Phineas Howie Final Paper Final Draft 1.

INFORMATION AVAILABILITY ON MEMORY AND EVALUATIONS !1
Cognition and the External World:
The Effects of Information
Availability on Memory and Evaluations
Phineas Howie
Purchase College of New York.

Abstract
People often offload cognitive processing to the external world by physically recording their
thoughts (e.g., in writing). Research has found that the availability of recorded information can
impact both memory and subsequent evaluations – when the information is available, memory is
reduced but the information may have greater impact on evaluations. The current study examined
whether these two findings are independent or contradictory by measuring both effects in a
single paradigm. Participants wrote down 15 trait words and thought of situations in which the
traits would be beneficial or detrimental. The words were then either shredded or kept in a folder.
Participants later evaluated each trait. Though there was no main effect of information
availability on memory or evaluations, there was a marginally significant interaction in which
participants who shredded the words later evaluated the traits more positively in the positive
thought condition and more negatively in the negative thought condition. Among participants
who kept the words in a folder, though, there was virtually no difference in the word evaluations
between those in the positive thought group and those in the negative thought group. Thus the
results of this study do not support the previous findings linking information's availability with
decreased memory and greater impact on evaluations. In fact our results suggest that disposing of
information (making it unavailable), may actually increase the extent to which people use it
during evaluations, whereas keeping information may have the opposite or no effect. Why the
results of this study are different from previous studies is unclear, and variations in methods may
have played a role.

Keywords: extended cognition, externalized memory, embodied thoughts
Cognition and the External World:
The Effects of Information Availability on Memory and Evaluations
In Western culture there is a shared conception that the mind, body, and the outside world
are three separate entities; the mind is an immaterial agent that exists within the body and uses it
as a medium for indirectly acting on the external world. However, research in psychology and
neuroscience has cast doubt on the separation of mind and body, suggesting that the mind is an
emergent property of a normally functioning brain. Furthermore, some philosophers and
psychologists have suggested that even the mind and world may not be as separate as they appear
to be. They suggest that the mind should not be understood as occurring solely inside the skull,
but as an interactive system between the internal processes of your brain and the material world.
(Clark and Chalmers, 1998; & Sutton, Celia, Harris, Keil, and Barnier, 2010). The proponents of
this “extended mind” hypothesis argue that human cognition becomes both more efficient and
more powerful when elements of the external world are incorporated into cognitive processing.
Philosophical work by Clark & Chalmers (1998) explicitly challenged the conception that
the mind and world are fundamentally separate. To build a case for the extended mind
hypothesis, Clark and Chalmers emphasize the possibility of externalized memory. They use the
fictional example of a man named Otto who has severe memory loss. In order to “remember”
past events, facts, and plans, Otto must consult his notebook, which he writes in continually. Otto
knows his birthday, for example, because it is written in his notebook. In order to retrieve this
information he simply has to look it up. Clark and Chalmers argue that for all practical purposes,

Otto’s notebook is in fact part of his memory and mind because it has all the most important
qualities that we associate with a normal person's memory mind: It is a constant in his life,
meaning that he consults it incessantly, it is easily accessible, Otto understands it to be
trustworthy and therefore endorses its material, and finally Otto know he himself is the “author”
of its contents. Otto’s unusual memory system is used to illustrate the point that even among
individuals with normally functioning internal memory, their minds and memory may still be
partially extended or offloaded into the external world. Much of the literature on extended
cognition has continued to work with an external memory model. There are various reasons to
focus on memory; it is relatively easy to define and measure, and it is highly integrated into other
cognitive processes.
Even if most people do not explicitly encode memories into an external source like Otto,
memories are still inextricably linked to environmental contexts as a result of the associative
nature of learning. Godden and Baddeley (1975) hypothesized that recall accuracy may be
partially dependent on the consistency between the learning and recall environments. To test this
hypothesis, participants learned a list of words either on land or underwater. For half of the trials,
recall for the list was tested in the same environment in which it was learned, and for the other
half recall was tested in the other environment. Godden and Baddeley found that material that
was learned on land was best recalled on land, while material learned underwater was best
recalled underwater. While extra information was not literally stored by the environmental
context, it appears that people unwittingly associate the material they are learning with the
context they are currently in. These findings suggest that our associative system disposes our
memories to incorporate and rely on cues from the external world.

