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Noticing and Revising Discrepancies as Texts UnfoldDavid N. Rapp a & Panayiota Kendeou ba School of Education and Social Policy and Department of Psychology , NorthwesternUniversityb Department of Educational and Counseling Psychology , McGill UniversityPublished online: 22 Jan 2009.
To cite this article: David N. Rapp & Panayiota Kendeou (2009) Noticing and Revising Discrepancies as Texts Unfold, DiscourseProcesses, 46:1, 1-24, DOI: 10.1080/01638530802629141
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Discourse Processes, 46:1–24, 2009
Copyright © Taylor & Francis Group, LLC
ISSN: 0163-853X print/1532-6950 online
DOI: 10.1080/01638530802629141
Noticing and Revising Discrepanciesas Texts Unfold
David N. RappSchool of Education and Social Policy and Department of Psychology
Northwestern University
Panayiota KendeouDepartment of Educational and Counseling Psychology
McGill University
Readers attempt to build coherent representations for what they read, but those
representations may fail to capture the actual content of texts. For example, al-
though narrative situations often change dramatically as plots unfold, readers
do not necessarily revise what they know to accurately represent the current
state of affairs in a text. This study investigated the conditions that might foster
revision, and the temporal locus of potential revision activity. In 2 experiments,
participants read stories that afforded the opportunity to build trait models of
characters. Trait descriptions were either immediately refuted or supported with
further evidence. Participants revised their models of characters when provided
with causal explanations. They did not revise, however, when previous character
information was simply refuted. Revision, when it occurred, was observed im-
mediately after refutations were provided. Whether they revised or not, though,
participants appeared to readily notice the discrepancies suggested by refutations.
The results of this study further outline the nature of narrative updating, as well as
the revision failures that can influence readers’ comprehension of unfolding texts.
A large body of research has investigated the processes by which readers attempt
to build coherent representations of what they read (Kintsch & Vipond, 1979;
van den Broek, 1994; van Dijk & Kintsch, 1983). In this context, coherence
Correspondence concerning this article should be addressed to David N. Rapp, School of
Education and Social Policy and Department of Psychology, Northwestern University, 2120 Campus
Drive, Evanston, IL 60208. E-mail: [email protected]
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2 RAPP AND KENDEOU
refers to the types of effective connections that readers may make among the
ideas conveyed within a text (for a review, see Louwerse & Graesser, 2005),
whereas cohesion refers to the degree to which texts have linguistic consistency
or unitary ideas across the course of their content (e.g., Beck, McKeown, Sinatra,
& Loxterman, 1991; O’Reilly & McNamara, 2006). Of course, the coherent con-
nections readers can make based on the ideas in a text are not solely a function
of cohesion. Coherence may be derived from both the unfolding discourse and
readers’ prior knowledge, and influenced by reading skill, cognitive resources,
task demands or goals, and motivation (e.g., Graesser, McNamara, & Louwerse,
2003; Long, Wilson, Hurley, & Prat, 2006; D. S. McNamara, Kintsch, Songer,
& Kintsch, 1996; D. S. McNamara & Shapiro, 2005; Singer & Ritchot, 1996;
van den Broek, Lorch, Linderholm, & Gustafson, 2001; Zwaan & Rapp, 2006).
Each of these contributors can act on the quality of a readers’ mental model of
the text, and consequently, comprehension is a direct function of that resulting
mental representation (Kintsch, 1998; Trabasso & Suh, 1993; Zwaan, Langston,
& Graesser, 1995). Thus, the coherence of a mental or situation model is a
critical factor in readers’ understanding and later use of text information.
Despite these various potential contributors, cohesion nevertheless influences
the types of coherent representations readers might build, and texts can vary a
great deal in the degree to which they are cohesive (e.g., Graesser, McNamara,
Louwerse, & Cai, 2004). For example, texts often contain ambiguous references
(e.g., Levine, Guzmán, & Klin, 2000), concepts that potentially convey multiple
meanings (e.g., Kambe, Rayner, & Duffy, 2001), or narrative discontinuities
that require readers to “fill in” missing information (e.g., Rapp & Taylor, 2004).
In each of these cases, readers may experience difficulty making connections
between text elements and, as such, may have trouble understanding and re-
membering what they have read (D. S. McNamara, 2001; D. S. McNamara &
Kintsch, 1996).
Text experiences in which cohesion is violated are actually quite common.
Consider that authors and narrators often withhold, dramatically change, or even
provide false information about characters and events that can call into question
what readers presumably already know (Booth, 1983). These conditions illustrate
that what readers learn at the beginning of a narrative may be quite different from
what they should know about story characters, events, or plots at the conclusion
of that text (Gerrig, 1993; Gilbert, Krull, & Malone, 1990). It seems reasonable
to expect that readers will try to reconcile these discrepancies as they attempt to
build coherent mental representations. One obvious way they might do this is to
revise what they know when texts suggest updating is necessary (Kendeou & van
den Broek, 2007). Unfortunately, evidence has convincingly demonstrated that
readers (a) rely on early text descriptions even when subsequent information
renders those descriptions invalid and (b) that this is unlikely to be due to
readers simply missing or ignoring text discrepancies (e.g., Seifert, 2002; van
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REVISING TEXT DISCREPANCIES 3
Oostendorp, 2002). Revision failures can lead to mental representations that,
although internally consistent, may not accurately mirror the relations among
concepts described in a text.
In this study, we investigated the processes that underlie readers’ attempts
to reconcile discrepancies between unfolding text segments, as well as the
processing consequences of such activity. These investigations are of consid-
erable theoretical and practical interest given that readers often fail to sponta-
neously revise what they know to reflect the current state of affairs in texts.
