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The Production Effect in Memory:
Evidence That Distinctiveness Underlies the Benefit
Jason D. Ozubko and Colin M. MacLeod
University of Waterloo
The production effect is the substantial benefit to memory of having studied information aloud as
opposed to silently. MacLeod, Gopie, Hourihan, Neary, and Ozubko (2010) have explained this
enhancement by suggesting that a word studied aloud acquires a distinctive encoding record and that
recollecting this record supports identifying a word studied aloud as “old.” This account was tested using
a list discrimination paradigm, where the task is to identify in which of 2 studied lists a target word was
presented. The critical list was a mixed list containing words studied aloud and words studied silently.
Under the distinctiveness explanation, studying an additional list all aloud should disrupt the production
effect in the critical list because remembering having said a word aloud in the critical list will no longer
be diagnostic of list status. In contrast, studying an additional list all silently should leave the production
effect in the critical list intact. These predictions were confirmed in 2 experiments.
Keywords: memory, production, distinctiveness, recognition, aloud
The category of encoding techniques that substantially benefit
memory is disappointingly small. Of course, there is rehearsal
(e.g., Rundus, 1971), the most intuitive way to increase memory.
And every mnemonics book emphasizes imagery, which dramat-
ically improves memory (e.g., Paivio, 1971). Since Craik and
Lockhart’s (1972) introduction of levels of processing, semantic
elaboration has also been well recognized, as has generation since
the seminal article of Slamecka and Graf (1978). A few other
candidates might be nominated, but the list would remain short. So
why would we ignore a potential member of this set?
In 1972, in a rarely cited article, Hopkins and Edwards reported
a remarkably simple mnemonic phenomenon that they referred to
as a pronunciation effect. Subjects studied a list of words and later
performed a recognition test. During study, half of the words were
underlined and half were not. In the between-subjects conditions,
subjects were to ignore the underlining and either read all of the
words aloud or read all of them silently. Recognition was unaf-
fected. However, in the within-subjects condition, where subjects
were to read one set aloud (e.g., underlined) and the other set
silently (e.g., nonunderlined), words studied aloud were recog-
nized about 10% better than those studied silently.
For purposes not having to do with the pronunciation enhance-
ment per se, this advantage of saying some words aloud has been
replicated a few times in the ensuing almost 40 years (Conway &
Gathercole, 1987; Dodson & Schacter, 2001; Gathercole & Con-
way, 1988; MacDonald & MacLeod, 1998) but has left little
impression in the literature. In reintroducing and more thoroughly
delineating this phenomenon, MacLeod, Gopie, Hourihan, Neary,
and Ozubko (2010) have rechristened it with a more general name:
the production effect.
One thing that makes the production effect noteworthy is its
similarity to the generation effect (Slamecka & Graf, 1978), one of
the most widely used manipulations in memory research (see
Slamecka, 1992). The generation effect has been studied directly
or indirectly in hundreds of research articles. In a recent meta-
analytic review, Bertsch, Pesta, Wiscott, and McDaniel (2007)
suggested that the average improvement that generation provides
on a recognition test is roughly 10%. Remarkably, despite its
simplicity, the published evidence suggests that the production
effect is similar in magnitude to the generation effect.
Both techniques involve producing a word. However, genera-
tion appears to require more cognitive effort and semantic analysis
because subjects must actually retrieve words, as opposed to the
production effect where words are explicitly provided. If the
generation effect is taken as the hallmark of an excellent way to
increase memorability, then it is indeed surprising to find that a
simpler manipulation that does not necessarily lead to deeper
semantic processing can improve memory so much. Intriguingly,
the production effect even confirms the common intuition that
studying aloud improves retention. For these reasons, the produc-
tion effect warrants more investigation and greater visibility.
What Causes the Production Effect?
To explain the production effect, MacLeod et al. (2010; see also
Conway & Gathercole, 1987; Dodson & Schacter, 2001; Gather-
This article was published Online First August 30, 2010.
Jason D. Ozubko and Colin M. MacLeod, Department of Psychology,
University of Waterloo, Waterloo, Ontario, Canada.