If we use and depend on cues from outside world to aid recall does this actually mean
that the environment plays an active role in recall, or are we simply taking advantage of a passive
exterior world that has nothing to do with the processes of internal memory? Clark and Chalmers
(1998) seem to suggest that memory really can be extended, and contend that it is
inconsequential that Otto’s notebook consists of an entirely different system of recording
information than that of the brain. However critics of extended cognition have argued that Otto’s
notebook is not comparable to brain-based memory. Adams and Aizawa (2001), for example,
describe several ways in which Otto’s notebook functions differently from the neurologically
based memory of a typical person. They point out that the relationship between Otto and his
notebook is “mono-causal,” meaning that Otto affects his notebook whenever he pleases but that
the notebook itself cannot affect Otto without Otto first initiating an interaction.
Objections like these only hold for extended memory models based on person-artifact
relationships, however, and therefore do not address “transactive” memory models, which
propose that memories can be distributed amongst individuals and collaboratively remembered
by means of social interaction (Harris, Keil, Sutton, Barnier, and Mcllwain 2011; Sutton, Celia,
Harris, Keil, and Barnier, 2010). Transactive memory theory predicts a collaborative facilitation
effect in recall; this means that the collaborative recall of a group should be greater than the sum
of the individual recollections made by group members. The presence of a collaborative
facilitation effect would suggest that not only can memories be shared across individuals, but that
the dynamic reconstruction of memories by groups produces something uniquely characteristic
of the interaction itself, beyond the individuals involved in it.
However, rather than finding a collaborative facilitation effect, many studies have instead

found the opposite: a collaborative inhibition effect, in which the sum of individual recall is
greater than the recall of the group with the same individuals (Harris et al., 2011). Harris and
colleagues (2011) hypothesized that collaborative facilitation may depend on the presence and
effectiveness of a social recall strategy which may have been absent among participants in
previous studies. They predicted that an effective collaborative strategy would produce “cross
cuing,” meaning that each member’s recollections would help cue to the other to further recall.
To test this hypothesis they interviewed older couples individually and together. There were three
types of material that the couples had to recall: word lists, personal lists (which consisted of
recalling the names of people who went to their Probus or Rotary club), and autobiographical
memories of important life events. Signs of a collaborative recall strategy such as cue attempts
and repetitions were coded among the couples. Cue attempt were when one member of the
couple attempted to help his or her spouse remember something by adding additional facts or
questions. Repetitions were simply when one partner repeated a word or phrase their spouse had
just said. Couples were also coded for signs of counterproductive recall strategies such as
corrections and disagreements for the recall strategy. Corrections were when one partner would
correct what their spouse had said. Disagreements for recall strategy were when couples could
not even agree about the meaning of a question (in the autobiographical memory task), or when
the couples disagreed about how they should go about recalling information; for example in the
personal list task one member of a couple may have wanted to remember names in alphabetical
order while the other wanted to remember them by according to age. Couples who scored high
on cue attempts and repetitions showed collaborative facilitation, while couples that were coded
as displaying corrections and disagreements for recall strategy, showed collaborative inhibition.

Sutton et al (2010) suggest that collaborative recall strategies may be one way in which older
couples ward of the effects of memory decline during aging. This research suggests that memory
can be distributed across people with normal memories and that recall can be aided through
social interaction.
In the modern world some of the most reliable and accessible sources of information are
digital databases (Sparrow, Liu, & Wegner 2011). Inspired by the fact that the Internet is one of
the most efficient tools for acquiring information, Sparrow and colleagues (2011) investigated
whether people treat search engines like Google as an external memory source. Their first
experiment examined whether making participants aware of a gap in their knowledge
automatically primed them to think about computer and Internet-related words. In this
experiment, participants were probed with either easy or hard trivia questions. The test phase
consisted of a modified Stroop task that contained both computer-related and non-computer
related words. Past research has shown that when concepts are particularly salient, reaction times
for words related to the concepts in the color-naming Stroop task are slowed. Sparrow and
colleagues found that the participants in the hard trivia question group had slower reaction times
in the Stroop task for computer related words, supporting the idea that making people aware of a
gap in their knowledge automatically primes them to think about databases where such
knowledge can be acquired. Presumably, the awareness of one's own ignorance is slightly
uncomfortable, which leads people to think about the quickest remedy to such discomfort.
Experiment 2 of this study tested whether the expectation of access to information affects
a person’s memory for that information. In other words, do people remember information better
when they think it has been saved to an external memory source like a computer, or when it has

