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Effects of Video Reversal on Gaze Patterns during Signed Narrative Comprehension

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Title: Effects of Video Reversal on Gaze Patterns during Signed Narrative Comprehension
Language: English
Authors: Bosworth, Rain, Stone, Adam, Hwang, So-One
Source: Journal of Deaf Studies and Deaf Education. Jul 2020 25(3):283-297.
Availability: Oxford University Press. Great Clarendon Street, Oxford, OX2 6DP, UK. Tel: +44-1865-353907; Fax: +44-1865-353485; e-mail: jnls.cust.serv@oxfordjournals.org; Web site: http://jdsde.oxfordjournals.org/
Peer Reviewed: Y
Page Count: 15
Publication Date: 2020
Sponsoring Agency: National Institutes of Health (DHHS)
National Science Foundation (NSF)
Contract Number: R01EY024623
1423500
Document Type: Journal Articles
Reports - Research
Descriptors: Video Technology, Eye Movements, Behavior Patterns, American Sign Language, Language Proficiency, Age Differences, Comprehension, Adults, Language Acquisition, Hearing Impairments, Correlation, Story Telling
DOI: 10.1093/deafed/enaa007
ISSN: 1081-4159
Abstract: Language knowledge, age of acquisition (AoA), and stimulus intelligibility all affect gaze behavior for reading print, but it is unknown how these factors affect "sign-watching" among signers. This study investigated how these factors affect gaze behavior during sign language comprehension in 52 adult signers who acquired American Sign Language (ASL) at different ages. We examined gaze patterns and story comprehension in four subject groups who differ in hearing status and when they learned ASL (i.e. Deaf Early, Deaf Late, Hearing Late, and Hearing Novice). Participants watched signed stories in normal (high intelligibility) and video-reversed (low intelligibility) conditions. This video manipulation was used because it distorts word order and thus disrupts the syntax and semantic content of narratives, while preserving most surface phonological features of individual signs. Video reversal decreased story comprehension accuracy, and this effect was greater for those who learned ASL later in life. Reversal also was associated with more dispersed gaze behavior. Although each subject group had unique gaze patterns, the effect of video reversal on gaze measures was similar across all groups. Among fluent signers, gaze behavior was not correlated with AoA, suggesting that "efficient" sign watching can be quickly learnt even among signers exposed to signed language later in life.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1256387
Database: ERIC
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  Value: <anid>AN0143509755;big01jul.20;2020Jun02.06:11;v2.2.500</anid> <title id="AN0143509755-1">Effects of Video Reversal on Gaze Patterns during Signed Narrative Comprehension </title> <p>Language knowledge, age of acquisition (AoA), and stimulus intelligibility all affect gaze behavior for reading print, but it is unknown how these factors affect "sign-watching" among signers. This study investigated how these factors affect gaze behavior during sign language comprehension in 52 adult signers who acquired American Sign Language (ASL) at different ages. We examined gaze patterns and story comprehension in four subject groups who differ in hearing status and when they learned ASL (i.e. Deaf Early, Deaf Late, Hearing Late, and Hearing Novice). Participants watched signed stories in normal (high intelligibility) and video-reversed (low intelligibility) conditions. This video manipulation was used because it distorts word order and thus disrupts the syntax and semantic content of narratives, while preserving most surface phonological features of individual signs. Video reversal decreased story comprehension accuracy, and this effect was greater for those who learned ASL later in life. Reversal also was associated with more dispersed gaze behavior. Although each subject group had unique gaze patterns, the effect of video reversal on gaze measures was similar across all groups. Among fluent signers, gaze behavior was not correlated with AoA, suggesting that "efficient" sign watching can be quickly learnt even among signers exposed to signed language later in life.</p> <p>Keywords: Sign language processing; eye gaze; eye tracking; lexical recall; narrative comprehension; age of acquisition; deafness</p> <p>Visual language perception—whether that is reading text or conversing with somebody in signed language—involves coordination of visual perceptual mechanisms, control of eye movements, and incremental language processing. Eye movements during reading are thought to reflect moment-to-moment cognitive processes involved in language processing and may be affected by many factors, such as the visual quality of the font, conceptual complexity of words, and the reader's pre-existing language expertise ([<reflink idref="bib46" id="ref1">46</reflink>]). For example, if a reader has poorer vocabulary knowledge, we expect to observe differences in eye gaze behavior during reading when compared to a good reader ([<reflink idref="bib16" id="ref2">16</reflink>]). Whether a person who has difficulty comprehending sign language exhibit different eye gaze behaviors compared to a fluent signer is unknown. The goal of the present paper is to characterize eye movements in deaf and hearing signing adults whose fluency in American Sign Language (ASL) ranges from native to novice. In doing so, we uncover how language expertise, age of acquisition (AoA), and stimulus intelligibility all influence adults' eye gaze behavior during natural sign language perception.</p> <p>Much is known about how sensory, linguistic, and experiential factors influence eye gaze behavior in reading. Variations in purely visual elements such as word length, letter and word spacing, font sizes, and the writing system itself used (e.g. alphabetic, syllabic, logographic) all have been found to influence eye movements (e.g. [<reflink idref="bib22" id="ref3">22</reflink>]; [<reflink idref="bib46" id="ref4">46</reflink>]). When readers are confronted with text of varying intelligibility, such as multisyllabic, misspelled, ambiguous, unexpected, or unfamiliar words, the characteristics of eye movements change, revealing indices of reading effort (e.g. [<reflink idref="bib58" id="ref5">58</reflink>]; and reviewed in [<reflink idref="bib46" id="ref6">46</reflink>]; [<reflink idref="bib9" id="ref7">9</reflink>]). The reader's prior language experience and expertise correlate with certain eye movement behaviors. For example, better reading skill is correlated with more "efficient" eye movements—briefer fixations or stops on words, and longer saccades or "jumps" in between words. Poorer readers show greater number of "regressions" (looking back at prior-viewed words) when they are "stuck" on an unfamiliar or infrequent word (e.g. [<reflink idref="bib16" id="ref8">16</reflink>]; [<reflink idref="bib40" id="ref9">40</reflink>]). Age of acquisition also impacts eye movements for reading: the amount of time fixating on individual words was shorter for words learned earlier in life for both first and second languages ([<reflink idref="bib13" id="ref10">13</reflink>]). If a combination of sensory, linguistic, and experiential factors influences eye gaze movements in reading static text, how do these same factors influence the way in which people "watch" sign language, which is a very different type of language skill, and what is "efficient" sign watching behavior in deaf native signers?