This research was supported by an Alexander Graham Bell Canada
Graduate Scholarship and by Discovery Grant A7459, both from the
Natural Sciences and Engineering Research Council of Canada. We thank
Emily Bryntwick and Molly Pottruff for their assistance with the data
collection and Ian Dobbins for helpful comments during the review pro-
cess.
Correspondence concerning this article should be addressed to Jason D.
Ozubko or to Colin M. MacLeod, Department of Psychology, University of
Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada N2L
3G1. E-mail: jdozubko@uwaterloo.ca or cmacleod@uwaterloo.ca
Journal of Experimental Psychology: © 2010 American Psychological Association
Learning, Memory, and Cognition
2010, Vol. 36, No. 6, 1543–1547 0278-7393/10/$12.00 DOI: 10.1037/a0020604
1543
cole & Conway, 1988) have championed a distinctiveness
account—that production at study makes words distinctive and
that this distinctiveness can be used heuristically at test: “I remem-
ber saying that aloud so it must be old.” Subjects cannot use the
opposite strategy to identify silently studied words (“I remember
not saying that word aloud”), because the distracters at test were
not said aloud during study either. MacLeod et al. cast this account
in terms of the replaying of an encoding record, in line with the
proceduralist view of memory (Kolers, 1973; Kolers & Roediger,
1984). In support of this distinctiveness account, MacLeod et al.
observed that the effect persisted when subjects mouthed (but did
not speak) words at study, because mouthing still provides dis-
tinctive responses to each word. However, when subjects repeat-
edly pressed a key or repeatedly said “yes” to some words at study,
no memory advantage was observed.
Perhaps most compelling, MacLeod et al. (2010) confirmed that
the production effect occurs within subjects but not between sub-
jects (see also Dodson & Schacter, 2001; Hopkins & Edwards,
1972). This finding is in line with other effects believed to be
driven by distinctiveness. For example, the orthographic distinc-
tiveness effect—the finding that orthographically atypical words
are remembered better than less atypical words—occurs only in
mixed lists, not in pure lists (Hunt & Elliot, 1980; Hunt & Mitch-
ell, 1982). Similarly, superior memory for bizarre sentences over
common sentences, believed to be driven by the distinctiveness of
the bizarre sentences, occurs only in mixed lists, not in pure lists
(Waddill & McDaniel, 1998). McDaniel and Bugg (2008) have
recently presented a thorough analysis of this design difference,
which encompasses many well-established encoding effects, nota-
bly, generation, enactment, word frequency, perceptual interfer-
ence, and bizarreness.
Despite the similarities between the production effect and other
distinctiveness-driven phenomena, a direct test of the idea that
production relies on distinctiveness has not yet been conducted.
Our goal here was to undertake that test. To do so, we sought to
disrupt the production effect in a manner that is clearly predicted
by the distinctiveness account. If this account is correct, then
production will lead to superior recognition at test because a
distinctive element forms part of the encoding record of each word
studied aloud, an element not shared by the silent words that were
also studied or by the distracters that appeared only on the test.
Logically then, if the distracters could be made to share this
element with the aloud words, this should undermine or even
eliminate the distinctiveness that ordinarily causes the production
effect, causing the effect to diminish or disappear.
Experiment 1
Our goal was to test the production effect in a paradigm where
the distinctiveness account predicts that the effect should be dis-
rupted. Subjects studied two separate lists: a critical mixed list and
a distracting pure list. The critical list always included half words
to be spoken aloud and half words to be read silently. The key
manipulation was on the distracting list, where the words could be
studied either all aloud or all silently. At test, subjects were
required to discriminate whether each word came from the critical
mixed list or from the distracting pure list. Thus, all of the test
words had been studied: The test was a list discrimination task
(see, e.g., Hintzman, Caulton, & Levitin, 1998; Hintzman &
Waters, 1970), not a yes–no recognition task.