not been saved? The participants in this experiment read a series of facts, and then typed those
facts into a computer document. Half of the participants were told that what they wrote would be
saved and half were told that what they wrote would be deleted. After a distraction task they
were tested on their memory for the facts. Those who were told that what they wrote would be
erased remembered more facts than those who were told that what they wrote would be saved.
This suggests that when people believe information will be accessible in an external source, they
do not put as much effort into encoding it into their own “internal” memory. The results also
support the hypothesis that people treat stored information as if it were an external memory
source. Sparrow and colleagues argue that this effect may be an adaptive response of the human
memory system to incorporate external memory sources, similar to the transactive memory
findings described above.
Not all studies relevant to extended cognition have used external memory models: Kirsh
and Maglio (1994), for example, studied how people externalize or “offload” spatial cognition
onto the environment. They first distinguish between two types of actions which people engage
in during goal directed activity: “pragmatic” and “epistemic” actions. Pragmatic actions literally
bring a person one step closer to their goal. Epistemic actions, on the other hand, reveal
information that is relevant to achieving the goal. In other words, epistemic actions are
manipulations of the world meant to simplify the mental computations necessary to solve a
problem. In a sense, epistemic actions allow the world to solve part of the problem for you. Kirsh
and Maglio argue epistemic actions can increase the likelihood that problems will be solved
correctly. In order to study epistemic and pragmatic actions, they observed participants play a
real time spatial computer game called Tetris, which involves stacking differently shaped pieces

(“zoids”) that fall down one at a time from the top of the screen so that there are no empty
spaces. Critically, players can rotate the zoids and move them from side to side as they fall. Time
is of the essence in Tetris, and the faster you can find a solution for each falling piece the higher
you will score. Kirsh and Maglio developed a model which predicted what the game behavior
would look like if the players executed pragmatic actions only. This model predicted that the
average number of rotations necessary to make a good fit for each piece was only 1.5. However,
the average number of rotations made by participants was 3. This suggests that at least half of the
rotations were epistemic, as opposed to pragmatic (or a combination of both). To help explain
this Kirsh and Maglio identified several ways in which zoid manipulation can serve epistemic
purposes: Rotating zoids before they are fully visible can help players identify which zoid type it
is more quickly (rotation for early discovery), and physical rotation in general is faster than
mental rotation, helping players match the contours of the falling zoid with those that are already
situated more efficiently (rotation to save effort in mental rotation). Finally, moving the zoids
from side to side (translation) allows participants to “double check” that the zoids were in the
correct column before dropping it into the target position. This study suggests that when given
the chance people prefer to minimize the need for internal cognition by choosing physical
epistemic manipulations (which reveal just as much information) over mental calculations. This
indicates that people prefer to allow external objects and actions to solve part of the problem for
them.
Our sense of self is also intimately tied to aspects of the external world (Belk, 1988). This
is relevant to the extended mind/cognition hypothesis because our sense of self has a significant
impact on thinking and behavioral patterns (Van Dyne and Pierce 2004). This means that

manipulations to external manifestations of the self might have a direct impact on the mental
state of an individual, and vice versa. One of the ways that the self is extended beyond the
individual is through possessions. Some evidence comes from reports of those who have lost
personal possessions. For example, victims of theft have explicitly equated their possessions with
their bodies, suggesting that they felt as if they had been physically violated or raped. Victims
who have lost their homes in natural disasters have also explicitly suggested that they felt as if
they had lost part of themselves (Belk, 1988).
Much like how people have a natural bias to view themselves in a positive light (e.g.,
Guenther, & Alicke, 2010), they may also have a bias to view their own possessions as better or
more valuable than non-possessions, which is known as an ‘ownership effect’ (Kahneman and
Knetsch, 1991). Kahneman and Knetsch (1991) investigated whether an ownership effect would
exist in the context of controlled trade markets. To create market activity, half of the participants
were given coffee mugs which sold for six dollars at the university bookstore while half were
not. Classical economic theory, which treats people as rational agents, predicted that because the
mugs were given at random, about half of those who had received a mug would sell it because
they would value it less than about half of those who did not receive a mug. In other words, half
of those who did not receive the mug would offer enough money to convince a mug owner to sell
it to them. However, the amount of mugs sold was much less than 50%. Out of 22 mugs, an
average of only three sold across the four trials.
Kahneman and Knetsch hypothesized that it was a sense ownership for the mug that
made the owners value it on average twice as much as those who had not received a mug. To test
this hypothesis, they ran a second experiment that included three different groups: the sellers

