Using schemata to improve usability

Schemata are existing knowledge that users develop. These are developed through established norms that designers create. Users learn these schemata and recognize them as patterns. This has the advantage that users can skim a display faster and with less effort, as they are familiar with the schemata. Because this method requires less cognitive effort, users can focus their energy on displays and values that do need more attention.

Designers convert raw quantitative data into visual displays so they can be easy understood and consumed fast. The act of converting raw data is called encoding. Designers use various methods to encode data to make it meaningful and sensible.

Designers know which visual display methods represent a data set best. They select the appropriate graph (for example bar graphs, pie charts, tables) to represent the body of data and numerical values (for example KPIs) to be interpreted.

When doing so designers take care that the size and visual encoding of the elements within a graph accurately reflect the data and correspond with the values to be displayed. For example a bar might as showing a value greater or smaller than it is. Designers also take into consideration to make sure that no optical illusions occur that could distort the way the data is interpreted. A good example is the Deboef illusion.

Designers basically make choices in regards to display selection and encoding in order to avoid giving the wrong impression which could lead to false judgement and poor decisions.

How users really read

With the rise of online media, and increase of created content, and the fact that every knowledge doubles incrementally (depending on industry or discipline ranging from 12 months to every 5 years) reading behaviour has changed significantly since 1900, when Buckminster Fuller created the “Knowledge Doubling Curve”.

People have adopted to scanning and skimmin what is displayed on their monitors. Text doesn’t get read to full extend, as we all know from how we read emails on a daily basis.

When designing dashboards, designers keep this in mind, and condense the information that it can be interpreted when skimming the screen. One way designers achieve this is by establishing certain norms and patterns and continue sticking to them consistently.

Readers and users learn these norms as schemata (or patterns) which enables them in the long term to consume the information even faster and focus their cognitive efforts on all data that requires more attention. An example of this is the location of where specific information can be found.

Schemata are established norms that designers create. Users learn these schemata and recognize them as patterns, from which they develop expectations. These schemata also help users to make sense of their environment and what they see.

Schemata have the advantage that users can skim a display faster and with less effort, as they are familiar with the pattern. Because this method requires less cognitive effort, users can focus their energy on displays and values that do need more attention.

Factors that affect attention

Attention is not always available in the same amount. There are multiple factors that affect attention in users. According to schema theory (Samuels, 1994, reading comprehension) there are three characteristics of internal attention:

  1. alertness (the active attempt/cognitive effort taken to access schemata of relevancy)
  2. selectivity (the ability to focus, isolate, and attend relevant information despite the presence of distractors)
  3. limited capacity (the amount of cognitive energy readers have available to attend to the relevant information)

Keeping this in mind designers can take advantage of this knowledge, as they can ensure the users attentional resources can be used effectively when reading a dashboard.

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