Conscious and unconscious detection of semantic anomalies.

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Conscious and unconscious detection of semantic anomalies Brenda Hannon

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Department of Psychology and Sociology, Texas A&M–Kingsville, Kingsville, TX 78363, USA Published online: 27 Jan 2015.

Click for updates To cite this article: Brenda Hannon (2015): Conscious and unconscious detection of semantic anomalies, The Quarterly Journal of Experimental Psychology, DOI: 10.1080/17470218.2014.982138 To link to this article: http://dx.doi.org/10.1080/17470218.2014.982138

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THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2015 http://dx.doi.org/10.1080/17470218.2014.982138

Conscious and unconscious detection of semantic anomalies Brenda Hannon

Downloaded by [University of Montana] at 22:01 06 April 2015

Department of Psychology and Sociology, Texas A&M–Kingsville, Kingsville, TX 78363, USA

When asked What superhero is associated with bats, Robin, the Penguin, Metropolis, Catwoman, the Riddler, the Joker, and Mr. Freeze? people frequently fail to notice the anomalous word Metropolis. The goals of this study were to determine whether detection of semantic anomalies, like Metropolis, is conscious or unconscious and whether this detection is immediate or delayed. To achieve these goals, participants answered anomalous and nonanomalous questions as their reading times for words were recorded. Comparisons between detected versus undetected anomalies revealed slower reading times for detected anomalies—a finding that suggests that people immediately and consciously detected anomalies. Further, comparisons between first and second words following undetected anomalies versus nonanomalous controls revealed some slower reading times for first and second words—a finding that suggests that people may have unconsciously detected anomalies but this detection was delayed. Taken together, these findings support the idea that when we are immediately aware of a semantic anomaly (i.e., immediate conscious detection) our language processes make immediate adjustments in order to reconcile contradictory information of anomalies with surrounding text; however, even when we are not consciously aware of semantic anomalies, our language processes still make these adjustments, although these adjustments are delayed (i.e., delayed unconscious detection). Keywords: Semantic anomalies; Moses illusion; Conscious detection; Unconscious detection.

What superhero is associated with bats, Robin, the Penguin, Metropolis, Catwoman, the Riddler, the Joker, and Mr. Freeze? If you answered Batman then you just succumbed to a semantic illusion because Batman protects Gotham City not Metropolis. People often fail to notice anomalies in questions like the Batman one, even though they know that Batman protects Gotham City and even when they are warned in advance that there will be anomalous questions (e.g., Erickson & Mattson, 1981; Hannon, 2014; Hannon & Daneman, 2001; Reder & Kusbit, 1991; Shafto & MacKay, 2000). Indeed, recent studies in the laboratory provide strong evidence of such shallow or incomplete semantic processing (e.g., Bohan & Sanford, 2008; Daneman, Hannon, & Burton,

2006; Daneman, Lennertz, & Hannon, 2007; Hannon & Daneman, 2001, 2004; see Hannon, 2014; Sanford & Sturt, 2002; for a review). In this article Just, Carpenter, and Woolley’s (1982) word-by-word moving-window technique is used to investigate immediate and delayed conscious and unconscious detection of semantic anomalies in questions like the Batman one.

Background One of the first pieces of empirical evidence for shallow semantic processing was by Erickson and Mattson (1981). In their study, participants completed a detection-based semantic anomaly task in which they read aloud anomalous and

Correspondence should be addressed to Brenda Hannon, Department of Psychology and Sociology, Texas A&M–Kingsville, Kingsville, TX 78363, USA. E-mail: [email protected] © 2015 The Experimental Psychology Society

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nonanomalous questions, such as How many animals of each kind did Moses take on the ark? (anomalous) or What is the capital of Canada? (nonanomalous). Then participants (a) answered the question, (b) said don’t know if they did not know the answer, or (c) said wrong if they detected something wrong with the question. Despite being warned in advance that some of the questions might include errors, participants frequently responded two to the Moses question even though they knew that it was Noah and not Moses who took two animals of each kind on the ark (e.g., Erickson & Mattson, 1981; also see Bredart & Docquier, 1989; Bredart & Modolo, 1988; Büttner, 2007; Hannon & Daneman, 2001; Reder & Kusbit, 1991; van Oostendorp & de Mul, 1990; van Oostendorp & Kok, 1990; Shafto & MacKay, 2000). People genuinely fail to notice the imposter word (e.g., Moses) and are not simply cooperating with the experimenter or failing to encode it (e.g., Erickson & Mattson, 1981; Reder & Kusbit, 1991). Furthermore, it appears that people fail to detect an anomaly when an anomalous word has many semantic features in common with the correct word in memory (e.g., Hannon, 2014; Hannon & Daneman, 2001; van Oostendorp & de Mul, 1990). Indeed, people are less likely to detect an anomaly if the word posing for Noah is Moses than if it is Adam because Noah and Moses have more common features (i.e., old men, long robes, biblical stories about water, Old Testament) than do Noah and Adam (i.e., Old Testament). On the other hand, people always detect an anomaly if the word Clinton is posing for Noah because these words have few, if any, common features (e.g., Erickson & Mattson, 1981; Hannon & Daneman, 2001). In addition, people fail to detect an anomaly when there are many contextual cues that lead to an incorrect answer (e.g., Hannon & Daneman, 2001). Indeed, people are less likely to detect an anomaly in questions like What superhero is associated with bats, Robin, the Penguin, Metropolis, Catwoman, the Riddler, the Joker, and Mr. Freeze? versus What superhero is associated with bats, Robin, Metropolis, as well as the Penguin,

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the Riddler, and the Joker? because the former question has eight contextual cues that lead to the incorrect answer whereas the latter one has six (i.e., superhero, bats, Robin, the Penguin, Catwoman, the Riddler, the Joker, and Mr. Freeze versus superhero, bats, Robin, the Penguin, the Riddler, and the Joker). The phenomenon of semantic illusions is theoretically important because it suggests that people are not scrupulous when processing text (e.g., Hannon & Daneman, 2001, 2004; van Oostendorp & Kok, 1990). Although some theories of sentence processing suggest that semantic analysis is exhaustive and complete (see Barton & Sanford, 1993; Hannon, 2014; Hannon & Daneman, 2001; Just & Carpenter, 1980; MacDonald, Pearlmutter, & Seidenberg, 1994, for a discussion of this point), semantic illusion research suggests that people frequently adopt a “good enough” approach to sentence processing (e.g., Ferreira, Ferraro, & Bailey, 2002) inasmuch as (a) integration of successive words in a text is often partial (e.g., Hannon & Daneman, 2001, 2004; van Oostendorp & Kok, 1990; see Sanford & Sturt, 2002, for a review), (b) semantic representations are often incomplete, (c) matches of words in the text to meanings in memory are often less than perfect (e.g., Hannon & Daneman, 2001; Reder & Kusbit, 1991), and (d) awareness of semantic information is sometimes reduced (i.e., the reduced awareness hypothesis, Sanford, Leuthold, Bohan, & Sanford, 2011). The phenomenon of semantic illusions also challenges some influential models of reading comprehension, especially those models that advocate the maintenance of local coherence over retaining global coherence (Hannon & Daneman, 2004). According to the minimalist hypothesis, the primary goal of reading comprehension is to maintain local coherence, and only in the rare instance of an inconsistency do readers use or refer to more global information, such as the passage theme (McKoon & Ratcliff, 1992). Semantic illusion research challenges such theories because it shows that people not only frequently fail to detect an anomalous word (e.g., Moses) at a local level but also frequently answer an anomalous question