</p> <p>Like reading, watching sign language requires controlling eye movement, perceiving visual information, and processing linguistic information. However, dynamic sign is different from static print. Sign language contains several moving elements: the hands as primary language articulators, the mouth as a conveyor of both sign language grammatical information (e.g. aspect, tense) and spoken language borrowings, and the eyes/eyebrows which also convey grammatical features (e.g. conditionality, topicality). Therefore, while sign watching and reading both involve perceiving linguistic information through the eyes and may be subject to similar sensory, linguistic, and experiential influences, they would nonetheless involve markedly different gaze behavior. One example of this is whether core linguistic content is present in the foveal and parafoveal regions or outside of it. Printed text tends to be processed only when it falls within the foveal or parafoveal regions ([<reflink idref="bib47" id="ref11">47</reflink>]). However, during sign watching, the primary articulators (hands) that convey core linguistic information fall almost entirely outside (usually far below) the foveal region ([<reflink idref="bib7" id="ref12">7</reflink>]). Sign watchers tend to fixate on the signer's face and not the signer's hands (c.f. [<reflink idref="bib54" id="ref13">54</reflink>]; [<reflink idref="bib1" id="ref14">1</reflink>]; [<reflink idref="bib11" id="ref15">11</reflink>]; [<reflink idref="bib15" id="ref16">15</reflink>]; [<reflink idref="bib35" id="ref17">35</reflink>]) despite having other competing elements they could fixate on, such as the hands.</p> <p>People who use sign language are characterized by wide variations in their sensory capabilities (hearing, born deaf, late-deafened, or deafblind), when they first acquire sign language (e.g. at birth, during primary school, in college), and their language proficiency. Such differences in language expertise, AoA, and hearing status might be expected to evoke different eye gaze patterns in studies using eye tracking. [<reflink idref="bib1" id="ref18">1</reflink>]) recorded gaze patterns of British Sign Language (BSL) users using eye-tracking while they watched videos of a BSL signer. They found that, while all participants maintained a primary focal point on the face near the mouth, hearing beginner signers frequently shifted their gaze towards the hands, while deaf and hearing fluent signers rarely did. Likewise, [<reflink idref="bib15" id="ref19">15</reflink>] observed that hearing beginner users of American Sign Language (ASL), when compared with native deaf signers, made more gaze shifts away from the face when watching a live ASL signer. They also found deaf native ASL users tended to focus more on the eyes while hearing beginner ASL users focused more on the mouth. [<reflink idref="bib29" id="ref20">29</reflink>]), on the other hand, found different results when using video stimuli of Spanish Sign Language (LSE). They found that native and non-native deaf signers looked at the mouth, while hearing nonsigners showed greater focus on the eyes.</p> <p>The incongruent findings regarding exactly <emph>where</emph> signers look is likely due to language variation in the stimuli, use of live versus videotape stimuli, differences in stimuli size, lower spatial resolution due to older eye-tracking devices, and measurement error.1 It is also difficult to exactly replicate live signing from one participant to the next, even when trying to control for viewing distances and other sensory factors. Also, in live settings, social pressures of maintaining eye contact under conditions of joint attention might override gaze behavior that optimizes processing efficiency and comprehension. Studying gaze in a live setting is important and interesting, but we believe the present study employing a video-based comprehension task truly tap into real-time language processing mechanisms. In short, while there exists general agreement in the literature that deaf and hearing signers of all skill levels choose to focus generally on the face, there remains considerable uncertainty about where on the face that focus is and how language expertise and hearing status influence sign-watching gaze behavior.</p> <p>Complexity and intelligibility of signed input may also have effects on eye gaze behavior. For example, a signer who has difficulty understanding a signed narrative may redirect gaze more frequently to the hands or, conversely, increase their focus on the face to extract more fine-grained information in that region such as English mouthing. [<reflink idref="bib15" id="ref21">15</reflink>] found that beginner signers made more shifts towards to the hands when viewing what they called "complex" narratives that incorporated spatial classifier constructions in signing space, compared to narratives without such elements. [<reflink idref="bib21" id="ref22">21</reflink>]) recorded eye gaze behavior in deaf native ASL users watching signed videos involving either a human signer or a computer-generated avatar signer, which was purported to be more unnatural and difficult to understand. In the avatar condition, signers fixated less on the face and showed greater gaze shifts to the body. Notably, these altered eye behaviors were correlated with participants' subjective judgments of the avatar's naturalness and intelligibility.