Application of chunking to the design of complex information displays

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1990-04-05
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Virginia Tech
Abstract

Chunking is defined as the process of organizing information into multi-item clusters appropriate to solving a particular task. It was hypothesized that dynamic information displays could be formatted to group related items. This formatting would facilitate chunking and, in turn, serve to reduce task difficulty. Two novel display grouping formats were evaluated. In Tight Spatial Proximity, iconic symbols belonging to the same class were rearranged so that they were located proximally on the display. In Chunks-In-Sequence (CIS), symbol classes were presented sequentially, but all members within a symbol class were presented simultaneously.

Ten individuals participated in Experiment 1. During a trial, 2 to 25 symbols (e.g., cannon, radar, etc.) were presented briefly on a computer display. Displayed symbols were sampled from a larger symbol set (Le., 64 total symbols) representing eight unique symbol classes (e.g., military, highway signs, etc.). Participants then viewed a prompt and responded "yes" or "no" to indicate whether the probe symbol was a member of a class that had been presented during that trial. Results indicated that grouping formats helped participants chunk symbols into appropriate classes and solve the classification task with reduced error rates and subjective workload.

Experiment 2 was similar to Experiment 1, with the exception that participants were tasked to remember each symbol presented during a trial rather than just the symbol class names. This task required forming chunks, storing them in memory, and then parsing the chunks into component items. Results indicated that display grouping formats reduced subjective workload, but not error rates.

Considering both experiments, it is concluded that spatially or temporally grouped symbols can be chunked more easily than information displayed in a non-grouped format. However, grouping formats will not help operators parse these information chunks given detailed component recall demands.

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