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CONSCIOUS AND UNCONSCIOUS ANOMALY DETECTION

based on its global theme (e.g., Barton & Sanford, 1993; Bohan & Sanford, 2008; Daneman et al., 2006, 2007; Hannon & Daneman, 2004). This has led some researchers to suggest that theories of comprehension need to acknowledge that people often form representations of the text that are incomplete or underspecified (e.g., Bohan & Sanford, 2008; Hannon & Daneman, 2004; see Sanford & Sturt, 2002, for a review). Most studies have assessed anomaly detection using offline measures, like the number of correctly identified detections in a detection-based semantic anomaly task similar to the one used by Erickson and Mattson (1981); although recently a few studies have employed more online reading measures such as eye tracking (e.g., Daneman et al., 2006, 2007) and event-related potentials (ERPs; Bohan, Leuthold, Hijikaata, & Sanford, 2012; Sanford et al., 2011; Wang, Hagoort, & Yang, 2009). For example, using ERP technology, Sanford et al. (2011) observed N400 peaks for detected anomalies but not for undetected anomalies. Nevertheless, as noted by Bohan and Sanford (2008), most applications of both offline and online measures have depended on people being consciously aware of an anomaly and saying so (see Bohan et al., 2012, for an exception). These authors further noted that with the right design, disruptions to semantic processing might exist even when people are not consciously aware of an anomaly—a speculation that, if true, would provide evidence that people unconsciously detect semantic anomalies. In the context of language processing, such a finding is important because it tells us that even though our language processes may slow down in an attempt to reconcile an anomaly with the surrounding text, such reconciliations can be beyond our level of awareness. Bohan and Sanford (2008) explored conscious and unconscious detection of semantic anomalies by assessing disruptions to reading as people completed a semantic anomaly detection task. Comparisons of reading times between undetected anomalous versus nonanomalous control statements revealed no disruptions in eye tracking measures for undetected anomalies—a finding that suggests that people do not unconsciously

detect anomalies (see Sanford et al., 2011, for a similar finding using ERPs). In contrast, comparisons of reading times for detected versus undetected anomalous questions revealed significant disruptions in eye tracking measures for detected anomalies—a finding that suggests that people consciously detect anomalies. However, Bohan and Sanford’s evidence for this latter effect was limited to measures of delayed detection—that is, (a) total number of fixations in the critical region of the text where the anomaly was located and (b) total reading time in the critical region—and not measures of immediate detection (i.e., first pass reading times, defined as the sum of the fixations in a region from the time the region is first entered to the time it is first exited). In the larger context, these null findings are somewhat surprising, especially when there is ample research showing immediate detection of other kinds of errors and inconsistencies (e.g., Braze, Shankweiler, Ni, & Palumba, 2002; Daneman, Reingold, & Davidson, 1995; Wang et al. 2009). By using ERPs, Sanford et al. (2011), for example, showed differences in immediate ERP measures between detected versus undetected anomalies. As well, Braze et al. (2002) used eye tracking technology to capture detections of syntactic and pragmatic anomalies, and Daneman et al. (1995) used eye tracking technology to capture detection of homophonic and nonhomophonic errors. On the other hand, Bohan and Sanford’s lack of evidence for immediate detection of anomalies is not an isolated occurrence (see Daneman et al., 2006, 2007). Indeed, using eye tracking technology, Daneman et al. (2006) also failed to show immediate detection of semantic anomalies. One plausible explanation for these null findings is that perhaps an inadequate number of critical stimuli were used in order to observe effects using first pass eye tracking measures. Indeed, Bohan and Sanford’s (2008) findings were based on 11 anomalous stimuli, and Daneman et al.’s (2006) findings were based on only three. Further, in both studies, anomalous stimuli were distributed between measures assessing either undetected or detected anomalies, leaving approximately 5–6


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passages per type of detection in Bohan and Sanford’s study and approximately 1.5 passages in Daneman et al.’s (2006) studies. With so few items per type of detection, the probability for detecting disruptions in reading was also reduced. This probability is especially relevant for effects like immediate conscious and unconscious detection of anomalies, which were assessed by a single dependent measure (i.e., first pass reading) rather than multiple measures like those used for delayed conscious detection. Indeed Bohan et al. (2012), who showed a different ERP signature for missed anomalies compared to detected anomalies and controls, used considerably more stimuli.

The present study The present study used a large number of stimuli (e.g., 57 anomalous questions in Experiment 1) in a detection-based semantic anomaly task in order to assess immediate and delayed online disruption to question processing even when the anomalies go undetected. In order to assess online reading during the anomaly task, the present study used Just et al.’s (1982) word-by-word moving-window technique. In the word-by-word moving-window technique, the entire question/statement is hidden from the reader except for the one word that is currently being read. When a reader is ready for the next word, he or she forces the “window” along from left to right by pressing a key, and the reading time for the previous word is recorded by the computer. Just et al. argue that reading times for individual words obtained from the word-byword moving-window technique are similar to gaze durations for individual words obtained from eye-tracking technology. Indeed, Just et al.’s results suggest that in the word-by-word movingwindow technique, readers initiate the processing of each word as soon as they encounter it rather than buffer the words and delay processing. In the context of the present study, the word-byword moving-window technique is suitable to include in a detection-based semantic anomaly task because both the moving-window technique and detection-based semantic anomaly tasks do not allow participants to regress back to earlier

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words in a question. Indeed, Reder and Kusbit (1991) used Just et al.’s (1982) word-by-word moving-window technique in their anomaly detection task, and Bohan et al. (2012) used a word presentation method in their ERP study. Additionally, both the word-by-word moving-window technique and detection-based anomaly tasks require participants to read each word in a question. Finally, and perhaps most importantly, given that reading times obtained from the word-by-word movingwindow technique most closely resembles first pass gaze durations in eye tracking (Just et al., 1982) and given that the moving-window technique does not allow a reader to look back at previous text, the reading times reported in the present study would be most consistent with first pass gaze durations for individual words observed in eye-tracking studies. Of particular interest to the present study was the time spent reading anomalous words in anomalous questions because this dependent measure captured immediate disruptions to semantic processing. The times spent reading the first and second words following anomalous words were also of interest because these dependent measures (i.e., first words following anomalous words, second words following anomalous words) captured delayed disruptions to semantic processing. In addition, because Hannon and Daneman (2001) observed that detection of semantic anomalies was influenced by the number of contextual cues, the present study systematically varied the positions of the anomalous words in the anomalous questions. The idea here is that perhaps immediate and delayed detections of anomalies might vary as a function of the number of contextual cues that precede the anomalous words. Consider, for example, the questions in Table 1 with anomalous words positioned early, in the middle, and later. Because only one contextual cue precedes an early anomalous word, an early anomalous word is not actually anomalous when it is first read. Rather, only after the reading of subsequent contextual cues does an early anomalous word become anomalous. Consequently, when people read a question with an early anomalous word they will not detect the early anomalous word immediately because



Table 1. Examples of position manipulation in anomalous questions that were used in the detection and gist conditions Position

Anomalous question

Early cXccccccc (a) What superhero is associated with Metropolis, bats, Robin, the Penguin, Catwoman, the Riddler, the Joker, and Mr. Freeze? (b) What country includes the Aztec, Apache, Cheyenne, Comanche, Sioux, Mohawk, Shawnee, and Navajo? Middle ccccXcccc (a) What superhero is associated with bats, Robin, the Penguin, Metropolis, Catwoman, the Riddler, the Joker, and Mr. Freeze? (b) What country includes the Apache, Cheyenne, Comanche, Aztec, Sioux, Mohawk, Shawnee, and Navajo?


Late cccccccXc (a) What superhero is associated with bats, Robin, the Penguin, Catwoman, the Riddler, the Joker, Metropolis, and Mr. Freeze? (b) What country includes the Apache, Cheyenne, Comanche, Sioux, Mohawk, Shawnee, Aztec, and Navajo? Note: First contextual cues are bolded in table for illustration purposes only. Anomalous words are italicized in the table for illustration purposes only. First words following anomalous words and second words following anomalous words are underlined for illustration purposes only. As mentioned in the introduction and Materials section, the identical stimuli were used in the detection and gist conditions.

they do not know that it is anomalous. Rather, an early anomalous word is likely to have delayed detection; for example, perhaps one or two words after the anomalous word has been read, people begin to realize that it is indeed anomalous. In contrast, because a number of contextual cues precede an anomalous word positioned in the middle or later in a question, people are more likely to detect the anomalous word immediately because at this point people will know the question’s exact answer/topic and should therefore realize that the anomalous word does not fit this answer/topic. The present study includes two experiments that assessed conscious and unconscious detection of semantic anomalies. Both experiments manipulated the position of the anomalous words and included both detection and control conditions. The major difference between the two experiments was that Experiment 1 manipulated the instructions in the semantic anomaly task, whereas Experiment 2 manipulated the stimuli. The details and logic for each of these manipulations are provided in their respective experiments.

EXPERIMENT 1 Experiment 1 assessed conscious and unconscious detection of semantic anomalies by manipulating

the instructions of the anomaly task. Participants assigned to the detection condition followed the standard instructions that are used in semantic illusion research; that is, participants said wrong if they detected something wrong in a question, don’t know if they did not know the answer, or answered the question with a one-word answer (see Erickson & Mattson, 1981; Hannon & Daneman, 2001; Reder & Kusbit, 1991, for examples). Anomalous questions that participants identified as “wrong” were classified as having detected semantic anomalies, whereas anomalous questions that participants answered (i.e., the participants failed to detect the anomalies) were classified as having undetected semantic anomalies. Participants assigned to the gist condition read the same set of anomalous questions as those that were used in the detection condition. However, unlike in the detection condition, participants in the gist condition were asked to “ignore the anomalies” as if no error existed and to either answer the anomalous questions with a one-word answer or say “don’t know” if they did not know the answer. With the exception of a few wording differences, the instructions for this “gist” condition were identical to those of Reder and Kusbit (1991). By using the same anomalous words in the same anomalous questions in the detection and gist conditions, I was able to create a baseline measure of


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reading times for the same anomalous words in the same anomalous questions that was unfettered by the instructions of the detection condition. Questions that were answered correctly were classified as critical control semantic anomalies that were used in the analysis. The logic behind these two conditions was as follows: If participants are consciously detecting semantic anomalies then reading times for anomalous words in detected anomalous questions (assessed in the detection condition) should be longer than reading times for the same anomalous words in undetected anomalous questions (also assessed in the detection condition). Further, if participants are unconsciously detecting semantic anomalies then reading times for anomalous words in undetected anomalous questions (assessed in the detection condition) should be longer than reading times for the same anomalous words in critical control questions (assessed in the gist condition).