</p> <p>Together, these studies suggest that eye gaze behavior for viewing sign language may be sensitive to effects of both the sign watcher's language expertise and the subject matter's intelligibility. However, it is still unclear how stimulus intelligibility affects gaze because it is not clear that the manipulations in these studies truly manipulated complexity, intelligibility, or cognitive demand, nor was accuracy actually lower in the purportedly more "complex" or "unnatural" conditions. To date, no study has investigated how gaze behavior changes based on the intelligibility of the signed language stimuli.</p> <p>One way the intelligibility of signed language input has been manipulated in experimental settings in order to study how processing is altered under more challenging conditions is by directly manipulating or distorting the video stimulus. These manipulations include local time-reversals (i.e. reversals of short 80–120 msec segments, which impacts the stimuli at the level of phonemes and syllables, [<reflink idref="bib20" id="ref23">20</reflink>]), vertical video inversion ([<reflink idref="bib10" id="ref24">10</reflink>]; [<reflink idref="bib55" id="ref25">55</reflink>]), playback speed changes ([<reflink idref="bib42" id="ref26">42</reflink>]; [<reflink idref="bib56" id="ref27">56</reflink>]), reduction of full images to point-light displays ([<reflink idref="bib23" id="ref28">23</reflink>]; [<reflink idref="bib43" id="ref29">43</reflink>]; [<reflink idref="bib56" id="ref30">56</reflink>]), or overlaying multiple semi-transparent clips ([<reflink idref="bib38" id="ref31">38</reflink>]; [<reflink idref="bib37" id="ref32">37</reflink>]). Such experimental manipulations have been useful in uncovering underlying cognitive processes governing sign language perception and production by effecting observable changes in behavior or neural activity.</p> <p>Here, we propose the novel use of another video manipulation: reversed video playback of signed stimuli. The viewer watches a video of a signed narrative which is played backwards. Backward speech has been commonly used in cognitive neuroimaging studies of language processing as a non-linguistic control to normal language stimuli that contains identical intensity, pitch, and duration as the spoken stimuli when played normally ([<reflink idref="bib2" id="ref33">2</reflink>]; [<reflink idref="bib12" id="ref34">12</reflink>]; [<reflink idref="bib48" id="ref35">48</reflink>]; [<reflink idref="bib49" id="ref36">49</reflink>]). While backward speech is virtually (or almost virtually) unintelligible, backward signing is not completely unintelligible. For one, some signs have movement patterns that may be relatively unaffected by reversal (DOCTOR, MOTHER) although they may still appear odd or "off" due to prosodic changes. Other signs clearly are affected but still easily retain their lexical label (BICYCLE, GIVE). We know of no sign that is phonetically "impossible" when presented in reverse (unlike speech), even though the tempo and acceleration of movement is clearly disrupted and perceived as "odd" when reversed (PRESIDENT, FALL-IN-LOVE). [<reflink idref="bib20" id="ref37">20</reflink>] showed local time-reversed2 ASL narratives to native and non-native ASL users and found that all participants were still able to comprehend about 50 percent of the manipulated content about. This is in stark contrast to studies of locally time-reserved speech where comprehension drops to near zero ([<reflink idref="bib17" id="ref38">17</reflink>]; [<reflink idref="bib50" id="ref39">50</reflink>]). [<reflink idref="bib60" id="ref40">60</reflink>]) have proposed that modality differences in syllabic structure might help explain why backward signing is relatively less unintelligible than backward speech is. Where reversal of speech involves reversing the <emph>order</emph> of all phonological units in an utterance, reversal of signing changes primarily one major phonological feature—movement—while preserving all other phonological features (e.g. handshape, location, palm orientation). Given that much phonological information is preserved in backwards signing, it is not surprising that reversing sign language does not render single signs wholly unintelligible unlike it does for spoken words.</p> <p>However, video-reversed signed <emph>narratives</emph> are quite difficult to understand, as entire syntactic, sentence, and prosodic elements are extremely disrupted.3[<reflink idref="bib20" id="ref41">20</reflink>] found that native ASL users understood locally time-reversed signed sentences better than non-native ASL users—that is, signers with late AoA. We believe that the use of reversed signing is a simple manipulation that not only changes the intelligibility of the stimuli, but potentially uncovers effects of language experience on sign language comprehension. We predicted that video reversal, besides reducing comprehension accuracy, might also affect eye gaze behavior since viewers may change their visual attention in order to better recover the semantic content. Such an experimental manipulation may elicit natural cognitive processing strategies that signers use in real-world settings where sign language is less intelligible, such as distortion during online video viewing (e.g. reduced frame rate or image size) or watching live sign input from noncanonical viewing positions (e.g. while running or in moving vehicles or for infants lying in cribs or strollers).</p> <p>One appeal of using this manipulation is that the two conditions, Forward and Reversed, are exactly identical in the vocabulary used and the overall visual content. Should any other manipulation be employed to create a less intelligible contrast, such as incorporating more complex vocabulary and grammatical constructions, then the visual and linguistic content would change as well, introducing confounding factors in eye gaze studies. To ensure that the video manipulation in the present study did, in fact, make the stimuli more difficult to understand, we used two measures of story comprehension in forward and reversed conditions: lexical recall accuracy and story comprehension (which we called "gist"; both described in detail in <emph>Methods</emph>).</p> <p>To date, no study has investigated how gaze behavior changes based on intelligibility of the language input and how sensory and language experiences contribute to eye gaze behavior changes. Moreover, there has been no attempt, to the best of our knowledge, to correlate comprehension with specific gaze behaviors in sign-watching, as has been done in reading studies where such relationships are well-documented ([<reflink idref="bib9" id="ref42">9</reflink>]; [<reflink idref="bib46" id="ref43">46</reflink>]). The present study aims to characterize eye gaze behavior of signers watching videos of ASL narratives and further asks whether signers' eye gaze behavior changed under conditions of low intelligibility. While we expected the great majority of eye fixations to be on the face area, we hypothesized that for reversed video stories, viewers would fixate on different locations or their gaze would be distributed over a larger viewing space. We examined the data for any correlations between gaze behavior and story comprehension, predicting that gaze behavior may depend on quality of language comprehension and gaze behavior may change with worse story comprehension (e.g. possibly becoming less focused or more spatially scattered with worse story comprehension).