For example, O’Brien, Rizzella, Albrecht, and Halleran (1998) demonstrated
that readers remain influenced by their initial models of story characters despite
subsequent information rendering those models inaccurate or appropriate only
under a restricted set of conditions. In their studies, participants who read
an initial description of a character (e.g., “Mary, a health nut, had been a
strict vegetarian for ten years.”) exhibited comprehension difficulty when that
character later behaved in an explicitly inconsistent way (e.g., “Mary ordered
a cheeseburger and fries.”). More importantly, these difficulties obtained even
if the initial description had been qualified to make the inconsistent behavior
entirely reasonable (e.g., “Nevertheless, Mary never stuck to her diet when she
dined out with friends.”; also see Guéraud, Harmon, & Peracchi, 2005). Johnson
and Seifert (1994, 1998, 1999) similarly showed that readers’ beliefs about the
causes of events demonstrate resistance to change in the face of obvious refuting
evidence. After learning about the cause of a warehouse fire, readers continued
to attribute the fire to that cause even when the text suggested it was no longer
plausible.
Findings like these reveal that readers often fail to revise what they have
previously learned even when the text contains information suggesting they
should do so. These types of failures can occur both with unheralded inaccuracies
or anomalies, as well as with materials in which discrepancies are openly
demarcated (e.g., Barton & Sanford, 1993; Daneman, Lennertz, & Hannon,
2007; Seifert, 2002). Readers commonly encounter texts with intentional and
unintentional discrepancies, as well as texts containing cues that call direct atten-
tion to potential inconsistencies (Ellis, Ottaway, Varner, Becker, & Moore, 1997).
With respect to these latter cases, everyday reading materials (e.g., newspapers,
novels, textbooks) often contain refutations that explicitly highlight the need
for readers to change what they know or discount prior text information (e.g.,
Guzzetti, 2000; Maria & MacGinitie, 1987; van Oostendorp & Bonebakker,
1999). However, even when warned about the need to revise, readers may fail
to carry out the activities necessary to accurately represent texts, in ways that
would resolve potential discrepancies.
Under what conditions, then, do readers both notice and act on the refutations
provided in a text? The degree to which readers revise what they have learned as
a text unfolds is influenced by the quality of the textual refutation or qualification,
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4 RAPP AND KENDEOU
as well as the particular tasks or goals that guide the reading experience. In
a series of experiments, Rapp and Kendeou (2007) demonstrated that readers
tended to revise if (a) refutations provided a causal explanation that specifically
targeted an earlier mentioned description and (b) the reading task required
participants to carefully consider the appropriateness of unfolding descriptions.
Participants in these experiments read stories that suggested characters possessed
particular traits. For example:
Albert was listening to the radio. He had finished getting ready to meet his friends
at the movies. They were going to see a new comedy that was getting rave reviews.
He pulled a sweater over his head. Then he began to look for his shoes. They were
buried under old candy wrappers, crumpled magazines, and some dirty laundry.
Albert didn’t care about keeping his room clean, and this is how it usually would
look.
The last two sentences of this text suggest Albert is a rather messy individual,
without explicitly stating that trait. A second episode followed each story for
which readers might generate expectations for future character behavior as a
function of any inferred trait model. Consider the following:
Albert had to take the bus to go to the movies. He bought a newspaper to read
during the ride to the theater. Albert had finished leafing through the paper when
his stop was announced. Albert put the newspaper on the seat next to him. As he
waited for the bus to stop, he noticed a sign asking riders not to leave garbage on
the bus.
Following this episode, participants read one of two outcomes, either consistent
with the trait (i.e., “Albert ignored the sign and got off the bus.”) or inconsistent
with it (i.e., “Albert picked up the newspaper to throw away later.”). Without
obvious discrepancies in the text description, readers expect characters will
behave in consistent ways (e.g., Albert will ignore the sign; Rapp, Gerrig, &
Prentice, 2001).
Rapp and Kendeou (2007) specifically assessed conditions under which read-
ers might revise these expectations. Using the prior example, revision would
result in the belief that Albert is not messy, which contradicts and is therefore
inconsistent with the earlier trait. Refutation conditions were set up by replacing
the last sentence of each first episode with either a simple refutation (i.e., “Albert
cared about the condition of his room, even though it currently wasn’t up to
par.”) or with an explanatory refutation that included a causal reason as to
why the earlier information was inappropriate (i.e., “Albert cared about the
condition of his room, but had only moved into the apartment yesterday.”).
With an explicit judgment task asking participants to indicate whether a story
outcome appropriately described a next likely event, both types of refutations
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REVISING TEXT DISCREPANCIES 5
led to revision—using our example, readers tended to believe Albert might
not be as messy as initially suggested. However, in a second experiment this
explicit judgment task was removed, and participants’ reading times to story
outcomes revealed evidence of revision only when refutations included causal
explanations—that is, participants took longer to read (formerly) trait-consistent
than trait-inconsistent outcomes after explanatory refutations, but not after simple
refutations. Spontaneous revision was a function both of task demands (i.e.,
evaluative, judgment tasks enhanced readers’ propensities toward revision) and
text content (i.e., explanatory refutations were more effective than simple ones).
The findings of that study raise an interesting question—namely, whether
readers in those experiments actually revised their trait models immediately after
reading the refutation material or whether they waited until the story conclusion
to generate any trait inference at all. Revision is a specific, demanding form
of updating that requires readers to substantially modify an existing memory
representation to reflect a new state of affairs. Although the previous exper-
iments suggest that readers’ final representations of story events, and hence,
their reading times to story outcomes, were influenced by task instructions and
explanatory refutations, the data are limited with respect to whether readers
actually encoded models of characters as the stories unfolded. It is entirely
possible that readers failed to build any type of trait model until the point at
which they were presented with the story outcome. Because Rapp and Kendeou’s
(2007) explanation relied specifically on the notion that readers revise what they
know during reading, it is important to test whether readers actually encoded
trait models prior to story outcomes.