Under the distinctiveness account, on a standard recognition
test, recollecting that a word was read aloud ordinarily is useful for
identifying it as studied because the distracters were not read
aloud. In list discrimination, however, because words from both
the critical mixed list and the all aloud distracting pure list were
read aloud at study, recollecting that a word was read aloud should
not assist in identifying the word’s source. Furthermore, failing to
recall that a word was read aloud should not be particularly
diagnostic, as this could indicate that the word was read silently or
was read aloud but not encoded well. In other words, the absence
of a feature at retrieval is not particularly strong evidence that a
feature was absent at encoding (although a small effect might
conceivably be observed here because this is somewhat informa-
tive). However, crucially, when the distracting pure list is read
silently, a production effect should be observed because now
recollecting that a word was read aloud at study is useful for list
discrimination. Any other data pattern would be inconsistent with
the distinctiveness account.
Method
Subjects. Thirty-six University of Waterloo students partici-
pated for course credit. For the between-subjects distracting pure
list manipulation, 18 students were randomly assigned to the all
aloud condition and 18 to the all silent condition.
Stimuli and apparatus. A pool of 120 words was taken from
the Appendix in MacDonald and MacLeod (1998). The words
were all nouns from 5 to 10 characters long with frequencies
greater than 30 per million (Thorndike & Lorge, 1944). The
experiment was programmed in E-Prime Version 1.2 (www
.pstnet.com) and was carried out on IBM PC-compatible comput-
ers with 15-in. color monitors.
Procedure. For each subject, the 120 words were randomly
ordered and two sets of 32 words were selected to form the critical
mixed list and the distracting pure list. For the critical mixed list,
half of the words were randomly selected to appear in blue and half
in white, with color order random through the list. For the dis-
tracting pure list, the words appeared either all in blue (aloud) or
all in white (silent). Subjects were told to read blue words aloud
and white words silently.
During study, words were presented individually at the center of
the screen for 2 s with a 0.5-s interstimulus interval. Prior to the
test phase, subjects were instructed that all of the words had been
studied (i.e., that all words were “old”) and that their task was to
identify which list each word came from. To identify a word as
belonging to the first (mixed) list, subjects pressed c; to identify a
word as belonging to the second (pure) list, they pressed m.
Results
The results are shown in the top portion of Table 1. An alpha
level of .05 was applied throughout the analyses. Performance on
the distracting pure list did not differ as a function of whether it
was all aloud or all silent, t(34) ⫽0.79, p⫽.44, d⫽0.31. This
is consistent with the absence of a between-subjects production
effect previously reported by Hopkins and Edwards (1972), Dod-
son and Schacter (2001), and MacLeod et al. (2010).
1544 RESEARCH REPORTS
Our focal analysis was a 2 (mixed list word type: aloud vs.
silent; within subjects) ⫻2 (pure list word type: all aloud vs. all
silent; between subjects) mixed analysis of variance (ANOVA)
conducted on the accuracy scores for the critical mixed list words.
Overall recognition of aloud and silent critical mixed list words
was equivalent, F(1, 34) ⬍1. When the distracting pure list
contained only aloud words, accuracy for the critical mixed list
words was lower than when the distracting pure list contained only
silent words, F(1, 34) ⫽7.09, MSE ⫽0.04, p
2
⫽.17.
Critically, consistent with the distinctiveness account, the inter-
action was significant, F(1, 34) ⫽5.56, MSE ⫽0.02, p
2
⫽.14.
As Table 1 clearly shows, there was a reliable production effect for
the critical mixed list only when all words on the distracting pure
list were studied silently, t(17) ⫽2.13, d⫽0.50, with 14 of the 18
subjects (78%) showing the effect. The production effect disap-
peared when all words on the distracting pure list were studied
aloud, t(17) ⫽1.24, d⫽0.30, with only five of the 18 subjects
(28%) showing the effect.
Discussion
Consistent with the prediction of the distinctiveness account, the
production advantage usually seen for a mixed list of aloud and
silent words was eliminated when the words in an additional
distracting list were all read aloud. The production effect was,
however, robust (11%) when the words in the distracting list were
all read silently. This fits with the idea that, at test, subjects are
recollecting having read a word aloud during study and are using
this processing record to improve memory accuracy for the aloud
words. Such recollection succeeds because of the distinctiveness of
the aloud words in a mixed list only when no other aloud words are
present, as in the all silent distracting list. But when other words
are said aloud during study, as in the all aloud distracting list, such
recollection is not diagnostic of list status, and consequently the
production effect disappears.