Method Participants and design The participants were 60 Introductory Psychology students who received course credit for their participation. All students were fluent English speakers and free of any known learning disability. Students were randomly assigned to either the detection condition or the gist (i.e., ignore anomalies) condition. Regardless of condition assignment, all students completed three tasks in the following order: (a) an anomaly detection task, (b) a distractor task, and (c) a posttest knowledge check. Position of imposter word (early, middle, or late) was a within-subjects variable that appeared in both the detection and gist conditions. Anomaly detection task Materials. The same stimuli were used in the detection and gist conditions. The 57 anomalous questions were created or adapted from other studies (Hannon & Daneman, 2001; Reder & Kusbit, 1991). Each question included 12 to 23 words (mean length = 15.05 words) and nine contextual cues (eight contextual cues + anomalous word; c

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X c c c c c c c, where “c” represents a contextual cue that provides a clue about the answer of the question, and “X” represents the imposter word). See Table 1 for examples of anomalous questions. The first contextual cue always served as the focus of the question (What country includes the Aztec, Apache . . . ?). Prior to the study, questions were normalized to ensure that students were familiar with most of the contextual cues in each question and that students believed that each question had only one anomalous word. Specifically, Introductory Psychology students, who were naive to the study’s purpose, were instructed to read anomalous questions and to circle all the words that they believed were incorrect. Questions with multiple words or nonanomalous words circled were modified, and another group of students again read the anomalous questions and identified incorrect words. This reiterative process continued until students were not circling multiple words per question, and it appeared that most students knew most of the contextual cues in a question. As Table 1 shows, three versions of each anomalous question were created. One version positioned the anomalous word early (i.e., c X c c c c c c c), one version positioned the anomalous word in the middle (i.e., c c c c X c c c c), and one version positioned the anomalous word late (i.e., c c c c c c c X c). All other properties were kept constant (e.g., the number of contextual cues, the order of the contextual cues, the number of words, etc.). Contextual Cue 2 (i.e., c X c c c c c c c) was selected as the early position because Contextual Cue 1 served as a clue about the question content (i.e., focus), and thus Contextual Cue 2 was the earliest possible position that an imposter word could appear. Contextual Cue 8 (i.e., c c c c c c c X c) was selected as the late position because, in order to equate the late and early positions, one contextual cue needed to follow the late position. Finally, Contextual Cue 5 was selected as the middle position (i.e., c c c c X c c c c) because it was situated at equidistance from the early and late positions (i.e., Contextual Cues 2 and 8). The 57 anomalous questions were randomly assigned to three stimulus sets such that each set




included 19 unique questions. Because there were three versions of each question (i.e., early, middle, late), the three sets were recombined to create six stimulus files with the constraint that each set included questions with anomalous words located in a different position. For example, File 1 included Set 1 early, Set 2 middle, Set 3 late; File 2 included Set 1 early, Set 3 middle, Set 2 late; File 3 included Set 2 early, Set 1 middle, Set 3 late, and so on. Students were randomly assigned to read one of these six stimulus files. Five students in each condition read the same stimulus file. Fifty-seven filler questions were added to each stimulus file, thus increasing each file to 114 questions. The filler questions contained contextual cues and queried trivia facts, but unlike the anomalous questions, they did not include imposter words (e.g., What country includes the Nile River, sphinxes, pyramids, Nefertiti, mummies, pharaohs, hieroglyphs, and Cleopatra?). There was no difference in the mean number of words in the filler (e.g., M = 14.83, SD = 1.95) and anomalous questions (e.g., M = 15.05, SD = 2.33), t(118) = 0.55, p = .58. Procedure. In the detection condition, students responded to each question in one of three ways: (a) don’t know, (b) wrong, or (c) answered the question. In order to familiarize students with the three types of responses, students completed practice questions before completing the critical portion of the anomaly detection task. As noted below, two keyboards were used: One keyboard was used by the students, and one keyboard was used by the research assistant. The 114 questions were randomly presented one at a time, and students read each word in each question aloud; see Erickson and Mattson (1981), Hannon and Daneman (2001), Reder and Kusbit (1991), and Shafto and MacKay (2000) for a similar procedure. Each question appeared one word at a time in the middle of a computer screen using Just et al.’s (1982) word-by-word moving-window technique, which was described in the introduction. The “window” was forced to the next word by pressing the “+” key, and the computer recorded the reading time for the

preceding word. Once a question was read, question marks (i.e., ???) appeared, signifying that the student should answer aloud using one of the three responses. The research assistant entered the student’s response using another keyboard. For a don’t know response the research assistant pressed the “2” key, for a wrong response the research assistant pressed the “3” key, and for an answered question the research assistant pressed the “1” key. If a student responded then within the same breath said “No, I meant to say X”, the requested alteration was noted and then changed at a later time. There were ,1.0% changes. In the rare circumstance that a student spent too much time reading each word in a question, the research assistant reminded the student to read at a normal pace. After responding to a question, students proceeded to the next question until all 114 questions were answered without breaking. The total time to complete all 114 questions was about 18 to 20 min. The procedure for the gist condition was identical to the one used in the detection condition except whereas the objective of the detection condition was to detect anomalies, the objective of the gist condition was to ignore any anomaly and just answer the question. Correctly answered anomalous questions (i.e., correct answers when the anomalous words were ignored) were categorized as critical control questions and were used to assess unconscious detection of semantic anomalies. Incorrectly answered questions and don’t knows were entered as incorrect and were not categorized as critical control questions. Distractor task The 30-minute distractor task included nine short passages and 45 multiple-choice questions taken from Scholastic Assessment Test (SAT) and Graduate Record Examinations (GRE) practice tests (e.g., Educational Testing Services, 1992; McCune, Wright, & Elder, 1999; Robinson & Katzman, 2002). Students were instructed to read a passage then answer its questions. Passages were not related to the anomalous questions used in anomaly tasks. The distractor task was added for two reasons. One reason was to introduce a break between the semantic anomaly task and the


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postknowledge check (see Hannon & Daneman, 2001, for a similar procedure, although see Experiment 2, which eliminated this task). The second reason was in order to lengthen the session time as per participant pool restrictions.

57 questions answered correctly. This result suggests that students had an adequate knowledge of the contents of the anomalous questions.

Posttest knowledge check task The posttest knowledge check assessed whether a student knew that the anomalous words did not fit the topic of the anomalous questions. There were 57 posttest knowledge check multiple-choice questions, one for each anomalous question—for instance, Batman protects _______ . 1) Gotham City 2) Metropolis 3) Atlantis. As this example shows, one choice was the correct word (e.g., Gotham City), one choice was the anomalous word (e.g., Metropolis), and the third choice (e.g., Atlantis) was semantically related to the correct word (e.g., Gotham City) although it did not appear in an anomalous question. In order to verify that the third choice in the posttest knowledge check was indeed semantically related to the correct word, two independent raters read two versions of each question, one version with the actual anomalous word, Metropolis, and one version with the semantically related word, Atlantis, and then they rated on a 5-point scale how much easier it was to detect one of the anomalous words (1 = no difference between questions, 3 = one question was moderately easier to detect, and 5 = one question was much easier to detect). The mean difference rating for the pairs of questions was 3.52 (SD = 0.74). This finding suggests that although the third choice (Atlantis) was semantically related to the correct word (Gotham City), its relatedness was neither equivalent to the imposter word (Metropolis) nor too unrelated. The questions were randomly presented one at a time in the middle of a computer screen. Students read each question stem aloud and then responded aloud by stating answer choice. Each question and its accompanying choices remained on the screen until a student selected a response, which was keyed in by the research assistant. Immediately after responding to a question, students proceeded to the next question until all 57 questions were completed. Mean performance was 48.45 out of

Unless otherwise stated, the alpha level was set to .05 for all analyses of variance (ANOVAs). All analyses were performed with participants (F1) and items as random variables (F2). In the item analysis, there were instances of missing values—for example, perhaps students failed to detect anomalous words in the middle position for Item 15. In instances such as these, the item was removed from the analysis. In addition, after testing, one question potentially had a wording problem and consequently was removed from all analyses. In total, 15 items were removed. For all ANOVAs, effect sizes were calculated with eta-squared (i.e., η2) using guidelines specified by Cohen (1988). Specifically, an η2 ≥ .14 was considered to be a large effect that is rare in the behavioural sciences, an η2 between .06 and .139 was considered to be a medium effect, an η2 between .011 and .059 was considered to be a small effect, and an η2 ≤ .01 was considered to be a trivial effect. See Hannon (2012, 2013), Hannon and Daneman (2007), and Hannon et al. (2010), for calculations and applications of effect sizes using eta-squared. In instances where interactions were marginal, and subsequent t tests were performed, effect sizes for the t tests were first calculated using Cohen’s d and were then converted to η2 for ease of interpretation.