In addition, although the obtained patterns of data in Rapp and Kendeou
(2007) proved informative, some of the item analyses were only marginally
significant. These marginal findings might indicate that the effect was, indeed,
not a real one; alternatively, the findings might be due to the variability inherent
in factors that underlie reading times (e.g., word length, familiarity, conceptual
complexity; Haberlandt, 1994). Thus, a replication of these effects, utilizing a
complementary experimental task, would provide an important test of the validity
of refutation-based contributions to revision.
In this study, participants read stories identical to those provided in Rapp
and Kendeou (2007), with each story potentially suggesting that a previously
inferred trait might not be appropriate. We coupled a probe-based methodology
with reading time measures to investigate the conditions under which readers
revise what they know about characters. It was hoped that these complementary
methodologies would help assess whether revision might occur during reading,
or whether any effects might be due to outcome-based reading activities that only
resemble revision in their products. In this way, the experiments were intended
to provide an additional test of refutation-based revision while also extending
our understanding of the locus of any effects.
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6 RAPP AND KENDEOU
EXPERIMENT 1
To begin this set of studies, we examined whether readers encoded and revised
trait information as stories unfolded, prior to story outcomes. Participants read
stories each containing two episodes. Episode 1 always included behavioral
evidence for traits. This information was either (a) supported with an additional
statement or (b) refuted with a causal explanation as to why any earlier trait
inference was potentially inaccurate. A second episode followed, concluding
with an outcome that was always consistent with the trait implied by the initial
behavioral evidence.
To test whether particular trait models were indeed encoded prior to story
outcomes, a lexical decision (LD) task was used at two different probe points.
The critical LD probe always described the relevant trait (e.g., messy for the
earlier Albert example). Participants completed the LD either (a) immediately
after the supporting or refuting statement in Episode 1 or (b) after the outcome
sentence concluding Episode 2. Reading times to outcome sentences were also
recorded.
We made several predictions with respect to reader revision. Our first pre-
diction was that, overall, readers would take longer to identify trait probes for
stories containing explanatory refutations than stories containing trait supporting
statements. This prediction, while potentially demonstrating revision with the LD
task, does not provide an indication as to when revision might occur. Thus, our
second set of predictions concerned the locus of any such effects. If readers revise
during reading, we expected that the aforementioned probe effect would obtain
immediately following the supporting or refuting statements (Probe Point 1 [P1]).
If, however, times to identify trait probes do not differ at this point, it would
suggest that revision had not yet taken place. Probe Point 2 (P2) provided a
complementary test; if a probe effect obtained at P2 only, it would suggest that
revision was focused at story outcomes.
The methodology, more importantly, also allowed us to examine story out-
comes as an additional test of the degree to which readers’ beliefs about char-
acters took into account any earlier refutations. We predicted that participants
would take longer to read trait consistent outcomes in stories containing refu-
tations with explanations compared to stories containing trait supporting state-
ments. These results would replicate earlier work on the consequences of refu-
tations containing explanations.
Method
Participants. Thirty-six University of Minnesota undergraduates partici-
pated in this study for course credit. All participants were native speakers of
English.
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REVISING TEXT DISCREPANCIES 7
Apparatus. The experiments used three Pentium 4 PC computers running
Superlab software to record responses. Participants sat in front of a Dell™ color
monitor with their hands on the keyboard. They used buttons on the keyboard
to provide their responses. Sentences were presented in the center of the screen
in standard upper- and lowercase type. Superlab software recorded participants’
responses including the keys pressed during the task, as well as latencies for each
response. These latencies were recorded as the time interval (in milliseconds)
from a probe word’s presentation onscreen to a press of the YES or NO key,
and a sentence’s presentation onscreen to a participant’s press of the NEXT key.
Materials. We began with the 24 stories from Rapp and Kendeou (2007),
with modifications as described later. Each story consisted of two episodes (see
Table 1 for examples). There were two versions of each first episode, which were
identical except for the final two sentences. These two sentences constituted the
different story contexts that participants read in the experiment. Across trait and
refutation with explanation contexts, the first sentence of the pair (sentence 6)
was always the same; this sentence provided behavioral evidence that suggested
the story’s protagonist possessed a particular trait. The second sentence of this
pair (sentence 7) was different across the two contexts. For trait contexts, this
sentence provided further support for the trait without providing any explicit
mention of the trait. For refutation with explanation contexts, this sentence
provided an explanation for the earlier behavior that was inconsistent with a
potential trait inference; these explanations included references to situational
rather than dispositional causes or statements, suggesting that characters had
changed in ways that no longer causally afforded such inferences.
The second episode immediately followed the first and described a situation
to which an inferred trait could potentially apply. This second episode was
identical across both story contexts. For each story, a trait-consistent outcome
was provided, describing an action performed by the protagonist of the story.
Each story, including both episodes and an outcome, was 13 sentences long.