who had been given the mugs, the buyers who had not, and the choosers who also had not. The
sellers then indicated at what amounts they would be willing to sell their mugs for, the buyers
indicated at what amounts they would be willing to buy a mug for, and the choosers indicated for
each amount if they would choose to receive the mug or the dollar amount. Although the sellers
and choosers were in objectively identical situations (choosing between a mug and money), the
choosers chose significantly lower dollar amounts over mugs than the sellers did. This study
shows that while ownership of an item increases its perceived value, non-ownership does not
necessarily decrease its perceived value.
A sense of ownership can also be felt for non-physical objects, such as immaterial goods,
abstract concepts, ideologies, and personal responsibilities (Van Dyne & Pierce 2004). Van Dyne
and Pierce (2004) predicted to find a positive relationship between employee feelings of
ownership for their job and organization of employment, and job satisfaction, organization-based
self-esteem, job performance, and citizenship behavior. To investigate their predictions they used
data from three field studies which sampled people from an array of different job positions.
Surveys in which participants evaluated a series of statements were used to measure their
psychological ownership for the organization of employment and other variables related to job
satisfaction. To measure job performance participants were rated by their supervisors and peers.
The surveys showed positive relationships between psychological ownership for the organization
and job satisfaction and organization based self-esteem. This study provides a strong indication
that physiological ownership for important aspects of your life can have a positive impact on
mental health and productive behaviors.
Language has many metaphors which equate thoughts to material objects (Lakoff &

Johnson, 1980). For example people talk about having, getting across, capturing, carrying and
losing thoughts. We also prescribe physical characteristics to thoughts such as deep, light, and
dark. With this in mind, Briñol, Gasco, and Petty (2013) predicted that feelings of psychological
ownership, and therefore positive feelings for one's own thoughts, might be affected by explicitly
treating thoughts as objects. To examine this issue they investigated whether or not physically
disposing of “embodied thoughts” (thoughts written on paper) would lead to their mental
disposal, and if keeping embodied thoughts would have the opposite effect. Participants were
assigned to write either positive or negative thoughts about the Mediterranean diet on a piece of
paper and were randomly assigned to complete one of three conditions: participants in the
“disposal” condition threw the piece of paper out, participants in the “control” condition folded
the corners of the paper, and participants in the “protection” condition kept the paper on their
person (e.g., in a pocket or wallet). Finally, after a distraction task the participants rated the
extent to which they approved of the Mediterranean diet. In the control and protection
conditions, those in the positive thought group rated the diet more highly than those the negative
thought group. However, in the thought disposal condition the opposite effect occurred: the
negative thought group had more favorable evaluations of the diet than the positive thought
group, as if throwing the thoughts away made participants value them less. These results suggest
that even though we do not typically consider thoughts to be of the same nature as real world
objects, treating them as such may affect our psychological ownership for them and therefore
how much we agree with them and use them in later evaluations.
These findings seem to contradict some of the external memory findings reported by
Sparrow, Liu, and Wegner (2011). On the one hand, the external memory model of Sparrow and

colleagues suggests that saving information in an external form minimizes the need to internalize
the information. External accessibility should therefore impair the internal accessibility of the
information. On the other hand, Briñol et al.’s (2013) embodied thought model predicts that the
symbolic act of saving and keeping information in physical form will increase feelings of
psychological ownership, which in turn will increase how this information is relied on and put to
future use.
In the present study, we test the compatibility of these two seemingly contradictory sets
of predictions, but in order to do so, the differences between the studies needs to be accounted
for. Sparrow, Liu, & Wegner (2011), for instance, measured participants’ memory for random
facts typed into a computer, while Briñol et al. (2013) measured the participants’ approval of
thoughts they themselves had produced and recorded onto a piece of paper. Thus, the present
study has two main goals: the first is to (conceptually) replicate the effects of Sparrow, Lui, &
Wegner (2011) and Briñol, et al. (2013) - namely, that the external availability of information has
a negative effect on memory for it, and that carrying a “thought object” on your person increases
the thoughts’ influence during later evaluations. The second goal is to see if these two effects are
independent. In other words, can a single manipulation (externalizing information by writing it
down, and then saving or discarding it) affect both memory for the information and the approval
and reliance for your previously formulated thought about the information?
In accordance with the external memory model, (Sparrow, Lui & Wegner 2011) we
predict that those who dispose of the information will have a better memory for it than those who
do not dispose of it. But in accordance with the embodied thought model (Briñol, et al. 2013) we
further predict that those who save the information will agree with their initial evaluations on the

