and organize your information well. Find the key types of data that need to be remembered and associate one of them with a specific visual image data type if possible. Use an appropriate peg system that has some relevancy to your information.
The index peg is a way of adding another peg list to a list of data items so that, as a prefix, it creates a new type of peg for each index peg you use. The index peg usually consists of one of the five major data types such as a person’s profession or point in time, or a location.
Another way to multiply your available storage areas is to double up your systems so that a peg system supplies the initial image in another narrative or peg system chain of visual sentences.
The paired peg is several different peg lists that all have the same length and are not associated with each other. But in associating the different types of data to see what the result might be, a new concept might be created.
(ceremonies, speeches, dialogs, history, lists of digits, locations by travelling).
You will be using a narrative system of some sort. A rule-based system, or pegs, will give you the ability to go from start to finish also and additionally start at any point in the list. Any narrative can be blended with a peg system to allow for randomly retrieving a visual image.
Verbatim text is best broken up into phrases that create visual sentences. Those phrases are then associated with each other in order in a meaningful story. Much review is needed to keep the words familiar and exact.
A speech or ceremony could be visualized on a rock, a shell, a colorful legal pad folder, or other found or created memory object. A story could be created that was associated with a series of people you meet along the way in your story. You would be the protagonist subject in this story. And a walking trail could be the trigger for multiple ideas as you reach each point of remembrance.
Any list of digits is usually chunked into two- or three-digit chunks and then images created by translating the digits to sounds and then to images which are placed in a journey or a palace (location peg systems, aka method of loci) where each position contains one or two of the images. An interesting technique is to create a phrase where each word has the number of letters of the digit it represents.
Locations have features that can become or interact with a main subject so that a story can be created as you move along the journey.
This is the first draft of the decision tree and I may make changes to it which will be stored in my document repository for memory related items. The glossary there will make my terms clearer and has many examples. If anyone has improvements, I am more than willing to take suggestions to help improve this tool.