For each story, we needed to select a single probe word that adequately
described the trait suggested in sentence 6. To do this, we presented 24 University
of Minnesota students with booklets that contained the first episode of each
of the stories (ending with sentence 6 so as not to include the supporting or
refuting statement). Participants were asked to write down three different words
that each could be used to describe the character. From this list, we selected 20
stories for which a single word emerged in at least 25% of the participants’
provided responses. Thus, we ended up with 20 stories, one half of which
included probes describing negative traits (e.g., dishonest, clumsy, forgetful)
and one half of which included probes describing positive traits (e.g., friendly,
responsible, hardworking). The average word frequency across all 20 trait probes
was 33.1 occurrences per million based on the Kucera and Francis (1967) word
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8 RAPP AND KENDEOU
TABLE 1
Sample Stories, Probes, and Outcomes From Experiments 1 and 2
Trait: messy
Episode 1
Albert was listening to the radio. He had finished getting ready to meet his friends at the movies. They
were going to see a new comedy that was getting rave reviews. He pulled a sweater over his head. Thenhe began to look for his shoes.Trait version:
They were buried under old candy wrappers, crumpled magazines, and some dirty laundry. Albertdidn’t care about keeping his room clean, and this is how it usually would look.
Refutation with explanation version (Experiment 1 only):
They were buried under old candy wrappers, crumpled magazines, and some dirty laundry. Albert
cared about the condition of his room, but had only moved into the apartment yesterday.Simple refutation version (Experiment 2 only):
They were buried under old candy wrappers, crumpled magazines, and some dirty laundry. Albert
cared about the condition of his room, even though it currently wasn’t up to par.
Probe Point 1: messyEpisode 2
Albert had to take the bus to go to the movies. He bought a newspaper to read during the ride to the theater.
Albert had finished leafing through the paper when his stop was announced. Albert put the newspaper onthe seat next to him. As he waited for the bus to stop, he noticed a sign asking riders not to leave garbageon the bus.Trait-consistent outcome:
Albert ignored the sign and got off the bus.Probe Point 2: messyComprehension question:
Did Albert read a sign on the bus? (YES)
Trait: forgetful
Episode 1
Greta had to pay her University fees this morning. She wouldn’t be able to register until she paid them,
so she had to pay today. She parked her car in the campus lot and headed over to the registrar’s office.She paid her bill and was now free to register. She headed back to the parking lot.Trait version:
It took her almost fifteen minutes to find where she parked her car. Greta could not seem to recall itslocation, and had to search to find it.
Refutation with explanation version (Experiment 1 only):
It took her almost fifteen minutes to find where she parked her car. Greta recalled the location of her
car but a truck had hidden it from view.Simple refutation version (Experiment 2 only):
It took her almost fifteen minutes to find where she parked her car. Greta did not have trouble recalling
the location, even though it took her that long.
Probe Point 1: forgetfulEpisode 2
When Greta got home she decided to bake a cake. She mixed the dough and put it into a pan. Then she
set the oven temperature for 450 degrees and put the cake in the oven. Greta decided to watch TV andsaw an interesting news report on former Governor Jesse Ventura. The cake baked in the oven.Trait-consistent outcome:
Greta only realized her mistake when she smelled the cake burning.
Probe Point 2: forgetfulComprehension question:
Did Greta watch a report on a former politician? (YES)
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REVISING TEXT DISCREPANCIES 9
frequency list. Across the 20 stories, the number of words in the two versions
of the critical sentence pairs (e.g., sentences 6 and 7) were equated (M D 13.71
words per pair across all stories with 13.26 for sentence 6 and 14.16 for sentence
7); within stories, the two versions of the critical sentence pairs were always
the same length. Two probe locations were selected for each of the stories: P1
appeared after the seventh sentence, and P2 after the final (13th) sentence (the
story outcome). Only one probe would be presented in each story, although
either probe point might be selected without prior warning as to its presentation.
We also wrote 20 filler and three practice stories that included situations
that were not directly related in any way to traits. The fillers were included to
reduce the likelihood participants might guess the purpose of the experiment.
Filler and practice stories were also 13 sentences long. Each filler story included
a pronounceable non-word probe to ensure an equal balance of real words and
non-words for the LD task. Finally, a single comprehension question was written
for each experimental, filler, and practice story. These questions were included
to insure that participants would attempt to comprehend the texts.
Design. The experiment was a within-subjects 2 (story context: trait vs.
refutation with explanation) � 2 (probe point: P1 vs. P2) design. There were
four versions of each of the 20 stories as a function of story context and probe
point. Using a Latin-square we constructed four lists so each story appeared in
a different version on each list. Thus, each list contained five trait stories with
a probe at P1, five trait stories with a probe at P2, five refutation stories with a
probe at P1, and five refutation stories with a probe at P2. The 20 filler stories
were added to each of the lists. Participants read each story from one of the four
lists presented in a different random order, with each list presented to an equal
number of participants (to ensure an equivalent number of observations for each
story version). Comprehension questions for the stories were counterbalanced
so each list contained 20 questions requiring YES and 20 questions requiring
NO responses.
Procedure. Participants began with 28 LD practice items, followed by three
practice stories, to become familiar with the task and keyboard controls. Each
story began with the words “Press NEXT for the next story” appearing on the
computer screen. Participants pressed the “A” key, labeled NEXT, to begin the
story. The first sentence of a story then appeared, and after reading it, participants
pressed the “A” key to advance to the next sentence. This response was repeated
for each sentence in the stories. After either the 7th sentence or the 13th sentence
of a story, depending on condition, a beep sounded; it was followed after 250 ms
by a string of letters surrounded by five asterisks on each side. Participants were
asked to decide whether the string was a real word. Participants indicated YES
(i.e., “This is a real word”) or NO (i.e., “This is not a real word”) by pressing
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10 RAPP AND KENDEOU
the “J” or “K” keys on the keyboard, respectively. The story then continued with
either the next sentence (if P1 was tested) or with a comprehension question (if
P2 was tested). After the conclusion of the story, or after completing the LD
for P2, a beep sounded and the string “* * * * * QUESTION * * * * *” was
displayed. This was replaced after 1,000 ms by a comprehension question and
participants pressed either the YES (i.e., “Yes, that is true”; J) or NO (i.e., “No,
that is false”; K) key to answer it. There was no time limit for responding to
either the LD or the comprehension question.