information more than those who dispose of it.
Method
Participants
We recruited 58 participants (8 males and 50 females; mean age = 19, SD = 2.12; age
range = 19-34) from Introduction to Psychology and Research Methods classes at SUNY
Purchase College. Participants received class credit or extra credit for their participation.
Design and Materials.
A 2 (Information availability: saved or disposed) X 2 (Information Context: negative or
positive) between-subjects design was used to examine (1) how thinking about concepts in
different contexts could affect one's overall opinion of them, and (2) how the “availability” of
information might affect memory and evaluations for that information.
Stimuli. The material we used in this study consisted of total of 30 trait words. Trait
words are simple enough for any person to remember several of them from a list. Additionally
they are words that people inherently tend to judge as good or bad, however the merit of any
relatively neutral trait word depends largely on the circumstance in which it is in, e.g. “modesty
can be beneficial and detrimental depending on the context. All trait words used in the
experiment (study phase, and novel words in test phase) were pilot tested to ensure they were
perceived to be relatively neutral (i.e., not too positive and not too negative) In the pilot study,
six undergraduate psychology majors rated a list of 183 trait words on a scale from 1-10 (1 =
very bad to score high on the trait, 10 = very good to score high on the trait). Only words with an

average rating of roughly 4-6 were used in the experiment. The set of 15 trait words used in the
study phase of the experiment included: Trusting, Proud, Stubborn, Eager, Innocent, Sly,
Affectionate, Cautious, Obedient, Concerned, Glamorous, Serious, Tolerant, Secretive, Alert,
Silly, Mysterious, Apologetic, Fierce, and Quiet. Five different counterbalanced orders of these
15 trait words were used in the experiment (see appendix A). Pen and paper were provided for
the participants. A standard office paper shredder was used to dispose of written words (for those
in the unavailable information condition), and a plain folder was used to store them (for those in
the available information condition).
The text-based distraction task, dependent variable test questions, and demographics
survey were created using Qualtrics, an online survey software and presented on an Apple iMac
computer. The distraction task consisted of a 534-word popular science article about energy
efficient televisions (see appendix B). In the test phase 15 additional trait words were presented
to participants along with the same original trait words from the study phase list. The novel
words included: Average, bold, busy, careful, dutiful, industrious, peaceful, popular, quick,
religious, restless, satisfied, sorry, and strict. These words were not match paired with those from
the study phase.
Procedure
Participants were welcomed into the lab by the experimenter, who then directed them to
fill out a consent form. They were then given basic instructions and randomly assigned to one of
four experimental conditions, detailed below.

Study phase. The experimenter read aloud 15 trait words, one every 10 seconds.
Participants were asked to write each word down and to think about it in a certain context as it
was read aloud. Participants in the negative context group were asked to think of a situation for
every trait word in which being above average in the trait would be detrimental in some way. In
the positive context group, participants were asked to think of a situation for each trait in which
being above average in the trait would be beneficial in some way. Participants were asked only to
write down the trait words and not the imagined situations, and the experimenter made sure
participants understood the instructions before they began. There was no way to confirm whether
participants actually thought of positive or negative contexts.
After this initial phase, participants in the saved information condition were instructed to
place the paper with the written words in a folder. The experimenter explained that this paper
could be theirs to keep for after the experiment if they chose, and the folder was placed next to
the participants. Participants in the disposed information condition were told that in order to
protect their privacy, they should place the paper into a shredding machine that was situated on
the counter where they had been writing.
Distraction phase. All participants then used a computer to access a Qualtrics survey. The
survey first presented a popular science article. Following the article, participants responded to
three different multiple-choice questions about the contents of the article, each with three
possible response options. Once participants had moved from the article to the questions they
could not refer back to the article. (See appendix B).
Test phase. Next, the Qualtrics survey prompted participants to freely recall as many of
the trait words as possible from the initial study phase by typing them into a response box. This

was a surprise for the participants, as they had not been previously told about this memory
portion of the experiment.
After the free recall prompt, participants were presented with a series of 30 trait words.
The order of the 30 traits was randomized for every participant. Half of the trait words were the
same as those from the original list while half were new (the new words were also drawn from
the earlier pilot study, and again ranged in mean ratings from roughly 4-6). The following written
instructions preceded the 30 trait words: For each word please rate how good or bad it would be
to score very highly on this trait. Participants rated the traits on a 1-10 scale where 1 was very
bad and 10 was very good.
Participants were then prompted to ask the experimenter what their subject number was,
and once provided they typed it into the response box. Participants then completed two
demographics questions by providing their sex and age in years using open text boxes. Finally,
the survey asked participants what they thought the purpose of the experiment was, which they
responded to using an open text response box.
Results
Memory. We first analyzed participants’ free recall memory for the trait words they had
written down during the study phase. We conducted a 2 (Information availability: saved or
disposed) X 2 (Information Context: negative or positive) between-subjects factorial ANOVA
with the number of words remembered as the dependent variable. We excluded any words that
were “recalled” that did not actually appear in the original study list (i.e., false memories: 19
total words across 18 participants). There was no main effect for information context, as