Experiment 2
Experiment 2 constituted a conceptual replication of Experiment
1. Only one change was made: This time, the distracting pure list
preceded the critical mixed list, representing a situation of proac-
tive influence. The same prediction was made as for Experiment 1.
Method
Subjects. Thirty-six students from the same pool took part for
the same credit. Half were randomly assigned to the all aloud and
half to the all silent pure list condition.
Stimuli and apparatus. The same stimuli and apparatus were
used as in Experiment 1.
Procedure. The procedure was identical to that of Experiment
1 except that the distracting pure list now preceded the critical
mixed list, rather than following it.
Results
The results are shown in the bottom half of Table 1. As in
Experiment 1, performance on the all aloud versus all silent pure
lists did not differ between subjects, t(34) ⫽0.55, p⫽.58, d⫽
0.19. This again is consistent with the uniform absence of a
between-subjects production effect in prior studies (Dodson &
Schacter, 2001; Hopkins & Edwards, 1972; MacLeod et al., 2010).
The same 2 ⫻2 mixed ANOVA was used as in Experiment 1.
Again, there was no overall difference in critical mixed list accu-
racy when the distracting pure list was all aloud versus all silent,
F(1, 34) ⬍1. This time, however, aloud study words were recog-
nized significantly better overall than were silent study words, F(1,
34) ⫽14.41, MSE ⫽0.02, p
2
⫽.30, likely because the critical
mixed list was studied immediately before the test.
Most important, as in Experiment 1, critical mixed list word
type interacted with distracting pure list type, F(1, 34) ⫽20.53,
MSE ⫽0.02, p
2
⫽.38. There was a large and reliable production
effect when the distracting pure list was all silent, t(17) ⫽6.10,
d⫽1.44, but no production effect when the distracting pure list
was all aloud, t(17) ⫽0.50, d⫽0.12. The production advantage
was present for 16 of 18 subjects (89%) when the pure list was all
silent but for only seven of 18 subjects (39%) when the pure list
was all aloud.
Table 1
Results of Experiments 1 and 2
Pure list type
Mixed list
Pure listAloud Silent
MSEMSEMSE
Experiment 1: Critical mixed list first
All silent .76 .05 .65 .05 .61 .04
All aloud .56 .04 .62 .04 .65 .02
Experiment 2: Critical mixed list second
All silent .77 .04 .50 .04 .67 .03
All aloud .62 .03 .64 .04 .65 .03
Note. Mean proportions (and standard errors) of aloud versus silent studied words correctly assigned to the
critical mixed list are shown separately as a function of the type of distracting pure list (all aloud vs. all silent).
Also shown are the mean proportions (and standard errors) of words correctly assigned to the distracting pure
lists.
1545
RESEARCH REPORTS
Discussion
In sum, the results of Experiment 2 very closely paralleled those
of Experiment 1. Again, a robust production effect (27%) occurred
in the critical mixed list only when the distracting pure list com-
prised all silent words; it was eliminated when the distracting pure
list comprised all aloud words. A 2 ⫻2⫻2 ANOVA incorpo-
rating experiment as a variable further demonstrated the consis-
tency of the experiments, with no three-way interaction ( p⬎.22).
The results of the two experiments are, therefore, thoroughly
consistent with each other and with the predictions of the distinc-
tiveness account.
General Discussion
The production effect is a simple yet effective means to improve
memory, as MacLeod et al. (2010) have argued. Indeed, it evi-
dently leads to substantial improvement, so its virtual invisibility
in the literature is surprising. To date, the few published studies
examining the benefit of production (Conway & Gathercole, 1987;
Dodson & Schacter, 2001; Gathercole & Conway, 1988; Hopkins
& Edwards, 1972; Hourihan & MacLeod, 2008; MacDonald &
MacLeod, 1998; MacLeod et al., 2010) have produced data largely
consistent with a distinctiveness account but have not directly
tested the main mechanism underlying that account. Our goal was
therefore to interfere with the production effect in a manner that
should undermine the distinctiveness account’s driving mecha-
nism.