Results and Discussion
To assess the reliability of the results in our experiments, we conducted anal-
yses with both participants (F1) and items (F2) as random variables. The LD
analysis focused on correct LD responses only: Table 2 presents the mean LD
latencies, and Table 3 displays the mean reading times to story outcomes. We
eliminated LD and reading times falling more than 2.5 SDs above the mean
for each participant (de Vega, León, & Diaz, 1996). This resulted in a loss of
TABLE 2
Mean Lexical Decision Times (in Milliseconds) for
Correct Responses Only in Experiment 1
Trait
Context
Refutation C Explanation
Context M
Probe Point 1 1,104 (365) 1,266 (502) 1,185
Probe Point 2 1,159 (339) 1,222 (467) 1,191
M 1,132 1,244
Note. Standard deviations are shown in parentheses.
TABLE 3
Mean Reading Times (in Milliseconds) for
Story Outcomes in Experiment 1
Trait
Context
Refutation C Explanation
Context M
Probe Point 1 2,273 (556) 2,390 (662) 2,332
Probe Point 2 2,272 (530) 2,379 (600) 2,326
M 2,273 2,385
Note. Standard deviations are shown in parentheses.
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REVISING TEXT DISCREPANCIES 11
2.5% of the data. In addition, recall that questions were included after each
story to encourage participants to read for comprehension: Participants correctly
answered, on average, 85.1% of the comprehension questions correctly.
First, we predicted that participants would take longer to identify trait probes
that followed refutations with explanations compared to probes that followed
trait supporting statements. This prediction was supported with a main effect of
context: Participants took 112 ms longer to identify trait probes as real words
following refutations with explanations than following trait statements, F1(1,
35) D 5.051, MSE D 90,343, p < .05, �2D .126; F2(1, 19) D 8.049, MSE D
35,475, p < .05, �2D .298. There was no main effect of probe point (both
F s < 1) but some evidence of an interaction between context and probe point,
significant by participants only, F1(1, 35) D 4.642, MSE D 18,958, p < .05,
�2D .117; F2 < 1.7. Planned comparisons were conducted to evaluate whether
LD performance specifically differed at P1 and P2. At P1, participants took 162
ms longer to identify trait probes following refutations with explanations than
following trait supporting statements, F1(1, 35) D 8.220, MSE D 114,983, p <
.01, �2D .190; F2(1, 19) D 11.951, MSE D 47,166, p < .01, �2
D .386. The
63 ms difference at P2 was in a similar direction, but not significant (both F s <
1.5). The error analysis for LD responses was not significant for either of the
main effects or the interaction (all F s < 2.2). Outcome sentence reading times
also revealed a main effect of context, F1(1, 35) D 4.976, MSE D 90,812, p <
.05, �2D .124; F2(1, 19) D 4.220, MSE D 58,925, p D .054, �2
D .182, with
no main effect of probe point or interaction (all F s < 1). Participants took 112
ms longer to read outcomes in stories containing refutations with explanations
than in stories containing trait supporting statements.
We additionally explored whether there were differences in reading times to
the critical sixth and seventh sentences, to assess whether readers noticed the
refutations. Recall that sentence 6 was identical in both trait and refutation with
explanation contexts and, indeed, reading times to sentence 6 were the same
across these conditions (all F s < 1.5). In contrast, the content of sentence 7
differed as a function of story context, and participants appeared to notice this.
Participants took 398 ms longer to read sentence 7 if it provided a refutation with
an explanation than if it was a trait supporting statement, F1(1, 35) D 32.447,
MSE D 175,899, p < .01, �2D .481; F2(1, 19) D 7.798, MSE D 403,482, p <
.05, �2D .291. Surprisingly, a main effect of probe point was also obtained;
participants took 119 ms longer to read sentence 7 if the probe point appeared
immediately after that sentence than if it appeared at the conclusion of the story,
marginal by participants and significant by items, F1(1, 35) D 3.306, MSE D
154,698, p D .078, �2D .086; F2(1, 19) D 6.529, MSE D 43,693, p < .05,
�2D .256. We have no ready explanation for this effect given that participants
received no prior warning as to when a particular probe point would be tested.
Finally, there was no interaction between context and probe point (both F s < 1).
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Overall, readers appeared to build expectations about characters prior to
story outcomes as indicated by LD latencies. LD times were overall longer to
trait-consistent probes that followed refutations with explanations as compared
to probes that followed trait-supporting statements. The locus of this effect
was restricted to P1 (although it was in a similar direction for P2). The lack
of a significant effect at P2 is likely due to that point always following a
trait-consistent outcome; that outcome thus provided support for the trait, and
presumably influenced the availability of the trait probe. Most important for this
analysis, the effect was obtained for P1, in a position that preceded the final
story outcome by six sentences.
The reading time results also provide evidence that readers held expectations
for the ways in which characters would behave, as a function of preceding story
contexts. Participants took longer to read trait-consistent outcomes following
stories that contained refutations with explanations as compared to stories con-
taining trait-supporting statements. Finally, participants’ reading times to refuta-
tion and supporting statements indicated they noticed the unfolding discrepancy
between the initial trait information and refutation. Rapp and Kendeou (2007)
argued that noticing a discrepancy is a critical first step in the process of engaging
in revision (although by no means does noticing guarantee revision will take
place). Taken together, the results replicate earlier findings and show that the
effects can be due to encoding activity that occurs prior to the reading of final
story outcomes.
