CS 7643 QUIZ 3 ACTUAL TEST SCRIPT 2026
VERIFIED SOLUTIONS
◉ Pre-attentive Processing. Answer: refers to our ability to
immediately recognize variations in some visual property with little
to no conscious effort (automatic recognition)
◉ bottom-up processing. Answer: Is pre-attentive as known as
bottom-up or top-down processing
◉ Attentive Processing. Answer: refers to situations where it takes
some deliberate mental effort to perceive visual differences
◉ top-down processing. Answer: Is attentive processing as known as
bottom-up or top-down processing
◉ goal-driven. Answer: Is attentive processing saliency-driven or
goal-driven
◉ saliency-driven. Answer: Is pre-attentive processing saliency-
driven or goal-driven
,◉ using a mix of open and closed shapes. Answer: what is one way
you can turn attentive tasks to pre-attentive takes
◉ things pop out, draws attention by highlighting something
important - allows people to make comparisons between groups
quickly. Answer: what are reasons to use pre attentive processing
◉ the dangers of using pre-attentive. Answer: can lead to
unintended visual patterns being recognized immediately, people
can be biased towards seeing what they deem intuitive
◉ the sine illiusion. Answer: our visual system has been trained to
find the shortest distance between two lines
◉ t/f: just optimizing visualizations for visual precision is enough.
Answer: false (we need to think about why we want to visualize data
in a particular way)
◉ true. Answer: t/f: we visualize data to optimize for a specific user
task
◉ action, target. Answer: we engage with real-world objects as
<____,____> pairs, and we do the same for data visualizations
, ◉ Taxonomies. Answer: structural decompositions of concepts that
help us understand categories and their relationships
◉ Stasko Taxonomy: Low-level components of analytic activity in
information visualization. Answer: focused on the intents and goals
people have rather than the user interface
◉ affinity diagramming. Answer: a visual tool that helps you
organize information by sorting ideas into different groups or
categories based on their relationship to another
◉ Retrieve Value Task. Answer: given a set of specific data cases, find
attributes of those cases (ex: how long is the movie Gone with the
Wind; What is the mileage per gallon of the Toyota Rav4)
◉ Filter Task. Answer: Given some concrete conditions on attribute
values, find data cases satisfying those conditions (ex: Which
Kellogg's cereals have high fiber; Which comedies have won awards)
◉ Compute Derived Value Task. Answer: Given a set of data cases,
compute an aggregate numeric representation of those data cases
(ex: What is the gross income of all stores combined; what is the
average calorie content of Kellogg cereals)
VERIFIED SOLUTIONS
◉ Pre-attentive Processing. Answer: refers to our ability to
immediately recognize variations in some visual property with little
to no conscious effort (automatic recognition)
◉ bottom-up processing. Answer: Is pre-attentive as known as
bottom-up or top-down processing
◉ Attentive Processing. Answer: refers to situations where it takes
some deliberate mental effort to perceive visual differences
◉ top-down processing. Answer: Is attentive processing as known as
bottom-up or top-down processing
◉ goal-driven. Answer: Is attentive processing saliency-driven or
goal-driven
◉ saliency-driven. Answer: Is pre-attentive processing saliency-
driven or goal-driven
,◉ using a mix of open and closed shapes. Answer: what is one way
you can turn attentive tasks to pre-attentive takes
◉ things pop out, draws attention by highlighting something
important - allows people to make comparisons between groups
quickly. Answer: what are reasons to use pre attentive processing
◉ the dangers of using pre-attentive. Answer: can lead to
unintended visual patterns being recognized immediately, people
can be biased towards seeing what they deem intuitive
◉ the sine illiusion. Answer: our visual system has been trained to
find the shortest distance between two lines
◉ t/f: just optimizing visualizations for visual precision is enough.
Answer: false (we need to think about why we want to visualize data
in a particular way)
◉ true. Answer: t/f: we visualize data to optimize for a specific user
task
◉ action, target. Answer: we engage with real-world objects as
<____,____> pairs, and we do the same for data visualizations
, ◉ Taxonomies. Answer: structural decompositions of concepts that
help us understand categories and their relationships
◉ Stasko Taxonomy: Low-level components of analytic activity in
information visualization. Answer: focused on the intents and goals
people have rather than the user interface
◉ affinity diagramming. Answer: a visual tool that helps you
organize information by sorting ideas into different groups or
categories based on their relationship to another
◉ Retrieve Value Task. Answer: given a set of specific data cases, find
attributes of those cases (ex: how long is the movie Gone with the
Wind; What is the mileage per gallon of the Toyota Rav4)
◉ Filter Task. Answer: Given some concrete conditions on attribute
values, find data cases satisfying those conditions (ex: Which
Kellogg's cereals have high fiber; Which comedies have won awards)
◉ Compute Derived Value Task. Answer: Given a set of data cases,
compute an aggregate numeric representation of those data cases
(ex: What is the gross income of all stores combined; what is the
average calorie content of Kellogg cereals)