</p> <p>We also asked whether eye gaze behavior differed among four signer groups that varied in AoA and hearing status: deaf adults who acquired ASL at birth or during early childhood (Deaf Early), deaf adults who learned ASL later in late childhood (Deaf Late), hearing adults who learned ASL later in early adulthood (Hearing Late), and hearing adult ASL students who recently took ASL classes in early adulthood (Hearing Novice). We hypothesized that we would observe group differences in their eye gaze behavior (i.e. more or fewer fixations on the face), as well as group differences in how these behaviors <emph>change</emph> if the sign language input was more difficult to understand. For example, we predicted Deaf Late signers, who may depend on lip-reading more than the other groups do, might increase their focus on the mouth during reversed videos in order to better extract English mouthing information. Conversely, Hearing Novice signers, because they are still learning sign language, might fixate towards regions where the hands are more likely to be. We do expect that all signers will be able to recover, to some extent, the semantic content of the story, but that this recovery will be contingent on language expertise and AoA ([<reflink idref="bib20" id="ref44">20</reflink>]).</p> <p>A better characterization of "sign watching" behavior in these four groups who differ in Hearing Status and AoA offers novel insights into how age of acquisition, language experience, and stimulus intelligibility influence human visual pathways for language comprehension. This knowledge will be enormously useful for identifying optimal gaze behavior that foster best comprehension and for promoting perceptual behaviors in sign language learners (both adults and children) that support better comprehension.</p> <hd id="AN0143509755-2">Methods</hd> <p></p> <hd id="AN0143509755-3">Participants</hd> <p>A total of 54 adult signers between 18 to 57 years of age were recruited for this study. Two participants were excluded due to experimenter error and poor gaze data acquisition. Of the remaining 52 participants, 29 were deaf signers who acquired or learned ASL between infancy and 19 years old, and 23 were hearing signers who learned ASL between 12 and 22 years old (see Table 1). Deaf signers were divided based on their age of ASL acquisition into Deaf Early (0 to 4 years)4 and Deaf Late (>4 years) groups. The cut-off age was selected based on [<reflink idref="bib30" id="ref45">30</reflink>]) who used 4 years of age to divide early/native signers from those who learned sign language later in childhood or adolescence. All deaf signers were severely to profoundly deaf in both ears (hearing loss > 80 dB in the better ear), and none used cochlear implants or hearing aids as beyond teen years. They all were born deaf or became deaf before 2 years old. All reported using ASL as their primary language and communication mode on a daily basis.</p> <p>Table 1. Demographics of all 52 subjects included in analysis. N's, Means, Standard Deviations, and Ranges are presented. Self-rating of proficiency scores (that range from 0 to 5) are based on a survey from [<reflink idref="bib28" id="ref46">28</reflink>])</p> <p> <ephtml> <table><thead><tr><th>Group. </th><th>N. </th><th>Age (years). </th><th>Age of ASL Acquisition. </th><th>Years Signing. </th><th>Self-Rating. </th></tr></thead><tbody><tr><td>Deaf Early </td><td>15 </td><td>33.6 ± 9.2 (22–57) </td><td>0.7 ± 1.1 (0–3) </td><td>32.8 ± 9.3 (21–57) </td><td>5.0 ± 0 </td></tr><tr><td>Deaf Late </td><td>14 </td><td>36.4 ± 5.6 (26–44) </td><td>11.0 ± 4.6 (4–19) </td><td>25.2 ± 5.6 (13–34) </td><td>5.0 ± 0 </td></tr><tr><td>Hearing Late </td><td>12 </td><td>28.9 ± 6.2 (18–39) </td><td>17.3 ± 3.4 (12–22) </td><td>11.8 ± 4.9 (5–20) </td><td>4.6 ±.5 (4–5) </td></tr><tr><td>Hearing Novice </td><td>11 </td><td>20.3 ± 1.3 (18–22) </td><td>17.6 ± 1.8 (15–21) </td><td>2.4 ± 1.0 (1–4) </td><td>3.0 ±.7 (2–4) </td></tr></tbody></table> </ephtml> </p> <p>Graph: Figure 1. class="chapter-para">Calibration procedures used. First, the 9-point calibration routine provided by Tobii Studios, shown in (a), was used to estimate instrument error (see text). At the onset of each test session, participants provided gaze data for each "spinning circle" in a five-point calibration. If calibration was of sufficient quality, testing was initiated. Then, as shown in (b), a three-point calibration routine was recorded within the test session both before and after testing. These were used as a second-stage off-line calibration check, as shown in (c). Only data sets that indicated the gaze hit the target, as shown here, were included.</p> <p>Hearing signers were also divided into two groups. Hearing Late signers were those who learned ASL primarily in high school or college, continued to use ASL frequently for more than 4 years. Hearing Novice signers had recently taken ASL courses (levels 3–4) within the past 2 years and were comparatively new to deaf communities. Without stipulating how much ASL usage was required to participate in the study, we selected Novice signers who had answered "yes" to the question, "Do you use ASL outside the classroom, or if your classroom education was completed, do you still use ASL now?"</p> <p>All participants were recruited from the San Diego area and testing was performed at the UCSD. All participants reported normal or corrected-to-normal vision. They all provided consent in the laboratory and received a small payment for their participation in the 30-minute study, which protocol was approved by the UCSD Institutional Review Board.</p> <hd id="AN0143509755-4">Apparatus</hd> <p>Video stimuli were presented on a HP p1230 20″ monitor (1,440 x 1,080 pixels; 75 Hz) using Tobii Studio version 3.4.2 on a Dell Precision T5500 Workstation computer. A Tobii X120 eye tracker recorded near-infrared reflectance of both eyes at 120 Hz. The eye tracker was positioned under the stimulus monitor, placed in front of the participant.