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Results

Evidence of anomaly detection from offline postquestion responses The proportions of detected anomalous and critical control questions that were answered correctly on both the semantic anomaly task and the posttest knowledge check were calculated as a function of imposter word position. After removal of incorrectly answered questions, the proportion of anomalous questions detected was calculated by dividing a student’s number of correct “wrong” answers on the anomaly detection task by the number of questions answered correctly on the posttest knowledge check. “Don’t knows” were excluded from these




calculations because they are neither correct responses nor incorrect responses. For the critical control condition, the proportion of critical questions answered correctly was calculated by dividing the number of critical control questions answered correctly on the anomaly detection task by the number of questions answered correctly on the posttest knowledge check. The results revealed that approximately half of the anomalous questions were detected (i.e., approximately 28 observations), and half went undetected (i.e., approximately 28 observations). Twenty-eight observations per type of detection is optimal for the types of analysis proposed in the present study as it means that there are a large number of observations per condition. Evidence of anomaly detection from online reading data Median reading times were calculated as a function of type of detection (detected anomalous, undetected anomalous, critical control) and anomalous word position (early, middle, late). Medians were selected because unlike means they are less susceptible to extreme values; no other data trimming methods were used. Median reading times for detected anomalous words were based on anomalous words correctly identified in both the detection condition and the posttest knowledge check. Median reading times for undetected anomalous words were based on anomalous words incorrectly identified in the detection condition (i.e., students just answered the questions) but correctly identified on the posttest knowledge check. Median reading times for critical control anomalous words were based on questions that were answered correctly in both the gist-based anomaly task and the posttest knowledge check. Don’t know responses were excluded because they are ambiguous. There were three dependent measures. One measure assessed immediate effects while the other two measures assessed delayed effects. (a) Reading time of anomalous words, which assessed immediate effects, was the median reading time of anomalous words. (b) Reading time of first words immediately following anomalous words was the median reading time for the first words

that followed the anomalous words. (c) Reading time of the second words immediately following the anomalous words was the median reading time for the second words that followed the anomalous words. See Table 1 for examples of first and second words following anomalous words. Each dependent measure was used in two analyses. The first analysis examined immediate and delayed conscious anomaly detection as a function of anomalous word position. Specifically, median reading times were submitted to a 2 × 3 ANOVA with detection (detected, undetected) and anomalous word position (early, middle, late) as within-subjects variables. The general idea behind this analysis was that if people consciously detect semantic anomalies then average reading times for anomalous words in detected anomalous questions should be significantly longer than average reading times for anomalous words in undetected anomalous questions. The second analysis examined immediate and delayed unconscious anomaly detection as a function of anomalous word position. Specifically, median reading times were submitted to a 2 × 3 ANOVA with detection (undetected, critical control → anomalous questions in the gist condition) as a between-subjects variable and anomalous word position (early, middle, late) as a within-subjects variable. The general idea behind this analysis was that if people unconsciously detect semantic anomalies then average reading times for anomalous words in undetected anomalous questions should be significantly longer than average reading times for anomalous words in critical control questions. Table 2 presents the average median reading times and standard errors for each dependent variable as a function of detection and position of an anomalous word. Detected versus undetected anomalous words (conscious detection of semantic anomalies) Immediate effects. There was strong evidence for immediate conscious detection of semantic anomalies. As Table 2 shows, on average people spent 114 ms longer reading detected than reading undetected anomalous words (i.e., 1115


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Table 2. Median reading times for anomalous word, first word immediately following anomalous word, and second word immediately following anomalous word, and total read time as a function of detection and position of anomalous word in Experiment 1 Dependent measures


Type of anomalous word

Anomalous word

First

Detected anomalous words Early 918 (45) 964 (35) Middle 1254 (72) 988 (44) Late 1173 (73) 616 (32) Average 1115 (69) 856 (51) Undetected anomalous words Early 910 (63) 995 (46) Middle 1110 (59) 935 (35) Late 985 (48) 585 (26) Average 1001 (58) 838 (49) Critical control anomalous words Early 842 (39) 820 (32) Middle 933 (39) 857 (32) Late 914 (49) 578 (27) Average 896 (43) 752 (37)

Second

Total read

1005 (43) 951 (54) 1179 (90) 1045 (67)

12,098 (419) 12,025 (448) 12,440 (503) 12,188 (454)

933 (43) 868 (36) 1230 (92) 1010 (68)

12,099 (470) 12,362 (496) 12,121 (491) 12,194 (480)

846 (33) 781 (31) 989 (60) 872 (46)

11,556 (448) 11,276 (426) 11,273 (475) 11,369 (445)

Note: Reading times in ms. Standard errors in parentheses. Total read time does not include the amount of time needed to answer a question. Detected anomalous words are anomalous words that students identified as wrong in the detection condition, undetected anomalous words are anomalous words that students failed to identify in the detection condition, and critical control anomalous words are anomalous words from questions students answered correctly in the gist condition.

versus 1001 ms) [F1(1, 29) = 8.16, MSE = 71,288, p = .008, η2 = .05; F2(1, 41) = 13.02, MSE = 134,007]. There was also a marginally significant Detection × Position interaction such that reading times for detected and undetected anomalous words varied as a function of position [F1(2, 58) = 3.13, MSE = 54,060, p = .06, η2 = .02; F2(2, 81) = 9.58, MSE = 119,070]. As Table 2 shows, when anomalous words were positioned early, reading times were equivalent for detected versus undetected anomalous words (i.e., 918 versus 910 ms), t , 1.0. In contrast, when anomalous words were positioned in the middle, reading times were 144 ms slower for detected than for

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undetected anomalous words (i.e., 1254 versus 1110 ms), t(29) = 2.02, p = .053, and when they were positioned later reading times were 188 ms slower for detected than for undetected anomalous words (i.e., 1173 versus 985 ms), t(29) = 2.73. Finally, although not relevant to the subject of immediate conscious detection of anomalous words, there was a main effect for position [F1(2, 58) = 17.57, MSE = 62,417, p , .001, η2 = .19; F2(2, 81) = 10.85, MSE = 144,413]. Anomalous words positioned early in questions were read more quickly than those positioned later (i.e., 914 versus 1079 ms), and anomalous words positioned later in questions were read more quickly than those positioned in the middle (i.e., 1079 versus 1182 ms), min t(29) = 2.29. Delayed effects. Counter to the findings for immediate effects, there was no evidence for delayed conscious detection of semantic anomalies. As Table 2 shows, regardless of the dependent measure for delayed effects (i.e., first word or second word following anomalous words), reading times were equivalent in detected and undetected anomalous questions, max F1(1, 29) , 1.0, F2 , 1.0. Additionally, none of the two possible interactions of Detection × Position were significant (i.e., one interaction per dependent measure), max F1 , 1.0 and F2 , 1.0. In fact, only the main effects for position for first and second words following anomalous words were significant [min F1(2, 58) = 16.20, MSE = 90,357, η2 = .19; min F2(2, 81) = 25.90, MSE = 68,885], and these effects were not related to the subject of interest—namely, delayed conscious detection. As Table 2 shows, reading times for first words following anomalous words were significantly faster when they were positioned later in questions than when they were positioned either early or in the middle (i.e., 601 ms versus 979 and 962 ms), min t(29) = 10.17. This finding is not that surprising given that first words following anomalous words positioned later in questions were always function words like “and”. See Table 1 for examples. On the other hand, reading times for second words following anomalous words were significantly slower when they were positioned later than when they were positioned early or in the