EXPERIMENT 2
Statements that contain explanatory refutations are effective at encouraging
readers to revise what they know about characters as texts unfold. Rapp and
Kendeou (2007) showed that simple refutations lacking explanatory power failed
to encourage readers to revise in a similar fashion. However, what leads to
those failures? It would be informative to know whether (a) revision failures
are observed immediately after simple refutations are read, suggesting they do
not encourage moment-by-moment revision; or (b) revision failures are due to
decisions that occur at story outcomes. This question is the same as that posed
in Experiment 1, but examines instances in which revision is unlikely.
For this experiment, we predicted that simple refutations would fail to exert
the same impact as explanatory refutations. Because previous work has shown
that simple refutations do not encourage readers to revise their expectations for
character behavior, we predicted no differences for outcome reading times or
LD responses to P2. If these effects are specifically due to reader failure to
update during reading, we also expected little in the way of LD differences as
a function of story contexts at P1. It is worth noting that the predictions here
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are for null effects. However, given the identical methodologies and closely
matched materials across Experiments 1 and 2, as well as previous research on
simple refutations, a null finding would inform hypotheses about the effects of
refutations on moment-by-moment reading activity. As an additional precaution
given our prediction of a null effect, we took steps to ensure we had sufficient
power to reject the null hypothesis if it was false. Based on Cohen (1988), we
used the effect size obtained in Experiment 1 and a power of .92 to compute
the required sample size for Experiment 2. This calculation (Cohen’s f D .40,
power D .92) yielded a required sample size of 35. Our actual sample size in
Experiment 2 was 40.
Method
Participants. Forty University of Minnesota undergraduates participated in
this study for course credit. All participants were native speakers of English.
Apparatus. The apparatus was identical to that in Experiment 1.
Materials. The same stories, probes, and fillers were used as in Experi-
ment 1 with the following modifications. The stories included either trait con-
texts (the same as in Experiment 1) or simple refutation contexts (see Table 1 for
examples), differing only as a function of sentence 7. Simple refutations contrast
with the explanatory refutations provided in Experiment 1 in that they suggest,
in sentence 7, that a trait inference would be inappropriate without providing an
explicit, causal explanation why.
Design. The design was identical to Experiment 1.
Procedure. The procedure was identical to Experiment 1.
Results and Discussion
Table 4 presents the mean LD times for correct responses and Table 5 displays
mean reading times to story outcomes. We eliminated recognition and reading
times falling more than 2.5 SDs above the mean for each participant, for a loss
of 2.28% of the data. Participants correctly answered, on average, 85.4% of the
comprehension questions correctly.
We predicted that participants would exhibit no differences in their LD probe
latencies as a function of story context or probe point. Neither of the main effects
nor the interaction was significant (all F s < 2.9). The error analyses revealed
no differences across conditions (all F s < 1.3). The data also supported our
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TABLE 4
Mean Lexical Decision Times (in Milliseconds) for
Correct Responses Only in Experiment 2
Trait
Context
Simple Refutation
Context M
Probe Point 1 1,134 (415) 1,154 (371) 1,144
Probe Point 2 1,207 (565) 1,152 (433) 1,180
M 1,171 1,153
Note. Standard deviations are shown in parentheses.
TABLE 5
Mean Reading Times (in Milliseconds) for
Story Outcomes in Experiment 2
Trait
Context
Simple Refutation
Context M
Probe Point 1 2,192 (516) 2,176 (543) 2,184
Probe Point 2 2,123 (500) 2,192 (543) 2,158
M 2,158 2,184
Note. Standard deviations are shown in parentheses.
prediction that reading times to the outcome sentences would not differ (all
F s < 1.9).
As a further check of the influence, or rather lack of influence, of simple
refutations, we tested whether readers nevertheless noticed the discrepancies
they suggested. Similar to Experiment 1, participants exhibited no difference in
reading times to sentence 6 across conditions (all F s < 1). Participants did take
183 ms longer to read sentence 7 following simple refutations than following trait
supporting statements, F1(1, 39) D 37.943, MSE D 141,168, p < .01, �2D
.493; F2(1, 19) D 12.355, MSE D 225,297, p < .01, �2D .394, indicating
they noticed the discrepancies. Neither the main effect of probe point nor the
interaction between context and probe point was significant (all F s < 1.9).
These results supported our predictions, as well as tentative explanations
offered in previous work. Readers showed no evidence of revision either at story
outcomes or immediately after reading simple refutations, which suggests that
at no point was their trait model updated. However, it is interesting to note that
readers did appear to notice the discrepancies suggested by the content of the
simple refutations. In contrast to the findings from Experiment 1, noticing was
clearly not enough to encourage readers to act on those perceived discrepancies.
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These results suggest that whatever restraint readers exhibit with respect to
revision can appear as early as immediately after a refutation statement.
GENERAL DISCUSSION
These experiments explored the conditions under which readers revise what they
know about characters as they read. Previous studies have investigated these
issues by setting up potential discrepancies between information provided about
a character at early and later points in a text (Guéraud et al., 2005; O’Brien et al.,
1998; Rapp & Kendeou, 2007). Some of these projects have utilized reading
times to story outcomes as a measure of revision. This dependent measure is
one of a class of methodologies that examine the products of processing that
presumably occur at earlier time points (Rapp & Gerrig, 2006; Rapp & van den
Broek, 2005). It remains an open question, however, whether those products
constitute effects actually derived from earlier processing activity. This study
attempted to address this issue, using a combined analysis of LD and reading
latencies.
The results suggest, generally, that readers build trait models of characters,
and that these models are amenable to change under the right circumstances.
They additionally provide insight into when such change might begin to occur.