</p> <hd id="AN0143509755-5">Calibration</hd> <p>The calibration instrument error was estimated based on running Tobii's 9-point adult calibration routine (see Figure 1a) which involves an observer gazing at the center of small red dots located in the center and periphery of the screen. Error was measured by calculating the offset between the participant's recorded gaze points and the actual locations of the red dots. This procedure was repeated every two weeks during the duration of the experiment to ensure stability of measurement. The average measured error was.57° and the maximal error recorded was 1.15°, which we used in our inclusion criteria for the main study.</p> <p>For each participant, a five-point calibration procedure was used with small spinning circles 2.3 cm wide (and at a viewing distance of 60 cm, this is 2.2° visual angle wide) presented in the corners and the center of the screen. If an adult participant showed error > 1.15° for any target during calibration, then we recalibrated until error for all targets was reduced below this value before starting the experiment.</p> <p>Embedded in each participant's test session was a pre-test and post-test three-point "calibration check" using the same spinning circles (after [<reflink idref="bib57" id="ref47">57</reflink>]; see Figure 1b). This allowed us to preserve per-participant calibration data along with each test recording. Data was included for analysis only if gaze plots showed that eye gaze had, in fact, hit each target in the three-point calibration check (see Figure 1c). Additional assurance of data quality is provided by the fact that the "area of interest" (AOI) boxes used for in our analyses were larger than this margin of error.</p> <hd id="AN0143509755-6">Materials</hd> <p></p> <hd id="AN0143509755-7">Stimuli</hd> <p>Stimuli consisted of four videos of an adult deaf female native signer narrating classic fairy tale stories in ASL (see <emph>Supplementary Material 1</emph>). The stories were produced with natural prosody and intonation. The model was asked to narrate, without a script, the following stories: Goldilocks and the Three Bears, Cinderella, King Midas and the Golden Touch, and Red Riding Hood and the Bad Wolf. These stories were chosen because they are easily understood even for novice ASL students and children. No attempt was made to restrain her word or grammar choice. The model was allowed to use natural mouthing, and she used both ASL nonmanual mouthing and English mouthing. All stories started and ended with the model's hands placed together on her lower torso (i.e., "resting" position) and in view. The video image of the signer's body spanned 15.33 degrees of visual angle in height. In a naturalistic setting, this stimulus size roughly corresponds to viewing a person of average height viewed from approximately 2 meters away.</p> <p>All participants watched all four stories, each in turn, with 2 stories presented in Forward and 2 in Reversed. As each participant was scheduled, they were alternately assigned to Group 1 or Group 2 to counterbalance the video-reversal conditions and stimuli order (see Table 2), and this was done keeping roughly even numbers of participants in each Group 1 and 2 for each Subject Group (Deaf Early, Deaf Late, Hearing Late, Hearing Novice).</p> <p>Table 2. Stories, the orders in which they were presented to subjects based on their pseudorandom assignment to Group 1 or Group, and the duration of each story (in seconds)</p> <p> <ephtml> <table><thead><tr><th>Group 1. </th><th>Group 2. </th></tr></thead><tbody><tr><td>Goldilocks, Forward (21 s) </td><td>Red Riding Hood, Forward (18 s) </td></tr><tr><td>Cinderella, Reversed (22 s) </td><td>King Midas, Reversed (37 s) </td></tr><tr><td>King Midas, Forward (37 s) </td><td>Cinderella, Forward (22 s) </td></tr><tr><td>Red Riding Hood, Reversed (18 s) </td><td>Goldilocks, Reversed (21 s) </td></tr></tbody></table> </ephtml> </p> <hd id="AN0143509755-8">Gist Task</hd> <p>The first way in which we measured participants' comprehension of the story was with our "gist" task. Immediately after watching a story (in either Forward or Reverse), the participant was asked, "What was the story about?" in ASL by the experimenter. In order to be marked as "correct" (score = 1), the participant had to name <emph>either</emph> the protagonist or major plotline of the story. In other words, the participant had to be able to get the "gist" of the story. For example, in the case of <emph>Red Riding Hood</emph>, correct answers included "This is about Red Riding Hood," (which named the protagonist) or "There was a girl who went to see her grandmother and there was a wolf." Both answers were considered correct. Answers were very brief, usually one sentence, taking no more than a few seconds. Participants were not given feedback on accuracy. For the purpose of the present study, we did not analyze detail of answers, but simply scored participants as being correct or incorrect.</p> <hd id="AN0143509755-9">Lexical Recall Task</hd> <p>If participants comprehended the story well, they should therefore be more accurate at recalling signs appearing in the story they had just watched. To measure participants' capacity to recognize and recall specific signs from the stories they had just seen, we created a word list for each story. Each list consisted of 20 ASL signed items, wherein 10 items appeared in the story ("targets," and the correct answer to those should be "yes") and 10 did not ("foils," and the correct answer to those should be "no"). Within each word list, half the foil words and half the target words were semantically related to the story and half were not (or at least semantically "neutral"). This was so that participants could not guess whether a word was more likely to be in the story based on it being related to the narrative's plot or to other words seen in the narrative. Also, if they did only guess and say "yes" for all semantically-related words, then accuracy would be near chance, i.e. 50 percent).</p> <p>To illustrate, here are example words used in the lexical recall task for Red Riding Hood.</p> <p></p> <ulist> <item> Semantically-related targets: SICK, FOOD, GRANDMOTHER. These are words that are strongly identified with this story and did appear in the story.</item> <p></p> <item> Semantically-related foils: BOWL, CURIOUS, UGLY. These are words that are strongly identified with this story but did not appear in the story. For example, Red Riding Hood mentions filling a basket of food to bring to her grandmother, hence, BOWL is semantically related.