middle (i.e., 1205 versus 969 and 910 ms), min t(29) = 2.50. Undetected anomalous words versus anomalous words from critical control questions (unconscious detection of semantic anomalies) Immediate effects. The evidence for immediate unconscious detection of semantic anomalies was limited to a marginally significant main effect for detection. On average, people spent 105 ms longer reading undetected anomalous words than reading anomalous words in critical control questions (1001 versus 896 ms) [F1(1, 58) = 3.40, MSE = 148,937, p = .07, η2 = .03; F2(1, 41) = 3.12, MSE = 218,168]. However, the Detection × Position interaction was not significant [F1(2, 116) = 1.44, MSE = 39,601, η2 , .01; F2 , 1.0]. Finally, there was a main effect for position [F1(2, 116) = 8.05, MSE = 39,601, η2 = .04; F2(2, 81) = 4.50, MSE = 100,216]. Anomalous words positioned early in the questions tended to be read more quickly than those positioned in the middle (i.e., 876 versus 1021 ms), t(59) = 4.11, p =.056, or later (i.e., 876 versus 949 ms), t(59) = 2.17. Delayed effects. The results provided evidence for delayed unconscious detection of anomalies. As Table 2 shows, people spent 86 ms longer reading the first words following anomalous words in undetected anomalous than in critical control questions (i.e., 838 versus 753 ms) [F1(1, 58) = 5.59, MSE = 60,726, p = .02, η2 = .03; F2(1, 41) = 4.90, MSE = 56,631, p = .056]. There was also a significant Detection × Position interaction [F1(2, 116) = 8.11, MSE = 20,051, p , .001, η2 = .02; F2(2, 81) = 3.89, MSE = 47,042]. As Table 2 shows, reading times for first words following anomalous words positioned early were 175 ms slower in undetected anomalous than in critical control questions (i.e., 995 versus 820 ms), t(58) = 3.12, and reading times for first words following anomalous words positioned in the middle were 78 ms slower in undetected anomalous than in critical control questions (i.e., 935 versus 857 ms), t(58) = 1.68, p = .05 (one-tailed test), η2 = .04. On the other hand, reading times for first words following

anomalous words positioned later were equivalent in undetected anomalous than in critical control questions, t , 1.0. Finally, there was a main effect for position [F1(2, 116) = 102.47, MSE = 20,051, η2 = .39; F2(2, 81) = 52.74, MSE = 37,982]. Reading times of first words following anomalous words positioned later were faster than first words following anomalous words positioned in the middle or early in questions (i.e., 582 . 896 and 908 ms), min t(59) = 10.51. This finding is not that surprising given that the first words following anomalous words positioned later were always function words like “and”. See Table 1 for examples. With respect to the second words following anomalous words, reading times were 138 ms longer in undetected anomalous than in critical control questions (i.e., 1010 ms versus 872 ms) [F1(1, 58) = 5.60, MSE = 153,893, p =.02, η2 = .05; F2(1, 41) = 9.98, MSE = 194,358]. There was also a marginally significant Detection × Position interaction [F1(2, 116) = 2.76, MSE = 51,474, p = .067, η2 = .01; F2(2, 81) = 5.19, MSE = 147,104]. As Table 2 shows, reading times for second words following anomalous words in undetected anomalous versus critical control questions were equivalent when they were positioned early or in the middle, max t(58) = 1.63. On the other hand, when they were positioned later, reading times for second words were 241 ms slower in undetected anomalous than in critical control questions (i.e., 1230 versus 989 ms), t(58) = 2.20, η2 = .07. In addition, there was a main effect for position [F1(2, 116) = 26.00, MSE = 51,474, η2 = .14; F2(2, 81) = 25.90, MSE = 147,104]. Reading times for second words following anomalous words positioned later in questions were significantly slower than those positioned early (i.e., 1109 versus 890 ms), which were slower than those positioned in the middle (i.e., 890 versus 824 ms), min t(59) = 2.73. Other effects. In order to determine whether questions in the gist condition were processed more quickly than questions in the detection condition, median reading times for entire questions (i.e., total read time shown in Table 2) were submitted


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to a 2 × 3 ANOVA with detection (undetected, gist) as a between-subjects variable and position (early, middle, late) as a within-subjects variable. The results were not significant (max F1 = 1.82, η2 , .01; F2 = 1.36). This lack of significance suggests that even though the instructions in the detection and gist conditions were quite different, the reading times of the questions in these two conditions were equivalent. Finally, in order to more closely examine reading times of detected anomalies and first and second words following detected anomalies, a 3 × 2 ANOVA was completed with type of word (detected anomaly, first word following anomaly, second word following anomaly) and position (middle, late) as within-subjects independent variables. The early position was eliminated from the analysis because, as noted earlier, the anomalous word is not anomalous until the reader encounters the subsequent contextual cues. The results revealed a significant main effect for type of word, F(2, 58) = 22.88, MSE = 2602781, p , .001, no main effect for position, F , 1.0, and a significant Type of Word × Position interaction, F(2, 58) = 18.42, MSE = 1,352,060, p , .001. Subsequent t tests revealed that location (i.e., middle, late) did not influence critical anomalous words, t(29) = 1.247, p = .222. On the other hand, first words in the middle position were read slower than first words positioned later, t(29) = 7.32, p , .001. In contrast, second words positioned in the middle were read faster than second words positioned later, t(29) = −2.60, p = .014.

EXPERIMENT 2 The results of Experiment 1 provided evidence for immediate conscious detection of semantic anomalies but no evidence for delayed conscious detection. The results also provided evidence for delayed unconscious detection of anomalies. Nevertheless some of these findings, in particular the findings for delayed unconscious detection of semantic anomalies, might be an artefact of a difference in the detection versus gist semantic anomaly tasks and not unconscious detection of

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anomalies per se. Specifically, whereas the detection task explicitly instructed students to detect anomalies, the gist task instructed students to answer each question. This instructional difference possibly influenced reading times, particularly reading times for anomalous words in the detection condition because the emphasis on detecting anomalies potentially encouraged students to read more slowly. Thus, by this account the significant differences in reading times for the first and second words following anomalous words in the detection versus gist conditions might be a consequence of different instructions in the detection versus gist conditions and not unconscious detection of anomalies. In order to eliminate this confounding explanation in Experiment 2, unconscious detection of semantic anomalies was assessed by comparing reading times for undetected anomalies in a detection condition versus nonanomalous critical words in a new, control condition. Unlike Experiment 1, which had different instructions in the detection and gist conditions but the same stimuli, in Experiment 2 the instructions for the detection and control conditions were identical but the stimuli were slightly different. Specifically, whereas the critical stimuli in the detection condition were anomalous (e.g., What state includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach?), the critical stimuli in the control condition were not anomalous (e.g., What country includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach?). Second, whereas the filler stimuli in the detection condition were nonanomalous, the filler stimuli in the control condition were anomalous. Experiment 2 also included an analysis that assessed whether the reading times of the critical anomalous versus nonanomalous questions were equivalent. Specifically, the reading times of the words immediately preceding the anomalous words in the critical anomalous questions were compared to the reading times of the words immediately preceding the matching critical words in the control nonanomalous questions.




For example, the reading time of the word Chattanooga in the anomalous question What state includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach? was compared to the reading time of the word Chattanooga in the nonanomalous control question What country includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach? The idea behind this analysis is that if the reading times for the words immediately preceding the critical words in the critical anomalous (e.g., Chattanooga) questions and critical nonanomalous questions (e.g., Chattanooga) are equivalent, then quite possibly students read the questions in the detection and control conditions at the same speed. On the other hand, if the reading times for the words immediately preceding the critical words in the critical anomalous questions are significantly different from the reading times for the words immediately preceding the critical words in the nonanomalous questions, then this would suggest that the questions in the detection and control conditions were not read at the same speed. In other words, the questions in the two conditions were processed differently. In addition, unlike Bohan and Sanford (2008), who used a within-subjects design, unconscious detection of anomalies in Experiment 2 was based on a between-subjects design. Although a withinsubjects design is often more desirous, especially in reaction time/reading time studies like the present study, stimuli restrictions forced the present study into a between-subjects design. Indeed, in order to retain approximately the same number of stimuli items per cell, a within-subjects design would have doubled the number of critical stimuli. Because the critical stimuli used in the present study were developed over a two-year period prior to Experiment 1 (see reiterative procedure described in the methods in Experiment 1), it was deemed prudent to use a between-subjects design and the existing critical stimuli rather than delay the present study for additional years for design/stimuli reasons. Finally unlike Experiment 1, Experiment 2 included only two positions for the anomalous words: middle

and late. The early position was eliminated because of stimuli limitations (i.e., not enough) that are noted below in the Materials section.

