COGNITIVE MODEL AND
EXPERIMENTS OF THE
EFFECT OF HINTS ON
IDEA GENERATION
Hint Study
• Participants given 30 min to come up with ideas to
improve the university
• 4 Conditions
• Hints given every 30 seconds for first 10 min
• Hints given every 30 seconds for the middle 10 min
• Hints given every 30 seconds for the last 10 min
• No hints given
Data Collected
• Recorded the time each idea was entered and each hint
was given
• Coded the ideas given for feasibility and effectiveness
• Assigned each idea generated to one of 26 categories
Analysis
Ideas Generated
We first analyzed the average
number of ideas generated by
the participants in each interval
Our current goal is to get the
output from our model to match
the trends we saw in the
experimental data
Categories
• 26 Categories
• Found frequency of each
category
• 6 Common Categories
• 7 Semi-Common Categories
• 13 Uncommon Categories
• Counted number of
transitions participants
made between categories
Transition Table
• All zero values replaced with 0.01
• Diagonal shows probability of staying in the same category
• Transition table is the input for the model
Model
• Developed by Vincent Brown
• Vincent R. Brown, M. Tumeo, T. Larey and P. B. Paulus:
Modeling cognitive interactions during group
brainstorming. Journal of Small Group Research, Vol 29,
No 4, 1998.
Basic Operation
• Similar to the study
• Each participant gets 180 “steps”
• Each step represents 10 seconds in the experiment
• Based on transition table probabilities, at each step will
generate an idea from one of the 26 categories or
category 27 (no idea)
Working Memory
• Represents a participants short term memory
• Starts as 1x26 vector of 0’s each representing a category
• When a category is visited by a participant the
corresponding vector index is set to 1
• Memory of all inactive categories will decay by working
memory decay factor (set around 0.7)
Transition Probabilities
• Change every step
• Active category will decrease by factor of “alpha”
(currently set around 0.6)
• Inactive categories will slowly increase every step
(including null category)
• Simulates a participant running out of ideas in a particular
category
• Will lower chance of same category being visited again in
the near future
Selecting a Category
• Multiply transition table by working memory
• Results in 1x27 vector “PC” which holds the probability of
each transition the participant can make this step
• Stay in same category
• Visit one of the 25 other categories
• Not generate an idea (null category)
Hints
• Hints given in same way as in the study
• First 10 min, 10-20 min, 20-30 min
• Hints given every 3 steps (30 seconds)
• Hints are from a randomly selected category based on
category frequency
• “Hint attention factor” determines if participant will pay
attention to a particular hint or ignore it.
• If they pay attention, they jump to the hints category
• If participant is in the null category they will always pay
attention to a presented hint
Results
Ideas Generated by Interval
46
44
42
Ideas Generated
40
38
No Hint
First 10
36
Middle 10
Last 10
34
32
30
28
0
1
2
Interval
3
4
Compared to Study
Ideas Generated by Interval
46
44
42
Ideas Generated
40
38
36
34
No Hint
First 10
32
Middle 10
30
Last 10
28
0
1
2
Interval
3
4
Future Changes
Issues
• In model idea generation
drops off too quickly after a
hint interval
• The hint conditions are
matching the no hint
condition too closely
Possible Solutions
• Currently “alpha” variable
is constant throughout the
whole experiment.
• Looking into adding a
motivation factor to
change alpha as the
experiment progresses
• Represent participants loss
of motivation to generate
new ideas