participants in both the positive and negative contexts did not differ in the number of words they
remembered, F(1,54) = .890 p = .350. There was also no main effect of information availability,
as those who saved their paper in a folder did not differ in the number of words they remembered
from those who disposed of their paper in the shredder, F(1,54) = .048, p = .828. We also found
no significant interaction between information context and information availability, F(1,54) = .
347, p = .558). Thus, unlike Sparrow et al. (2011), who found that saving information lead to
impaired memory for it, the present study does not provide evidence that the external availability
of information necessarily affects internal memory for that information. See Figure 1.
Evaluations. Next, we analyzed the participants’ evaluations of the study phase words.
We conducted a 2 (Information availability: saved or disposed) X 2 (Information Context:
negative or positive) between-subjects factorial ANOVA with the rating of the words as the
dependent variable. There was no main effect of information context, as the word ratings of those
in the negative context did not differ from the ratings of those in the positive context, F(1,54) =
2.27, p = .138. There was also no main effect for information availability, as the word ratings for
those who saved the words did not differ from those who shredded them, F(1,54) = .064, p = .
801. We did find a marginally significant interaction between information context and
information availability, F(1, 54) =2.65, p = .109. However, we observed the opposite pattern of
results as Briñol and colleagues (2013), who found that among those who saved their thoughts,
the positive thought group gave more favorable evaluations than the negative thought group and
among those who disposed of their thoughts the reverse occurred. In the present study, we found
virtually no difference in the word ratings between the positive and negative context groups in

the saved information condition. However, among those who shredded their word lists,
participants showed greater agreement with their original thoughts, with participants in the
positive group rating the words more favorably than those in the negative group. See Figure 2.
Next we examined whether participants’ explicit memory for the trait words impacted
subsequent evaluations. Thus we repeated the analysis described above, first with ratings of
words freely recalled by participants as the dependent variable, and then with words not recalled
by participants as the dependent variable. For words recalled, there was no main effect for
information context (F(1,54) = .681, p = .413) and no main effect for information availability
(F(1,54) = .103, p =.750 ). Finally, though the interaction between information context and
information availability was not statistically significant (F(1,54) =.524 , p =.472 ), it did show
the same numerical trend as described above. See Figure 3.
For words that were not recalled, there was likewise no main effect for information
context (F(1,54) = 1.51, p = .225) or information availability (F(1,54) = .256, p = .615). Once
again, the interaction between information context and information availability was marginally
significant, in the same direction observed for recalled words, F(1,54) =3.15, p = .082. See
Figure 4.
Finally, we examined whether this pattern of evaluations was restricted to words from the
initial study list, or whether it would generalize to the novel words presented only in the test
phase. We conducted a 2 (Information availability: saved or disposed) X 2 (Information Context:
negative or positive) between-subjects factorial ANOVA with the ratings of the novel test phase
words as the dependent variable. There was no main effect of information context (F(1,54) = .
899, p = .347) or information availability (F(1,54) = .009, p = .923). Interestingly, though the

interaction between information context and information availability was not significant,
numerically speaking it showed the same pattern as observed for the study phase words, (F(1,54)
=.625, p = .433.) This suggests that whatever impact disposing or saving recorded thoughts has
on later evaluations, these effects might spread to other, novel items. See Figure 5.
Discussion
To study the effects of information availability on both memory and evaluations in a
single paradigm, we used two between-subjects manipulations: thinking about the trait words in
either a positive or negative context and either saving or shredding the list of words. By testing
participants on their memory and evaluations of the words after a brief distraction task, we were
able to probe whether the availability of externally recorded information impacts memory for
and evaluations of that information independently.
In accordance with the “external memory model” (Sparrow, Lui & Wegner, 2011), which
suggests that the human memory system has adapted to incorporate external sources of memory
into its memory system, we predicted that those who disposed of written trait words in the
shredder would remember more words than those who kept them in a folder. However, we failed
to observe any effects of information availability on memory for the trait words. Only within the
positive context group was the trend consistent with our prediction, but this effect did not reach
statistical significance. There may be several reasons for this pattern of findings. While
participants in Sparrow, Lui & Wegner (2011) reviewed full trivia statements that were designed
to be interesting, participants in our study reviewed only single words. The simplicity of our
study material may have led to a type of ceiling effect in which on average participants