Method Participants and design The participants were 48 students who received a small $10.00 gift for their participation. All students were fluent English speakers and free of any known learning disability. The students were randomly assigned to either the detection condition or the nonanomalous control condition. Regardless of condition assignment, all students completed two tasks in the following order: (a) an anomaly detection task and (b) a posttest knowledge check. No distractor task was included in Experiment 2. Position of imposter word (middle or late) was a within-subjects variable. Anomaly detection task The structure of the anomaly detection task (e.g., the presentation of each question, the instructions, etc.) in both the detection and control conditions was identical to the anomaly detection task used in the detection condition in Experiment 1. The only difference between the detection and control conditions was the stimuli. Materials. Forty-four of the critical questions from Experiment 1 were altered in order to create both (a) an anomalous critical question and (b) a nonanomalous critical control question. The other 13 questions from Experiment 1 were not used because they could not be converted to a nonanomalous control question. For example, the anomalous question What state includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach? was altered to become the anomalous question What state includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanooga, and Daytona Beach? and the nonanomalous control question What country includes Orlando, Sarasota, St. Augustine, Key West, Miami, Tampa, Chattanoga, and Daytona Beach? All alterations involved small changes at the beginning of the questions. All other features of the


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questions, such as number of context words, number of words, and so on, remained constant. The 44 anomalous critical questions were assigned to one stimulus set, and the 44 nonanomalous control questions were assigned to another stimulus set. Students were randomly assigned to read one of these two stimuli sets. Because there were two positions for the critical word (i.e., middle or late), the stimuli in each set were divided in half so that 22 of the questions had the critical word positioned in the middle, and 22 of the questions had the critical word positioned late. Both the type of stimulus question (anomalous, nonanomalous) and the location of the critical word (middle, late) were counterbalanced so that they appeared an equal amount of times. Forty-four filler questions were added to each stimulus file, thus increasing each file to 88 questions. Like the anomalous questions, the filler questions contained contextual cues and queried trivia facts. When the critical questions were anomalous (i.e., those used in the detection condition, the filler questions did not include anomalies (e.g., What country includes the Nile River, sphinxes, pyramids, Nefertiti, mummies, pharaohs, hieroglyphs, and Cleopatra?). On the other hand, when the critical questions were nonanomalous (i.e., the control condition), the filler questions included anomalies (e.g., What country includes the Amazon River, sphinxes . . . ?). When the filler questions included anomalies, half of the anomalous words appeared in the middle of the questions, and the other half of the anomalies appeared later in the question. However unlike critical questions, the positions of the anomalous words were not counterbalanced in the filler questions, and the reading times of the critical words in these questions were not coded for recording by the computer. Posttest knowledge check task Unlike the posttest knowledge check used in Experiment 1, in the present posttest knowledge check students could: (a) select a single answer (e.g., 1, 2, or 3), (b) answer don’t know, or (c) indicate there was more than one answer. Mean performance was 83.8% of the 44 questions answered correctly; 11.2% of the 44 questions were answered

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with a wrong answer; 4.0% of the 44 questions were answered with don’t know; and 1.0% of the 44 questions were answered with more than one answer. All other features of this task, such as presentation, and so on, were identical to those of the posttest knowledge check task in Experiment 1.

Results Evidence of anomaly detection from offline postquestion responses As in Experiment 1, proportions of detected anomalous and control questions that were answered correctly were calculated as a function of imposter word position. In total, about 40% of the anomalous questions were detected. Although this is not the 50% detection rate that was observed in Experiment 1, this percentage still indicates that a suitable number of anomalies went detected and undetected. Evidence of anomaly detection from online reading data As in Experiment 1, there were three dependent measures: (a) median reading time of anomalous words, (b) median reading time of first words immediately following anomalous words, and (c) median reading time of the second words immediately following the anomalous words. Each dependent measure was submitted to (a) analyses that examined conscious detection of anomalies and (b) analyses that examined unconscious detection of anomalies. These two analyses were completed for participants and items. Eleven items were removed from the item analysis for the same reason as in Experiment 1. Detected versus undetected anomalous words (conscious detection of semantic anomalies) Immediate effects. Consistent with Experiment 1, there was evidence for immediate conscious detection of semantic anomalies. Indeed as Table 3 shows, on average people spent 202 ms longer reading detected than reading undetected anomalous words (i.e., 1146 versus 946 ms) [F1(1, 23) = 16.56, MSE = 57,681, p , .001, η2 = .32; F2(1, 32) = 9.87, MSE = 61,998, p , .004]. However,



Table 3. Median reading times for anomalous word, first word immediately following anomalous word, second word immediately following anomalous word, and word prior to anomalous word in Experiment 2 Dependent measures


Type of anomalous word Detected anomalous words Middle Late Average Undetected anomalous words Middle Late Average Critical control anomalous words Middle Late Average

Anomalous word

First

Second

Word prior to anomalous word

1143 (69) 1148 (69) 1146 (68)

977 (47) 667 (41) 822 (55)

850 (46) 1144 (102) 997 (84)

955 (43) 901 (57) 929 (47)

922 (42) 970 (60) 946 (37)

936 (60) 646 (39) 791 (58)

820 (47) 1118 (69) 969 (66)

902 (47) 921 (56) 912 (47)

934 (33) 956 (35) 945 (34)

848 (24) 644 (34) 746 (41)

847 (25) 985 (52) 916 (43)

938 (42) 911 (37) 925 (42)

Note: Reading times in ms. Standard errors in parentheses. Detected anomalous words are anomalous words that students identified as wrong in the anomaly condition, undetected anomalous words are anomalous words that students failed to identify in the anomaly condition, and critical control anomalous words are questions that students answered correctly in the nonanomalous control condition.

unlike in Experiment 1, there was no Detection × Position interaction, F1 , 1.0, F2 , 1.0. This lack of an interaction is not surprising given that the Detection × Position interaction in Experiment 1 was a consequence of significant differences for middle and later anomalous words in detected versus undetected anomalous questions and a lack of a significant difference for detected versus undetected anomalous words in the early position, an anomalous word position not included in Experiment 2. Indeed, a re-run of an analogous ANOVA for Experiment 1 revealed that the Detection × Position interaction became nonsignificant, F , 1.0, when the earlier anomaly location was removed. Finally, there was no main effect for position [F1(1, 23) = 1.21, MSE = 14,691, p = .28, η2 , .02; F2(1, 32) = 1.16, MSE = 67,240, p =.29]. Delayed effects. Consistent with Experiment 1, there was no evidence for delayed conscious detection of semantic anomalies. As Table 3 shows, regardless of the dependent measure for delayed effects (i.e., first words or second words following anomalous words) reading times were equivalent in detected

and undetected anomalous questions [max F1(1, 23) = 1.13, MSE = 20,276, p . .29, η2 , .01; max F2 , 1.0]. Additionally, neither of the two possible interactions of Detection × Position was significant (i.e., one interaction per dependent measure), max F1 , 1.0 and F2 , 1.0. In fact, only the main effects for position for first and second words following anomalous words were significant [min F1(1, 23) = 19.74, MSE = 106,930, p , .001, η2 = .15; min F2(1, 32) = 29.46, MSE = 150,551, p , .001], and these effects were not related to the subject of interest—namely, delayed conscious detection. As Table 3 shows, reading times for first words following anomalous words were significantly faster when they were positioned later in questions than when they were positioned in the middle (i.e., 656 ms versus 956 ms). This finding is not surprising given that the first word following anomalous words in the latter position were function words like “and”. On the other hand, reading times for second words following anomalous words were significantly slower when they were positioned later than when they were positioned in the middle (i.e., 1131 ms versus 835 ms).


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Undetected anomalous words versus anomalous words from critical control questions (unconscious detection of semantic anomalies) Immediate effects. As Table 3 shows, Experiment 2 revealed no evidence for immediate unconscious detection of semantic anomalies (946 versus 945 ms), F1 , 1.0, F2 , 1.0. This finding is inconsistent with those of Experiment 1, which showed a marginally significant effect. On the other hand, the remaining results—the lack of a significant interaction and a main effect for position—were identical to those of Experiment 1. Specifically, consistent with Experiment 1, there was no significant Detection × Position interaction, F1 , 1.0, F2 , 1.0, but there was a main effect for position, although this main effect was only for subjects [F1(1, 46) = 4.05, MSE = 7390, p = .05, η2 = .01; F2 , 1.0]. Anomalous words positioned later in questions tended to be read more slowly than those positioned in the middle (i.e., 963 versus 928 ms). Delayed effects. With respect to first words following anomalous words, as Table 3 shows, there was no main effect for delayed unconscious detection of semantic anomalies, F1 , 1.0, F2 , 1.0—a finding that is inconsistent with that of Experiment 1. There was, however, a marginal Detection × Position interaction [max F1(1, 46) = 3.37, MSE = 13,303, p = .073, η2 = .01; F2(1, 32) = 7.74, MSE = 37,373], such that reading times for first words following anomalous words positioned in the middle of questions were 88 ms slower in undetected anomalous than in critical control questions, t(46) = 2.36, η2 = .15. On the other hand, there was no difference for first words following anomalous words in the later position, t , 1.0. Finally, although not relevant to the question of unconscious detection of semantic anomalies, there was a main effect for position [F1(1, 46) = 110.28, MSE = 13,303, p , .001, η2 = .28; F2(1, 32) = 73.10, MSE = 53,354, p , .001], such that first words following anomalous words in the later position were read faster than first words in the middle position. With respect to the second words following anomalous words, there was no evidence for a

