The term chunking was introduced in a 1956 paper by George A. Miller, The Magical Number Seven, Plus or Minus Two : Some Limits on our Capacity for Processing Information. Chunking breaks up long strings of information into units or chunks. The resulting chunks are easier to commit to working memory than a longer and uninterrupted string of information. Chunking appears to work across all mediums including but not limited to: text, sounds, pictures, and videos. Perhaps the simplest example of chunking is a phone number as displayed in Figure 1.
Without chunking, the number is hard to remember.
1 604 755 9385
The breaking down of the number into more “logical” chunks makes the number easier to remember.
1 (604) 755-9385
The addition of deliminators can also make the chunking process even more effective.
In his original paper, Miller proposed that the maximum number of items (one number in a phone number would be an item) that should be chunked is 7 +/- 2. In other words, chunking enhances working memory most effectively when a string of information is broken into chunks of five to nine items.
More recently, Miller’s contemporaries such as Broadbent (1975) have suggested that the working memory capacity is actually 4-6 items and others like LeCompte (1999) have argued for as few as three. In practice, a range of three to six bits (4+/-1) appears ideal for interaction design. To validate this practice, consider Figure 2 which examines different size chunks in the context of an Operating System License Key (this is a random number and not an actual key).
An example of chunking that is > 7 +/- 1
An example of chunking that is = 7 +/- 1
B17JQ X84ME HP3JC XQV74 QLVBE
An example of chunking that is = 4+/- 1
For most people, the last example would best facilitate a quick glance at one chunk of information, placement of the chunk in working memory, and the data entry of the chunk into the license key field. The end user could then repeat this process for the remaining four chunks.
The primary purpose of chunking is the enhancement of working memory. Chunking, therefore, should not be used when the information must be searched, scanned, or analyzed. Search engine results are an example of information that does not need to be memorized and therefore should not be chunked. If one where to constrain the number of results per page to five (4+/-1); then the end user could actually spend more time moving back and forth between pages (searching), comparing the various definitions (scanning), and deciding on the most appropriate definition (analyzing).
In short, Chunking should not be used as an argument for improved simplicity, legibility, or uncluttered page design. Many novice interaction practitioners unwittingly apply chunking in this manner (Bailey 2000) when they:
None of the above examples are a valid use of chunking and arguably such misapplication of the chunking principle has led some to dismiss chunking as little more than a “superstition” (Bailey 2000) or an “Urban legend” (Jones 2002). This is not to say that the above constraint should not be applied for other design reasons, rather that “the limits on our capacity for processing information” as described by Miller and others are not a proper justification in this context
Chunking is ideal when specific information must be memorized for later use. E-learning applications should make liberal use of chunking to aid in end-user memorization. Chunking is also ideal in environments where an interface must compete against other stimuli for the attention or working memory of the end user (car navigation systems, cell phone, public kiosks). Consider a health practitioner in an emergency room scenario. They are often:
In the above environment, effective use of chunking can improve the usability and effectiveness of an information system. In Figure 3, the left hand column (Column A) does not use chunking while the right hand column (Column B) does. Of the two scenarios, Column B makes it much easier and faster for a health practitioner to focus on and memorize the Patient ID, especially when faced with the sensory overload of an emergency room.
Column A - Without Chunking
Column B - With Chunking
Name: Joe Smith
Patient ID 6782 9023 4
Name: Joe Smith
DOB 02 / 11 / 1973
Chunking, when applied in its proper context, is a subtle but powerful design principle that can help improve the overall usefulness of systems. The primary goal of chunking is to help in situations where the commitment of information to working memory is required. Chunking helps in this process by breaking long strings of information into bit size chunks that are easier to remember, especially when the memory is faced with competing stimuli.
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