</item> <p></p> <item> Semantically-neutral targets: ARRIVE, LOOK-AT, HAVE. These are words that are not particular to this story but did appear in the story.</item> <p></p> <item> Semantically-neutral foils: DISAGREE, BREAD, BLOOD. These are words that are not particular to this story and did not appear in the story.</item> </ulist> <p>Sign frequencies for each item was retrieved from the ASL-LEX database at <ulink href="http://www.asl-lex.org">www.asl-lex.org</ulink> ([<reflink idref="bib8" id="ref48">8</reflink>]), and t-tests showed no significant difference in sign frequencies between target and foil items. The task was administered immediately after the conclusion of each story, just after the Gist task. The experimenter produced each sign item individually, while facing the participant, and for each item, the participant was asked to indicate whether it appeared in the story or not. No feedback was provided. Accuracy is reported here as percent correct items out of 20 total items.</p> <hd id="AN0143509755-10">Procedure</hd> <p>Prior to testing, a paper-based self-rated sign language proficiency questionnaire was administered, taken from [<reflink idref="bib28" id="ref49">28</reflink>]). Individuals give themselves scores between 0 (not fluent) to 5 (highly fluent) for various statements about their own sign language fluency (such as "I know some signs or short phrases, and I can respond to basic questions signed to me but I very often have to ask for signs to be repeated or ask that something be signed in a different way" (<reflink idref="bib1" id="ref50">1</reflink>, low fluency) to "I am able to have a very comfortable, in-depth conversation about social and school topics" (<reflink idref="bib5" id="ref51">5</reflink>, high fluency). Mean self-ratings are presented in Table 1.</p> <p>Participants sat in a low-lit room and viewed the stimulus at a distance of 60 cm. They were told that we were measuring the intelligibility of the ASL stories and were not told about the reversal manipulation. They were told that a remote eye tracker was positioned beneath the monitor, but that they should simply watch the videos naturally. Before seeing the first reversed story, they were told, "This story will look odd, but your task is still the same, to try to understand the story and I will ask you if you remember some words from the story."</p> <p>The experiment began with eye tracker calibration (~10s) which was followed by a three-point calibration check (~5 s) performed in order to double-check and record calibration accuracy. Subjects were instructed to foveate on each calibration target (see Figure 1b). The duration of each calibration target was controlled by the experimenter.</p> <p>If calibration was ideal, the first story video was then presented. After the story video, the experimenter, using ASL, administered the Gist and Lexical Recall tasks in ASL only. This procedure was repeated for the remaining 3 videos. Immediately after the last video was shown, but before the Gist or Lexical Recall tasks were administered for that story, the three-point calibration check was repeated to check for signal drift. The initial and final calibration-checks were later visually superimposed with gaze plots to see if there were any differences. Visual inspection showed no discernable drifts or significant changes in calibration for any participant.</p> <hd id="AN0143509755-11">Data Analysis</hd> <p> <emph>Behavioral Data.</emph> The dependent measures were each participant's percent accuracy scores on the Gist and Lexical Recall tasks. Gist data were analyzed with nonparametric statistics on proportion of subjects obtaining zero, one, or two stories correct. Mean Lexical Recall accuracy data from Group 1 and Group 2 were collapsed together, to counterbalance the stimuli for each within-subject condition and to eliminate story order effects. Accuracy for the two stories for each Video Direction condition were also averaged together, which helps eliminate any possible idiosyncratic effects of each story. 2x4 mixed ANOVAs were performed with within-subjects factor Video Direction (Forward, Reversed) and between-subjects factor Subject Group (Deaf Early, Deaf Late, Hearing Late, Hearing Novice) for Lexical Recall accuracy. If an interaction between Video Direction and Subject Group was found to be significant, we explored the interaction by running one-way ANOVAs (between-subjects factor Subject Group) separately for the Forward and Reversed conditions. Because the Forward condition was intended to be a baseline condition that was very easy, it was predicted that no or few group differences might be found for this condition, and that greater group differences would exist in the more difficult, Reversed condition.</p> <p>When a significant main effect of subject group was observed in ANOVA results, we explored what drove these group differences using planned comparisons with least-significant differences (LSD) contrasts for the following groups:</p> <p></p> <ulist> <item> Deaf Early versus Deaf Late, addressing effects of AoA of ASL in deaf people,</item> <p></p> <item> Deaf Late versus Hearing Late, addressing effects of hearing status while matching for late AoA during late childhood/adolescence,</item> <p></p> <item> Hearing Late versus Hearing Novice, addressing effects of signing experience (years) while matching for hearing status and AoA.</item> </ulist> <p>These comparisons were preferable to running a comprehensive ANCOVA with AoA, Years Signing, and Hearing Status due to high collinearity among the three factors. For example, AoA and Years Signing are highly correlated, and would always be the case unless age-at-testing was tightly controlled (which was not the case in the current study). Likewise, AoA and Hearing Status are also confounded; the AoAs among Hearing and Deaf groups do not overlap very much, so we cannot entirely separate the effects of those two factors. It was not the goal of the present study to precisely tease apart these effects, but rather to see if gaze and comprehension were sensitive to differences in language experience. Data was processed and summarized in R (R [<reflink idref="bib45" id="ref52">45</reflink>]) with tidyverse code ([<reflink idref="bib59" id="ref53">59</reflink>]). ANOVAs were run using the afex package ([<reflink idref="bib53" id="ref54">53</reflink>]), and planned comparisons using the lsmeans package ([<reflink idref="bib24" id="ref55">24</reflink>]) with uncorrected p-values.