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significant main effect of unconscious detection [F1(1, 46) , 1.0; F2(1, 32) = 2.33, MSE = 93,917], a finding that is inconsistent with Experiment 1. This lack of a replication is likely a consequence of the removal of the early anomalous word position. Nevertheless, there was a marginal unconscious Detection × Position interaction [F1(1, 46) = 3.57, MSE = 43,405, p = .065, η2 = .02; F2(1, 32) = 3.52, MSE = 126,665] such that reading times for second words following anomalous words positioned later were 133 ms slower in undetected anomalous than in critical control questions, t(46) = 2.05, η2 = .05. In contrast, reading times were equivalent for second words following imposters positioned in the middle of questions, t(46) , 1.0. Finally, there was a main effect for position, F1(1, 46) = 26.34, MSE = 43,405, p , .001, η2 = .16, F2(1, 32) = 27.34, MSE = 98,464, such that second words following anomalous words located later were read slower than second words following anomalous words located in the middle. Other effects. In order to verify that there were no differences in the reading times for the anomalous critical questions versus the nonanomalous control questions, the median reading times for the word just prior to the critical anomalous word were submitted to an ANOVA using position (middle, late) as a within-subjects variable and condition (anomalous, control) as a between-subjects variable. As Table 3 shows, there were no significant effects. That is, the main effect for detection, the main effect for position, and the Detection × Position interaction were all nonsignificant, all F1s , 1.0, F2s , 1.0. This lack of significant results provides some evidence that students did not read the anomalous questions more slowly than the critical control questions. Finally, in order to more closely examine reading times of detected anomalies and first and second words following detected anomalies, a 3 × 2 ANOVA was completed with type of word (detected anomaly, first word following anomaly, second word following anomaly) and position (middle, late) as within-subjects independent variables. The results revealed a significant main effect




for type of word, F(2, 46) = 20.17, MSE = 1,284,093, p , .001, no main effect for position, F, 1.0, and a significant Type of Word × Position interaction, F(2, 46) = 25.44, MSE = 1,094,712, p , .001. Subsequent t tests revealed that location (i.e., middle, late) did not influence critical anomalous words, t , 1.0. On the other hand, first words in the middle position were read slower than first words positioned later, t(23) = 9.96, p , .001. In contrast, second words positioned in the middle were read faster than second words positioned later, t(23) = −3.32, p = .003.

GENERAL DISCUSSION Previous semantic illusion research suggests that people frequently fail to notice anomalies in questions like the Batman example, even though they know that Batman protects Gotham City and even when they are warned in advance that there will be anomalous questions (e.g., Erickson & Mattson, 1981; Shafto & MacKay, 2000). Rather, research suggests that people tend to adopt a “good enough” approach inasmuch as integration of successive words in the text is often partial (e.g., Hannon & Daneman, 2001; van Oostendorp & Kok, 1990), semantic representations are often incomplete, and matches of words in the text to meanings in memory are often less than perfect (e.g., Hannon & Daneman, 2001). However, we have limited knowledge as to whether detection of anomalies is immediate or delayed and the extent to which they are conscious or unconscious. The present study begins to address these limitations. The results of both experiments clearly revealed that detected anomalies were read more slowly than undetected anomalies, a finding that provides strong evidence for immediate conscious detection of semantic anomalies. On the other hand, the results revealed that reading times for the first and second subsequent words following anomalies were equivalent for both detected and undetected anomalies, a finding that provides no evidence for delayed conscious detection of anomalies. This is

the first study to demonstrate conscious detection of semantic anomalies using questions similar to the so-called Moses Illusion and non-ERP technology. The results of both experiments also revealed that the reading times were equivalent for undetected anomalies and critical nonanomalous control words, a finding that provides no evidence for immediate unconscious detection of anomalies. On the other hand, although the significance of the main effects for the first and second words following both the anomalous words in the detection conditions and critical nonanomalous control words in the control conditions varied across the two experiments, for both experiments the marginally significant interactions with significant effects for first and second words following anomalous words/ critical nonanomalous control words provided some consistent evidence for delayed unconscious detection of anomalies. Specifically, for first words following anomalous words/critical nonanomalous control words, the significant t tests, with effect sizes ranging from small to large, in both experiments revealed slower reading times for first words following anomalous words positioned in the middle of undetected questions than for critical nonanomalous control words positioned in the middle of control questions. Similarly, for second words following anomalous words/critical anomalous words, the significant t tests, with effect sizes ranging from small to large, in both experiments revealed slower reading times for second words following anomalous words positioned later in undetected questions than for critical nonanomalous words positioned later in control questions. Of course, caution must be exercised when interpreting these results because they are based on t tests taken from marginally significant interactions. And certainly, these results might have become significant had the power of the study been increased by using a within-subjects design instead of a between-subjects design. Nevertheless, these findings are suggestive because they indicate that it might be possible to capture unconscious detection of anomalies in an experimental setting. On the whole, the present findings both replicate and extend the recent ERP studies of Bohan,


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Sanford, and colleagues (i.e., Bohan et al., 2012; Sanford et al., 2011). From a replication perspective, the present finding for immediate conscious detection of semantic anomalies replicates Bohan, Sanford, and colleagues’ recent ERP research that shows that easy-to-detect semantic anomalies show N400 effects, whereas nondetected semantic anomalies and controls do not (Bohan et al., 2012; Sanford et al., 2011). The present study also extends this research by showing conscious detection of anomalies using a behaviourally based moving-window technique rather than the biologically based ERP technology. In addition, the present study shows that immediate conscious detection of semantic anomalies generalizes to questions similar to those of the so-called Moses Illusion rather than short paragraphs typically used by Bohan, Sanford, and colleagues (e.g., Bohan et al., 2012; Bohan & Sanford, 2008; Sanford et al., 2011). From a theoretical perspective, this generalization is important because while researchers who use paragraphs containing anomalies advocate a more linguistic-based partial or shallow processing theory (e.g., Barton & Sanford, 1993; Bohan et al., 2012; Bohan & Sanford, 2008; Sanford et al., 2011), researchers who use questions advocate other theories, such as the partial match theory (Reder & Kusbit, 1991), the node structure theory (Shafto & McKay, 2000), or a two-cognitive-mechanism theory (Hannon, 2014; Hannon & Daneman, 2001). Finally, the present study shows that the results generalize across two control conditions: (a) one condition that includes stimuli that are identical to the detection condition but instructions that are different and (b) a second condition that includes instructions that are identical to the detection condition but stimuli that are different. The present somewhat suggestive results for delayed unconscious detection of semantic anomalies are also related to the findings of Bohan et al. (2012) who observed some evidence that undetected anomalies produce a different ERP signature when compared to detected anomalies and controls. Similar to Bohan et al., the present study observed that undetected anomalies were indeed processed differently from

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detected anomalies inasmuch as readers were slower to read detected than undetected anomalies. However, unlike Bohan et al., who observed two completely different ERP signatures for detected versus undetected anomalies (i.e., a N400 effect versus an ERP waveform that was less than positive in the P2 interval), the present study observed different reading times for detected versus undetected anomalies using the same dependent measure. Indeed, whereas Bohan et al., observed that the ERP signature for undetected anomalies was different from both detected anomalies and controls (i.e., lower late positive potential [LPP] amplitude for undetected anomalies versus higher LPP amplitude for both detected anomalies and controls); the present study did not observe such a difference, which suggested that undetected anomalies were processed differently from detected anomalies or controls. Finally, whereas Bohan et al. observed their ERP effect for undetected anomalies starting at about 200 to 500 ms following the onsets of anomalies (i.e., starting at P2), the present study observed the effect for undetected anomalies about 1000–2000 ms after the onsets of the anomalies (i.e., at the first and second words following an anomaly). The present study’s findings were also very dissimilar to the findings of Bohan and Sanford (2008), the major impetus for the present study. Specifically, whereas the present study observed immediate conscious detection and some evidence for unconscious detection of anomalies, Bohan and Sanford (2008) observed only delayed conscious detection. Although the exact reasons for these differences are unclear, there are a number of possibilities, including differences in: (a) number of stimuli, (b) emphasis in task instructions, (c) task operations, and (d) the nature of the stimuli. For example, the present study included considerably more critical stimulus items than did Bohan and Sanford. This increase in stimuli may very well have made the present semantic anomaly task more sensitive to detecting effects, especially immediate effects. Indeed other studies that used more stimuli have observed immediate effects (e.g., Bohan et al., 2012; Sanford et al., 2011).




