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Retention and Comprehension of Information
Published in Robert W. Proctor, Van Zandt Trisha, Human Factors in Simple and Complex Systems, 2018
Robert W. Proctor, Van Zandt Trisha
Strings of digits are often used for such things as telephone numbers, bank accounts, customer identification, and so on. From a customer’s perspective, these numbers are essentially random. It is very difficult to remember random strings of digits, so chunking is an important strategy that can be used to remember them. Some important chunking strategies involve the size of the chunk and the modality in which the information is presented. Wickelgren (1964) showed that lists of digits are easiest to remember if they are organized into groups of a maximum of four. Grouping provides a better benefit when digits are presented auditorily rather than visually, because people tend to chunk visual digits into pairs even when they are not grouped (Nordby, Raanaas, & Magnussen, 2002).
Collaboration, Training, and Pattern Recognition
Published in Michael P. Letsky, Norman W. Warner, Stephen M. Fiore, C.A.P. Smith, Macrocognition in Teams, 2017
So what are the appropriate structures to be shared for human group cognition? We believe a chunk representation is the most appropriate stimulating structure for collective pattern recognition and communication due to its superior cognitive alignment. However, it is possible that any portion of the recognized pattern might be a suitable stimulating structure. For example, if one were trying to communicate about a room in a house, using the word ‘kitchen’ would facilitate the memory retrieval of a ‘kitchen’ chunk, complete with sink and all the appliances. However, another way to represent this room might be to communicate sink, refrigerator, stove, dishwasher, cupboard, etc; the discrete elements. Both imply similar amounts of information, yet a difference in cognitive alignment and retrieval from memory. Research suggests that the chunk representation can be retrieved faster and with less effort, because it uses fewer cognitive resources.
Memory and Training
Published in Christopher D. Wickens, Justin G. Hollands, Simon. Banbury, Raja. Parasuraman, Engineering Psychology and Human Performance, 2015
Christopher D. Wickens, Justin G. Hollands, Simon. Banbury, Raja. Parasuraman
Chunking may also be facilitated by parsing; that is, by physically separating likely chunks. The sequence 4149283141865 is probably less easily encoded than 4 1492 8 314 1865, which is parsed to emphasize five chunks (“for Columbus ate pie at Appomattox”). For an imaginative reader these five chunks may be “chunked” in turn as a single visual image. Loftus, Dark, and Williams (1979) investigated pilots’ memory of air traffic control information and observed that four-digit codes were better retained when parsed into two chunks (27 84) than when presented as four digits (2 7 8 4). Bower and Springston (1970) presented sequences of letters that contained familiar acronyms and found that memory was better if pauses separated the acronyms (FBI JFK TV) than if they did not (FB IJF KTV). Finally, Wickelgren (1964) found that our recall of telephone numbers is optimal if numbers are grouped into chunks of three digits. Results such as these have led to the general recommendation that the optimum size of grouping for any arbitrary alphanumeric strings used in codes is three to four (Bailey, 1989).
The Unit and Size of Information Supporting Auditory Feedback for Voice User Interface
Published in International Journal of Human–Computer Interaction, 2023
Min Chul Cha, Hyo Chang Kim, Yong Gu Ji
Determining what size of information to provide begins with determining the size of the information unit. Therefore, to adjust the amount of information, the size of the information unit needs to be limited and the amount of information must be determined based on this. Previous researchers believed that the magical number 7 ± 2 was the limit of working memory (Miller, 1956). On the other hand, Baddeley and Hitch (1974) proposed 2s limits for a phonological rehearsal loop, and they implied that chunks could extend beyond the words. However, as opposed to this, Cowan (2001) proposed the small size of chunks, the magical number 4. Although there have been discussions on the various size of chunks, they had the common result that the size of the memorizing item could be expanded through chunking. Therefore, to understand the form and amount of information that users need, it was necessary to study not only the unit in which chunking occurs but also the size of the unit affected by the chunking mechanism.
An Edge Computing Unloading Algorithm for IIoT-based Mobile and Internet of Vehicles (IoV) Applications
Published in IETE Journal of Research, 2022
In [13], the authors state that limited computing power in the vehicular networks, delay in task processing, and over utilization of energy are the basic problems in IoV. Based on the tasks and their respective features, the tasks are divided into manageable chunks. Binary offloading in a combination with partial offloading is proposed. The binary offloading optimizes the delay and energy consumption when processing the tasks with high computational needs. In [14], the study proposes a solution for IoV task offloading using mobile edge computing based on the application needs. The proposed study reduces system overhead and minimizes the execution time of IoV tasks. In [2], a dynamic task offloading scheme for IoV based on reinforcement learning is proposed. By combining the benefits of deep networks and reinforcement learning, it uses the best of both algorithms. The research outcome minimizes delays, optimizes energy consumption, and reduces the system overheads.
Software Innovations to Support the Use of Social Media by Emergency Managers
Published in International Journal of Human–Computer Interaction, 2018
Linda Plotnick, Starr Roxanne Hiltz
Miller’s “magical number seven plus or minus two” has been noted by Eppler and Mengis (2004) as a very significant perspective when considering information overload. Miller describes several techniques for trying to mitigate this limitation, including the idea of “organizing or grouping the input into familiar units or chunks” (Miller, 1956, p. 93). The idea is that more information can be processed, remembered, and understood, if it is “chunked” so that the individual pieces of information in a chunk are related. Miller claims that the critical dimension of the information is the number of chunks and not the amount of data contained within each chunk. It is noteworthy that in his article, Miller discusses an experiment that showed that when subjects were told ahead of time what attributes were being considered with data, they made more accurate judgements on the attributes than when they were informed of which attributes were to be judged after having observed the data (Miller, 1956). This suggests that technological enhancements to SM that “chunk” SM data into groupings that are identifiable by the user prior to actual examination of the data may be useful to combat information overload. The technology would be doing what in his 1956 seminal article Miller called “recoding” which he claims “is an extremely powerful weapon for increasing the amount of information that we can deal with” (Miller, 1956, p. 95).