</p> <hd id="AN0143509755-12">Eye Tracking Data</hd> <p>Raw eye gaze data in x,y form, indicating horizontal (x) and vertical (y) position in 2-D space, were obtained for each eye, and averaged across both eyes. (The z-position was also recorded but not used in the present study.) The raw data were first smoothed with a standard moving average noise reduction algorithm (window size = 3 samples) which acts as a low-pass filter that reduces the influence of microsaccades, blinks, and large data gaps ([<reflink idref="bib61" id="ref56">61</reflink>]; [<reflink idref="bib51" id="ref57">51</reflink>]). Then, the Tobii Studio I-VT filter was applied which removed saccades and eye movements classified as greater than 30 degrees per second (see [<reflink idref="bib41" id="ref58">41</reflink>]). The purpose of this was to focus analyses on fixations, i.e. where subjects foveate, which represents volitional and attentional behavior ([<reflink idref="bib19" id="ref59">19</reflink>]). Note, however, saccades and eye movements slower than 30 degrees per second would be included in gaze analyses.</p> <p>Areas of interest (AOIs) were drawn using Tobii Studio Pro software. Ten AOIs were drawn, corresponding to the forehead, eyes, mouth, chin, upper chest, middle chest, lower chest, belly, left side, and right side (see insert in Figure 3). The AOI was dynamically re-positioned every 5 frames to align with the signer's body position throughout the story. This ensured that each AOI consistently referred to the same part of the body. For example, the AOI box that encompasses the mouth always covered that part of the signer's body. Total looking duration for each AOI was calculated for each participant and summed for each story.</p> <p>Next, we converted looking durations for each AOI to percentages of total looking time recorded for each story. In other words, for every participant, the looking percentages for all AOIs always summed to 100 percent for each story. This allowed for meaningful comparisons of time spent looking at AOIs regardless of differences in story length or individual variation (e.g. missing data due to blinking, saccades, looking away, rare occlusions from moving hands across the face, moving briefly out of eye tracker range). There were no significant group differences in amounts of missing data, which averaged to only 1.2 percent of total possible eye gaze data across all participants.5</p> <p>Most gaze points fell along a vertical axis running from the face to the lower chest (discussed below in <emph>Results</emph>). The eyes, mouth, and chin AOIs accounted for about 95 percent of total eye gaze data, with 2.0 percent (±4.3 percent) falling outside this region, mostly in the neck to belly AOIs. We generated heat maps (Figure 4) comparing concentration of gaze points in the central axis AOIs (excluding left and right AOIs) across video direction and subject groups.</p> <p>Based on visual inspection of the heat maps, we calculated a Face-Chest Ratio for each participant and each story by first taking the sum of looking percentages in the forehead, eyes, and mouth AOIs (the "face") and the sum of looking percentages in the neck, upper chest, midchest, and lower chest AOIs (the "chest"). A Face-Chest Ratio (FCR) was calculated, (Face—Chest)/(Face + Chest), modeled on similar formulas comparing two regions of interest ([<reflink idref="bib44" id="ref60">44</reflink>]; [<reflink idref="bib52" id="ref61">52</reflink>]). A positive FCR value indicates greater looking at the face region, while a negative FCR value indicates greater looking at the neck and chest region. In this way, we were able to test predictions about whether groups would differ in how they allocated gaze behavior to signing space (i.e. chest region) compared to the face.</p> <p>FCR was analyzed with a mixed 2x4 ANOVA with within-subjects factor Video Direction and between-subjects factor Subject Group, with identical planned group comparisons for possible interactions as described above. Last, we calculated correlations among behavioral measures, gaze measures, AoA, and years signing, which, for the present study, were purely exploratory.</p> <hd id="AN0143509755-13">Results</hd> <p></p> <hd id="AN0143509755-14">Behavioral Data</hd> <p></p> <hd id="AN0143509755-15">Gist Accuracy</hd> <p>The proportion of subjects who obtained zero, one, or both of the stories correct is shown in Table 3. Across all subject groups, 90 percent of the participants obtained 1 or 2 stories correct for Forward, compared to 67 percent for Reversed, indicating an effect of intelligibility on the Gist measure. A nonparametric Kruskal-Wallis H test indicated there was a statistically significant difference amongst the four subgroups for Forward (H(<reflink idref="bib3" id="ref62">3</reflink>) = 25.46; p =.0001) and for Reversed (H(<reflink idref="bib3" id="ref63">3</reflink>) = 11.37; p =.01) in number of stories obtained as correct (0, 1, or 2). Mean rank scores for each of the four groups (Deaf Early, Deaf Late, Hearing Late, Hearing Novice) were 29, 30, 30, and 14 for Forward and 36, 25, 23, and 19 for Reversed. As expected, Deaf Early performed the best and Hearing Novice performed the worst, respectively, with Deaf Late and Hearing Late being intermediate. These results suggest that the gist comprehension measure is sensitive to both intelligibility and AoA effects.</p> <p>Table 3. Proportion of subjects who obtained 0, 1, or 2 stories correct on the Gist task</p> <p> <ephtml> <table><thead><tr><th><italic>Video Direction</italic>. </th><th><italic>Subject Group</italic>. </th><th>No Stories Correct. </th><th>One Story Correct. </th><th>Both Stories Correct. </th></tr></thead><tbody><tr><td rowspan="4">Forward (High Intelligibility) </td><td>Deaf Early </td><td>0% </td><td>7% </td><td>93% </td></tr><tr><td>Deaf Late </td><td>0% </td><td>0% </td><td>100% </td></tr><tr><td>Hearing Late </td><td>0% </td><td>0% </td><td>100% </td></tr><tr><td>Hearing Novice </td><td>45% </td><td>18% </td><td>36% </td></tr><tr><td /><td><italic>Percentage of Total (N = 52)</italic></td><td><italic>(5/52) 10%</italic></td><td><italic>(3/52) 6%</italic></td><td><italic>(55/52) 85%</italic></td></tr><tr><td rowspan="4">Reversed (Low Intelligibility) </td><td>Deaf Early </td><td>7% </td><td>53% </td><td>40% </td></tr><tr><td>Deaf Late </td><td>43% </td><td>36% </td><td>21% </td></tr><tr><td>Hearing Late </td><td>33% </td><td>67% </td><td>0% </td></tr><tr><td>Hearing Novice </td><td>55% </td><td>45% </td><td>0% </td></tr><tr><td /><td><italic>Percentage of Total (N = 52)</italic></td><td><italic>(17/52) 33%</italic></td><td><italic>(26/52) 50%</italic></td><td><italic>(9/52) 17%</italic></td></tr></tbody></table> </ephtml> </p> <p>Averages for percent accuracy on the Gist task presented in Table 4 mirrors the above proportion data. Across all participants, average accuracy for Gist identification was 86 percent for Forward and 41 percent for Reversed. The best overall Gist performance by those with earlier AoA (Deaf Early, average 82 percent accuracy) and progressively worsening performance by those with later AoA (Deaf Late, Hearing Late, and Hearing Novice, in that order, with average accuracy, 70 percent, 67 percent, and 34 percent, respectively).