Furthermore, there were differences in the instructions in the tasks used by Bohan and Sanford (2008) versus the present study. For instance, the instructions in Bohan and Sanford’s task emphasized comprehension of the paragraphs first and detection of anomalies second, whereas the instructions in the present study’s task emphasized detecting anomalies first and question answering second. This difference in emphasis might have led participants in the former study to have more delayed detections of anomalies because detecting anomalies was not their primary focus. In contrast, the emphasis in the latter task might have led participants to have more immediate detections of anomalies because detecting anomalies was their primary focus. Indeed, differing emphasis for detecting anomalies in the instructions may very well explain why Bohan and Sanford failed to detect immediate effects, whereas Bohan et al. (2012), Sanford et al. (2011), and the present study did. One final possible explanation for the differences between the present study and Bohan and Sanford’s (2008) is the differences in stimuli. In the present study, once the anomaly was identified the remaining message in the text still made sense, whereas in Bohan et al.’s study once the anomaly was identified the remaining message in the text became meaningless. Because of this difference, quite possibly detection of anomalies for these two types of stimuli would also result in different patterns of disruptions, with the former type of stimuli resulting in more immediate detection and the latter type of stimuli more delayed detection as the anomalies relations are processed with the overall context. From a theoretical perspective, Bohan and colleagues (e.g., Bohan et al., 2012; Bohan & Sanford, 2008; Sanford et al., 2011) argue that processing of anomalies is often shallow or incomplete inasmuch as (a) retrieval of semantic information for lexical items may be inefficient, and/or (b) integration of the lexical information in the text may be inefficient (Bohan et al., 2012). This theoretical framework is similar to Hannon and Daneman’s (2001) view that frequency of semantic anomalies is influenced by two cognitive mechanisms: (a)

knowledge-based comprehension processes that “either retrieve partial knowledge from long-term memory or accept partial matches between the anomalous word and knowledge retrieved from long-term memory” and (b) integration-based comprehension processes that “accept partial analyses and integration” of the successive words in a text (p. 451). Consider, for instance, the significantly faster reading times for undetected than for detected anomalies. In the context of Hannon and Daneman’s theory, perhaps the quality of the integration processes for undetected anomalies is poorer than the quality of integration processes of detected anomalies. In instances such as this, the contradictory information about an anomaly might be activated; however, because the integration of the information about the anomaly with the information in the preceding and subsequent text is poor or even nonexistent, the contradictory information of the anomaly goes undetected. Another possibility is that perhaps the quality of the lexical access of an undetected anomaly is poorer than that of a detected anomaly. With poorer lexical access, the contradictory information of an anomaly may not be activated, and, consequently, the anomaly goes undetected. In addition, poorer lexical access in conjunction with the reduced awareness hypothesis (Sanford et al., 2011) may very well explain delayed unconscious detection of anomalies. Consider, for instance, that perhaps the contradictory semantic information for an anomaly is available but not at an activation level that is high enough that a reader becomes consciously aware of the inconsistent information. In instances such as this, perhaps enough contradictory information is activated that the integration processes slow down in an attempt to reconcile this contradictory information with subsequent text. However, because this slowdown or adjustment occurred at words following the anomaly and not the anomaly itself, the activation level of the anomaly has decreased even more, and, consequently, the anomaly goes undetected. In other words, even though language processes have slowed down in an attempt to cope with the contradictory information, by the time this


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slow-down occurs the anomalous nature of the anomaly is even less activated, and consequently the anomaly goes undetected. Such a possibility is consistent with previous research that has observed disruptions in eye tracking patterns when readers encounter anomalies, even when readers do not report such anomalies (e.g., Daneman et al., 1995). Of course, it might be argued that Experiment 1’s finding for unconscious detection of anomalies is a consequence of instructional differences in the detection versus gist semantic anomaly tasks rather than unconscious detection of anomalies per se. Indeed, the former task explicitly instructed students to detect anomalies, whereas the latter task instructed students to answer each question. Although this explanation is possible, there are at least three reasons why it is unlikely. First, as evidenced by the analysis in Experiment 1, the reading times for the questions in the detection and gist conditions were equivalent. If the questions in the detection condition had been processed more slowly and deeply, one would have expected significant differences in reading times. Second, the results of Experiment 2, which included the same instructions in the detection and control conditions, closely paralleled those of Experiment 1. If the questions in the detection and gist conditions in Experiment 1 had been processed differently, one would expect substantial differences between the results of Experiments 1 and 2. Finally, the reading times of the words preceding the anomalies in the detection and control conditions in Experiment 2 were equivalent. If these two conditions had been processed differently, one might expect significant differences in reading times for the words preceding the anomalies. Besides the findings for conscious and unconscious detection of semantic anomalies, it is also worth noting that the analyses of the type of word (detected anomalous word, first word, second word) and position (middle, late) for the detected anomalies were consistent across the two experiments. That is, the reading times for detected anomalies were equivalent regardless of position, a finding that suggests that depth of detection for semantic anomalies did not vary as a function of location of the semantic anomaly. This finding

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also suggests that the number of contextual cues that precede the anomalous words did not influence detection of semantic anomalies. On the other hand, first words following detected anomalies were read more slowly when anomalies were in the middle location than when they were in the later position. This finding is likely because the first words following impostor words in the middle position, which are contextual cues, are read more slowly than the first words following impostor words in the later position, which are function words like “and”. For example, in the Indian example in Table 1 the first word following the impostor word in the middle position is “Sioux”, whereas the first word following the impostor word is the later position is “and”. In contrast, second words following detected anomalies were read slower when they were located later in a question than when they were located in the middle. This finding is probably attributed to end of question wrap-up. On another note, it is worth mentioning that one limitation of most semantic illusion tasks is that it is never clear whether the reader said “wrong” because of (a) the anomalous word or (b) another word that the reader thought was incorrect but was actually correct. Although the present study avoids this issue by recording actual reading times of words, future research should consider this concern when designing their semantic illusion tasks. In conclusion, the present research extends the findings of Bohan and Sanford (2008) by providing evidence for immediate conscious detection of semantic anomalies and some weak evidence for delayed unconscious detection. It also extends the findings of Bohan et al. (2012) and Sanford et al. (2011) inasmuch as the present study observed immediate conscious detection of semantic anomalies using behaviourally based measures rather than physiologically based measures and questions similar to those of the so-called Moses Illusion. In the context of language processing, this finding suggests that sometimes we are immediately aware of semantic anomalies, and our language processes will immediately slow down when they encounter such contradictory




information. Finally, the present study extends Bohan et al. and Sanford et al. by providing some evidence across two experimental designs that unconscious detection of semantic anomalies may occur although this detection is possibly delayed. In the context of language processing, this latter finding suggests that although we may not be consciously aware of semantic anomalies, sometimes our language processes may still slow down to make adjustments in order to reconcile the contradictory information of an anomaly with the surrounding text, although this slowdown will probably be delayed rather than immediate. Original manuscript received 15 January 2014 Accepted revision received 6 August 2014

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Wanted: direct comparisons of unconscious and conscious lie detection.

Conscious or unconscious?

Conscious and unconscious memory systems.

Connecting conscious and unconscious processing.

Conscious and unconscious context-specific cognitive control.

Quantum-like model of unconscious-conscious dynamics.

The conscious roots of selfless, unconscious goals.

Brain. Conscious and unconscious mechanisms of cognition, emotions, and language.

Hippocampus is place of interaction between unconscious and conscious memories.

Conscious and unconscious perceptions of self in children of alcoholics.

Unconscious vision and executive control: how unconscious processing and conscious action control interact.

Dissociating conscious and unconscious learning with objective and subjective measures.

Interference between conscious and unconscious facial expression information.

Who Am I: The Conscious and the Unconscious Self.

More power to the unconscious: conscious, but not unconscious, exogenous attention requires location variation.

There Is an 'Unconscious,' but It May Well Be Conscious.

Distinct neural responses to conscious versus unconscious monetary reward cues.

There are conscious and unconscious agendas in the brain and both are important-our will can be conscious as well as unconscious.

Unconscious processes improve lie detection.

KT-1000 arthrometer: conscious and unconscious test results using 15, 20, and 30 pounds of force.

Some evidence for unconscious lie detection.

Binocular rivalry in children with schizophrenia: the conscious and unconscious cognitive processing of interpersonal information.

Distinct cortical codes and temporal dynamics for conscious and unconscious percepts.

Comparing the Neural Correlates of Conscious and Unconscious Conflict Control in a Masked Stroop Priming Task.