remembered nearly seven words, which is close to the maximum amount “items” that can be
held in working memory. If participants were close to ceiling in this respect then it would be
difficult for any potential effect of the availability manipulation to make a significant difference.
A recognition memory task might have produced more variability in memory performance than
the free recall task used in this study. However because recognition is easier than free recall more
trait words or more challenging memory material would need to be used in a revised study
design; furthermore, while participants in Sparrow et al. (2011) read and typed a series of
statements into a computer, participants in our study constructed original imaginary scenarios
around single written words. While thinking about the words in certain contexts was in part
meant to help the participants remember more of them, the imagined contexts may have actually
dominated participants’ memory. Thus, the true “object of memory” may have been the imagined
scenarios about the words rather than the actual recorded words themselves. If this was in fact
the case, then our measure of memory for the material was poor because it did not access the
participant's’ memory for their imagined contexts.
Briñol and colleagues (2013) “embodied thought” model suggests that physically
disposing of information can limit its influence on later evaluations. We therefore predicted to
find an interaction such that for participants in the available (saved) information condition, those
in the positive context group would have more favorable ratings of the traits than those in the in
the negative context group. For participants in the unavailable (disposed) information condition,
we predicted that those in the positive context group would have less favorable ratings that those
in the negative context group. The trend we in fact found was nearly the opposite from what we
predicted. For participants in the available information condition there was virtually no

difference between the positive and negative word groups. However for participants in the
unavailable condition the positive group had more favorable ratings of the traits than those in the
negative group. This same trend persisted whether we looked at overall ratings, ratings for
recalled words, ratings for not-recalled words, and even slightly for novel words. Why we found
the opposite effect of Briñol et al. (2013) is difficult to explain, but if this trend is in fact
systematic it would suggest that disposing of information may actually solidify and strengthen
thoughts about it, as opposed to weakening them. It is possible that when information is available
externally, participants feel they have the opportunity to reflect on it in the future, which may
allow them to keep their opinions about it more flexible. But when information is disposed of
and no longer externally available, such reflections become more difficult, making one’s present
opinion less susceptible to change. So while someone might try to rid themselves of their
feelings (negative or positive) toward their ex-boyfriend/girlfriend by destroying their
photograph, such an action may actually make the present feelings felt toward their “ex” less
susceptible to change than if the photograph was not destroyed. In other words, the awareness of
the ability to reflect on the photograph may allow one to keep a more “open mind” about
subsequent evaluations. It is interesting to consider that although the main effect of information
availability on the free recall memory did not come close to reaching significance, there could
still possibly have been a difference between the conditions in their recognition of the words
during the evaluation phase. If this were the case then memory (recognition) may have had an
unexpected effect on the word evaluations. For instance if the shred condition recognized more
words that the keep condition, this could feasibly explain why we see a bigger difference
between the context groups in the shred condition than we do in the keep condition.

In future work, researchers might consider using different study materials. It may be
better, for instance, to use full paragraph descriptions about a person or event instead of single
words. This would allow thoughts about material to have a more concrete connection to what is
physically recorded. It may also be important to have participants write down their own thoughts
and opinions about the material, as was done in the work by Briñol et al. (2013), rather than
simply imagining them, this would also allow the experimenter to confirm whether participants
truly had imagined a positive or negative scenario. The scenarios could be coded as either
positive or negative or rated on a scale. Future research should investigate whether it is necessary
to write down thoughts for evaluations be manipulated, or if it is enough to simply throw away
material one has thought about (as in the present study).
Finally, exactly why the patterns of data observed in our study failed to replicate (and
even showed the opposite patterns compared to) previous research remains unexplained, so
further research is necessary to fully understand the consequences of information availability on
memory and evaluations.