In Experiment 1, participants took longer to identify trait-consistent probes as
real words after reading explanatory refutations of an immediately preceding
trait, in contrast to statements that supported those traits. Thus, readers’ models
appeared to reflect the unfolding nature of character descriptions. In addition,
reading times to story outcomes indicated that these earlier encoding activities
exerted an influence on later story expectations: Participants took longer to
read trait-consistent outcomes when events had previously refuted those traits
than when events supported them. In Experiment 2, identical methodologies
were used to examine analogous issues with simple refutations. In contrast
to Experiment 1, simple refutations did not similarly influence readers’ probe
latencies or expectations for story outcomes. Overall, these findings provide
modest, converging evidence that readers do not spontaneously revise their trait
models unless refutation statements provide a salient reason for doing so.
For this project, the LD task was used to examine the retrieval of particular
concepts (i.e., character traits) from memory (e.g., T. P. McNamara, 2005).
To date, probe methodologies like the LD have been used to investigate the
encoding and retrieval of situation models (Bower & Morrow, 1990; Glenberg,
Meyer, & Lindem, 1987; Morrow, Bower, & Greenspan, 1989), the suppres-
sion and inhibition of text concepts (Gernsbacher, Robertson, Palladino, &
Werner, 2004; Linderholm et al., 2004), and the integration of inferences into
mental representations of text (Potts, St. John, & Kirson, 1989). However,
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a potential concern for this research is whether methodologies like the LD
provide a valid means of analyzing processes that occur during reading, or rather
assess processing that is dependent on the presentation of a probe (i.e., context
checking or backwards updating; de Vega, 1995; McKoon & Ratcliff, 1988).
Researchers have carefully considered the selection of such methodologies and
their effectiveness at detecting the moment-by-moment activation of concepts
during reading (e.g., Lucas, Tanenhaus, & Carlson, 1990; McKoon & Ratcliff,
1989; Potts, Keenan, & Golding, 1988; Whitney, Ritchie, & Crane, 1992). The
upshot of this work is that converging data from multiple methodologies is
necessary to protect against the potential limitations of any single task on its
own. The results described in this article will necessarily require replication with
other methods to confidently account for the time course and consequences of
refutations intended to foster revision activity.
For example, consider one alternative explanation for these findings. Par-
ticipants’ reading times to sentence 7 paralleled the LD times, which might
suggest that the refutations incurred processing difficulty that was not merely
restricted to the refutation statement, but spilled over to processing of the LD
probe—that is, the probe responses may have been influenced not just by
activation of any particular trait concept, but also by any inherent complex-
ity of the sentence immediately preceding the probe. This account would not
obviate the claim that readers appeared to notice the contradiction offered in
the refutation, but would call into question whether such noticing resulted in
revision (we thank an anonymous reviewer for pointing out this possibility).
Other methods (e.g., speeded response tasks, naming latencies, think-alouds),
experimental manipulations (e.g., delays between sentences and probes), and
stimuli controls (e.g., accounting for sentence difficulty and textual coherence)
should prove useful in future work attempting to reconcile the nature of the
updating process. However, regardless of whether updating is due to context
checking or moment-by-moment revision activity, these results further affirm
the utility of explanatory refutations as an effective method of encouraging such
updating.
An additional concern for this study might be raised with respect to the
nature of the probes selected in these experiments. The probes associated with
“yes” decisions in the LD task were always trait related. This, one might argue,
could set up task demands that encouraged readers to build trait models, or
to expect trait-related probes to follow events that suggested such models. The
critical finding for these experiments, however, is that participants’ responses
to trait probes differed as a function of the refutation, or lack thereof, provided
in the text. The pattern of LD responses argues against this being due solely
to anticipatory processes linked to item-specific associations. Readers’ revision
of their trait models was not uniformly influenced by this type of overarching
strategy.
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One broader conceptual issue for these kinds of studies is whether the con-
ditions that foster revision with respect to characters during text experiences
might generalize to other instances of potential updating, including revision
with respect to plot-driven logic and declarative facts or other text dimensions,
such as time and space (Rapp & Taylor, 2004; Zwaan & Radvansky, 1998).
This issue is of considerable theoretical importance given that the ways in which
individuals encode and update information about characters (and more generally,
people and social experiences) might be specialized or particularly well-practiced
(Just & Carpenter, 1988; Uleman, Hon, Roman, & Moskowitz, 1996). Whether
character-based processes are privileged or not, the types of experiences that act
on these processes may be broadly influential during the comprehension of texts
and the updating of text representations (Taylor & Tversky, 1997; Trabasso &
van den Broek, 1985; van den Broek, 1994). Consider that causality is viewed
as playing an important role in a variety of situations that involve the encoding,
updating, and retrieval of text representations; in some cases, causality even
encourages text processing that might not occur spontaneously (e.g., Hakala,
1999; Jahn, 2004). Based on work examining the influence of causality during
reading, as well as studies that have identified conditions that foster conceptual
change (Diakidoy, Kendeou, & Ioannides, 2003; Guzzetti, Snyder, Glass, &
Gamas, 1993; Maria & MacGinitie, 1987; Posner, Strike, Hewson, & Gertzog,
1982; Vosniadou & Brewer, 1987), we hypothesize that the effects derived from
explanatory refutations might generalize to a variety of discourse experiences.