Using a list discrimination test, Experiment 1 demonstrated that
when a second list is studied after the critical mixed list, the
production effect for the critical mixed list is eliminated when the
words from that second list are all said aloud but remains robust
when they are all read silently. Experiment 2 confirmed this
pattern when the words in the extra list were instead studied before
the critical mixed list. These results are thoroughly consistent with
a distinctiveness account: Only when recollection that a word was
said aloud is diagnostic of list status should a production effect
emerge.
These experiments confirm that recollective distinctiveness—
and hence memory—can be improved via production. Production
provides extra distinctive information which can be used heuristi-
cally at test to improve performance. This phenomenon bears some
similarity to other recent work that emphasizes the heuristic value
of using distinctive information to reject distracters—the recall-
to-reject strategy (see, e.g., Clark & Gronlund, 1996; see also the
idea of criteria recollection, e.g., Gallo, Weiss, & Schacter, 2004).
For example, using a contextual encoding manipulation, Dobbins,
Kroll, Yonelinas, and Liu (1998) found that items encoded in more
distinctive contexts were better remembered than items encoded in
less distinctive contexts but that this benefit arose primarily from
participants’ ability to reject distracters. In essence, distinctive
information did not benefit recall or hit rates but did help partic-
ipants reject novel test probes.
Generally, then, studies that find that participants use discrim-
inative information at test to strategically reject distracters also
find that distinctive information does little to boost hit rates. It is
important to realize, though, that both benefits of distinctiveness—
more hits and more correct rejections—have been previously
reported, notably by Hunt (2003). Because in traditional recogni-
tion paradigms, production seems primarily to improve memory
for target items (see MacLeod et al., 2010), production provides an
instance where distinctive information is used to increase hit rate,
whereas the recall-to-reject work focuses more on instances where
distinctive information is used to decrease false alarm rate.
Our work also bears on simple strength accounts of production.
Recall that our distinctiveness account predicted that a production
effect should emerge only when recollection that a word was said
aloud is diagnostic of list status. A straightforward strength ac-
count (see, e.g., Hovland, 1951; Wickelgren, 1969) would not
readily make this prediction. Instead, appealing to the idea of
repetition incrementing strength (see Murdock, 1989, for a re-
view), a strength account would say that words said aloud are
encoded more strongly than those said silently. If so, then the
nature of the distracting pure list should not selectively weaken
the stronger aloud words more than the weaker silent words in the
critical mixed list. Indeed, a strength account would also predict
that if the encoding of aloud words is stronger than that of silent
words this should be true even in the distracting pure list situation.
But studies have repeatedly shown that there is no production
effect between subjects, a finding which was confirmed here in
that the all aloud and all silent distracting pure list items were
equally well discriminated. The strength view is therefore wrong
on both counts.
A major empirical appeal of the production effect is its simplic-
ity. Consequently, it can easily be used in diverse situations. For
example, as a quick method for increasing the distinctiveness of
some items over others, the production effect is far easier to use
than the generation effect. Generation requires the creation of extra
cues from which the items will be generated. Further, in genera-
tion, subjects occasionally make “mistakes,” generating an item
other than the intended one. None of these issues exist for pro-
duction because the word being studied is its own cue. The
production effect may therefore prove to be a useful technique in
study situations, or whenever relatively quick and easy memory
enhancement is desired. As noted earlier, the existence of the
production effect fits with the common notion that information
studied aloud is better remembered.
In this article, we sought to examine the theoretical basis of the
production effect. Our findings are entirely consistent with a
distinctiveness account: Production makes items stand out at study,
and recollection of this is useful at test. When distinctiveness is
undermined, the production effect vanishes. Clearly, any adequate
theory needs to successfully predict not only when an effect will be
present but also when it will be disrupted or eliminated. So far, the
distinctiveness account has met this requirement for the production
effect.
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Received August 11, 2009
Revision received May 11, 2010
Accepted May 26, 2010 䡲
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