References
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Cognitive science, 4(2), 195-208.
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Appendix A
Word List Order 1:
Innocent, Mysterious Eager, Cautious, Quiet, Apologetic, Serious, Obedient, Stubborn, Proud,
Secretive, Trusting, Silly, Glamorous, Concerned.
Word List Order 2:
Cautious, Quiet, Apologetic, Serious, Obedient, Stubborn, Proud, Secretive, Trusting, Silly,
Glamorous, Concerned, Innocent, Mysterious, Eager
Word List Order 3:
Serious, Obedient, Stubborn, Proud, Secretive, Trusting, Silly, Glamorous, Concerned, Innocent,
Mysterious, Eager, Cautious, Quiet, Apologetic
Word List Order 4:
Proud, Secretive, Trusting, Silly, Glamorous, Concerned, Innocent, Mysterious, Eager, Cautious,
Quiet, Apologetic Serious, Obedient, Stubborn
Word List Order 5:
Silly, Glamorous, Concerned, Innocent, Mysterious, Eager, Cautious, Quiet, Apologetic Serious,
Obedient, Stubborn Proud, Secretive, Trusting

Appendix B
The following article appeared in a recent issue of Scientific American. Please read it carefully at your
own pace, and click on the arrow at the bottom right only when you have finished reading.
Televisions Get Bigger and Greener
New technology allows new televisions to be both bigger and more energy efficient than ever
before
According to the U.S. Department of Energy, Americans’ 275 million TV sets burn through some
65 billion kilowatt hours of energy each year, representing four to five percent of U.S. household
electricity consumption. Each U.S. household spends around $200/year for electricity to power
their TVs and related equipment. But while we may not be giving up our TVs anytime soon,
there is some light at the end of the tunnel, as the consumer electronics industry has started to
prioritize reducing its environmental footprint.
While screen size has continued to increase, the overall mass of televisions is much smaller than
back in the days of boxy cathode ray tube (CRT) sets. And many new flat screen models (LCD,
OLED or plasma) sport hyper-efficient screens that can be tweaked even further by the user to
reduce their power needs.
Some of the energy-saving features that this new generation of greener TVs include screens
back-lit by light emitting diodes (LEDs), automatic brightness controls that adapt the picture to
the light intensity of the room, “local dimming,” where sections of backlighting are dimmed or
turned off when not needed, and the ability to pre-determine picture settings optimized to save
energy. All of the major TV makers—Vizio, LG, Samsung, Panasonic, JVC, Sharp, Toshiba,
Sony—now offer power-sipping models.
“Even though televisions are the most widely owned device in the U.S., with a 97 percent
household penetration in 2013, their total annual electricity consumption dropped 23 percent
from 2010,” reports the Consumer Electronics Association (CEA), the trade group for electronics
manufacturers that puts on the annual Consumer Electronics Show in Las Vegas.
The U.S. Environmental Protection Agency’s (EPA’s) ENERGY STAR program certifies
appliances, electronics and other energy-efficient consumer items to help Americans save money
and protect the climate through saving energy. If you’re shopping for a new TV, start your search
at EnergyStar.gov, where you can find and compare new models that are all at least 25 percent

more energy efficient than conventional ones. The easy-to-use site allows you to check-off which
brands, screen sizes, technology types, resolutions and other features you’re looking for before it
serves up a list of matches complete with estimated energy use over a year. The EPA reports that
if every TV, DVD player and home entertainment system purchased in the U.S. this year
qualified for an ENERGY STAR label, consumers would keep some 2.2 billion pounds of
greenhouse gas emissions out of the atmosphere, the equivalent of taking 200,000 cars off the
road.
Of course, buying a new TV introduces another potential environmental hazard: that associated
with the disposal of your old set. Throwing your old TV in the garbage where it will end up in a
landfill is not only bad for the environment, given the risk of chemical and heavy metal leakage,
it is also typically illegal. If you’re buying your new TV from a local store, ask them if they can
take back your old set. Also, the CEA’s Greener Gadgets website provides an up-to-date list of
resources to find out how to responsibly recycle old TV sets and other electronics directly with
the manufacturers or through third-party recyclers.
According to the article, approximately what percent of US household energy consumption is used by TVs?
■ 4-5%
■ 10-12%
■ 20-25%
Each U.S. household spends about how much money every year on electricity to power their TVs and related
equipment?
■ 100$
■ 200$
■ 300$
The annual electricity consumption of TVs has dropped by what percent since 2010?
■ 13%
■ 23%
■ 33%

Figure 1. Memory for study phase trait words. Error bars represent standard error of the means

Figure 2. Mean evaluation ratings for study phase trait words during the test phase. Error bars
represent standard error of the means.

Figure 3. Mean evaluation ratings for the recalled study phase trait words. Error bars represent
standard error of the means.

!
Figure 4. Mean evaluation ratings for the study phase trait words that were not freely recalled.
Error bars represent standard error of the means.

!
Figure 5. Mean evaluation ratings for the novel trait words that only appeared in the test phase.
Error bars represent standard error of the means.

Phineas Howie Final Paper Final Draft 1.

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