Evidence from these literatures also suggests that causal information increases
the degree to which readers focus on text elements, which would be a necessary
first step in revising prior representations. If readers are unaware of inconsis-
tencies in a text, they are unlikely to engage in the types of activities necessary
to revise expectations based on what they have read. The results of this study,
along with previous work (e.g., Dole, 2000; Hewson & Hewson, 1984; Kendeou
& van den Broek, 2007; Posner et al., 1982; van den Broek & Kendeou, 2008),
suggest that such noticing on its own, however, is insufficient to instantiate
revision. Factors such as motivation, task instructions, prior knowledge, reader
preferences, and so on, probably interact in complex ways such that readers’
processing characteristics and beliefs, text variables, and task demands all, to
some degree, contribute to the propensity to revise. For example, beliefs about
the credibility of a source affect the likelihood that individuals will be persuaded
by arguments (e.g., Petty & Wegener, 1998). Credibility judgments for sources,
arguments, and explanations might therefore influence readers’ noticing and
acting on refutations.
Related to this issue, the propensity to revise previous text information may
be, to some degree, underestimated in experiments such as those described
in this article. Some researchers have contended that studies implementing
experimenter-designed texts (so-called “textoids”) might provide an incomplete
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picture of the processing activities readers routinely engage in during naturalistic
reading (Graesser, Millis, & Zwaan, 1997). For example, readers might be
differentially motivated to construct coherent representations depending on the
quality of the content offered in experimental texts (e.g., Gámez & Marrero,
2001). The current set of materials included several instances of contradictions
and inconsistencies, which may have encouraged careful processing of the texts
or, in contrast, may even have led participants to discount the importance of
revision based on repeated cases with contradictory descriptions. Many studies
of text comprehension rely on “textoids” in their investigations and, indeed,
some theoretical investigations would be quite difficult without them (Sanders
& Noordman, 2000). Continued study of revision would benefit from examining
the impact of real-world cases of refutations such as those commonly found in
newspaper retractions, product recalls, and even political debate to evaluate the
naturalistic activities involved in potential cases of revision. A good base for
such work already exists with investigations of the types of refutations found in
science textbooks and classroom discourse (e.g., Guzzetti, Williams, Skeels, &
Wu, 1997).
Nevertheless, the empirical work on refutations that has utilized experimen-
tally controlled materials, to date, has demonstrated that readers often fail to
conduct elaborative processing unless task demands or texts necessitate such
activity (van den Broek, Rapp, & Kendeou, 2005). The notion that, for the most
part, revision does not occur spontaneously fits nicely with several existing
accounts of text comprehension. The minimalist approach (McKoon & Ratcliff,
1992) suggests that processes such as inference construction and logical evalu-
ation need not occur unless readers expend effort to do so. Other researchers,
in a similar vein, have contended that readers might not engage in elaborative
processing, but rather build “good-enough” representations that are sufficient
for a basic understanding of texts (Ferreira, Bailey, & Ferraro, 2002; Klin,
Guzmán, Weingartner, & Ralano, 2006). Thus, we take the findings here as
further evidence that readers’ attempts at comprehension need not guarantee a
fully formed mental representation of the entire situation. Rather, readers build
a representation of events described in texts that is more piecemeal (Sanford
& Graesser, 2006) and, as such, may fail to reconcile inconsistencies and dis-
crepancies. Explanatory refutations that directly and explicitly denote logical
gaps via explanations stand a greater chance of encouraging readers to resolve
potential inconsistencies through revision and perhaps build more coherent text
representations.
One interesting and potentially informative extension of such work that might
prove informative to research on both text cohesion and the coherence of readers’
mental models could examine the role of connectives in the processing of
refutations. For these experiments, the seventh sentence of each text utilized
discourse markers that established additive (e.g., “and”), causal (e.g., “because”),
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and adversative (e.g., “but”) relations between clauses (e.g., Murray, 1997).
Refutations that included explanations were more likely to employ adversative
relations than simple refutations and trait-supporting statements, as such relations
are often a direct consequence of attempts to negate preceding content in a clause
(e.g., Knott & Sanders, 1998). Research has suggested that connectives may dif-
ferentially influence the online and offline processing of explanations (Kamalski,
Lentz, Sanders, & Zwaan, 2008; Maury & Teisserenc, 2005; Millis, Golding, &
Barker, 1995; Millis & Just, 1994) and, thus, a focus on the connective relations
provided in refutations may prove useful for further understanding the extent of
their effects on readers’ representations of texts.
Indeed, explanations (particularly causal ones) have been directly linked to
the coherence of a reader’s mental representation (e.g., Graesser, Singer, &
Trabasso, 1994; Kintsch, 1988) and feelings of satisfaction in the reader that
he or she understands the material (Brewer, Chinn, & Samarapungavan, 2000).
The importance of explanations in establishing coherence is also reflected in the
fact that many interventions aimed at improving reading comprehension foster
the construction of explanations via externally or internally generated questions
(Pressley, 2000; van den Broek, Tzeng, Risden, Trabasso, & Basche, 2001)
or through self-explanations (Chi, deLeeuw, Chiu, & LaVancher, 1994; D. S.
McNamara, 2004). Thus, our beliefs about what texts are about, and whether
we understand them, are a function not only of the cohesiveness of texts, but also
the ways in which readers build coherence among the elements of such texts.
Revision exemplifies one set of activities that, under the right conditions, can
influence how we build mental representations for what we read, and whether
those coherent representations match the actual situations described in texts.
ACKNOWLEDGMENTS
This material is based on work supported by the Institute of Education Sciences
Grant R305G040021 and a Faculty Summer Fellowship from the Office of the
Dean of the Graduate School at the University of Minnesota awarded to David
N. Rapp, as well as a Research and Development mini-grant from the National
Science Foundation awarded to David N. Rapp and Panayiota Kendeou. We
thank Tuyen Trinh for her assistance with data collection. We are also very
grateful to Sid Horton and three anonymous reviewers for their comments on
an earlier version of the manuscript.
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