</p> <p>Table 4. Average Accuracy and SD for the story comprehension tasks, Gist and Lexical Recall</p> <p> <ephtml> <table><thead><tr><th>. </th><th colspan="3">Gist. </th><th colspan="3">Lexical Recall. </th></tr><tr><th>Group. </th><th>Forward. </th><th>Reversed. </th><th><italic>Average</italic>. </th><th>Forward. </th><th>Reversed. </th><th><italic>Average</italic>. </th></tr></thead><tbody><tr><td>Deaf Early </td><td>97 ± 18% </td><td>67 ± 48% </td><td><italic>82%</italic></td><td>85 ± 7% </td><td>76 ± 12% </td><td><italic>81%</italic></td></tr><tr><td>Deaf Late </td><td>100 ± 0% </td><td>39 ± 50% </td><td><italic>70%</italic></td><td>85 ± 8% </td><td>69 ± 12% </td><td><italic>77%</italic></td></tr><tr><td>Hearing Late </td><td>100 ± 0% </td><td>33 ± 48% </td><td><italic>67%</italic></td><td>87 ± 9% </td><td>69 ± 14% </td><td><italic>78%</italic></td></tr><tr><td>Hearing Novice </td><td>45 ± 51% </td><td>23 ± 43% </td><td><italic>34%</italic></td><td>78 ± 13% </td><td>64 ± 13% </td><td><italic>71%</italic></td></tr></tbody></table> </ephtml> </p> <hd id="AN0143509755-16">Lexical Recall Accuracy</hd> <p>There was a significant main effect of Video Direction (F(<reflink idref="bib1" id="ref64">1</reflink>,<reflink idref="bib48" id="ref65">48</reflink>) = 106.25, p <.0001; η<sups>2</sups> =.43) reflecting that Lexical Recall accuracy was significantly higher for Forward than Reversed (84 percent versus 70 percent, respectively). Across all participants, the average reduction in accuracy due to video reversal was 14.2 percent (SD = 1.3 percent). Remarkably, accuracy for Reversed videos was still significantly above chance (one-sample t test, t(<reflink idref="bib51" id="ref66">51</reflink>) = 14.08, p <.0001; Cohen's d = 1.38), indicating that participants still understood some, but not all, words, in Reversed videos. This finding suggests that the reversed videos were not wholly incomprehensible.</p> <p>There was a significant main effect of Subject Group (F(<reflink idref="bib1" id="ref67">1</reflink>,<reflink idref="bib48" id="ref68">48</reflink>) = 4.05, p =.01; η<sups>2</sups> =.14) on Lexical Recall accuracy. Averages are presented in Table 4 and displayed in Figure 2b. Counter to our predictions, there was no significant Video Direction x Subject Group interaction (F(<reflink idref="bib3" id="ref69">3</reflink>,<reflink idref="bib48" id="ref70">48</reflink>) = 1.96, p =.13; η<sups>2</sups> =.04). Consequently, planned comparisons among subject groups were conducted collapsing across Video Direction. There was no significant difference in overall Lexical Recall accuracy for Deaf Early versus Deaf Late (averages: 81 percent versus 77 percent), nor between Deaf Late versus Hearing Late (77 percent versus 78 percent; all t's < 1.37). The Hearing Novice group performed worse than all other groups, and significantly worse than Hearing Late (t(<reflink idref="bib48" id="ref71">48</reflink>) = 2.23, p =.03; Cohen's d =.64).</p> <p>Graph: Figure 2. class="chapter-para">Story Comprehension Measures. Each participant group's average A) Gist and B) Lexical Recall accuracy scores. Dotted line in 2B indicates chance (50%). Overall, reversal drastically decreased participants' ability to understand ASL narratives. Error bars reflect SEM.</p> <hd id="AN0143509755-17">Correlations</hd> <p>Pearson's correlation coefficients are presented in Table 5. We performed these analyses across all participants, regardless of hearing status. This allowed us to consider the full range of AoA and Years Signing. Had we calculated correlations for Deaf and Hearing groups separately, AoA and Years Signing would be highly confounded, and the ranges restricted.</p> <p>Table 5. Correlations for both behavioral tasks (Pearson r values) for all subjects</p> <p> <ephtml> <table><thead><tr><th>. </th><th>AoA of ASL. </th><th>Years Signing. </th><th>Gist (Forward). </th><th>Gist (Reversed). </th><th>Lexical Recall (Forward). </th></tr></thead><tbody><tr><td>Years Signing </td><td>−.79<sup>***</sup></td><td /><td /><td /><td /></tr><tr><td>Gist (Forward) </td><td char=".">−0.32<sup>*</sup></td><td char=".">0.50<sup>***</sup></td><td /><td /><td /></tr><tr><td>Gist (Reversed) </td><td char=".">−0.39<sup>**</sup></td><td char=".">0.34<sup>*</sup></td><td char=".">0.27 </td><td /><td /></tr><tr><td>Lexical Recall (Forward) </td><td char=".">−0.08 </td><td char=".">0.30<sup>*</sup></td><td char=".">0.49<sup>***</sup></td><td char=".">0.22 </td><td /></tr><tr><td>Lexical Recall (Reversed) </td><td char=".">−0.34<sup>*</sup></td><td char=".">0.32<sup>*</sup></td><td char=".">0.15 </td><td char=".">0.49<sup>***</sup></td><td char=".">0.38<sup>**</sup></td></tr></tbody></table> </ephtml> </p> <p>1 * = p <.05; ** = p <.01; *** = p <.001</p> <p>For the Gist task, AoA was significantly correlated with accuracy for <emph>both</emph> the Forward (r = −.32, p =.02) and Reversed (r = −.39, p =.004) conditions. That suggests that those who learn ASL earlier are better at comprehending signed narratives. For Lexical Recall, AoA was <emph>not</emph> correlated with accuracy for Forward (r = −.08, p =.57) condition, but it was for the Reversed (r = −.34, p =.01) condition. That suggests that those who learn ASL earlier are better at deciphering and recalling words in low-intelligible conditions. There were also strong positive correlations between Years Signing and both behavioral measures (Gist and Lexical Recall, in both Forward and Reversed conditions, shown in Table 5).</p> <p>Gist and Lexical Recall accuracy were significantly correlated with each other in both video conditions (both r's were identical, r =.49, p =.002). Accuracy was also marginally correlated between Forward and Reversed video conditions on the Gist task (r =.27, p =.05) and significantly so on the Lexical Recall task (r =.38, p =.005), suggesting that video reversal impacted the two tasks to a similar degree.</p> <hd id="AN0143509755-18">Eye Gaze Data</hd> <p>Figure 3 shows averages where participants' gaze points fell in both the Forward and Reversed conditions. To check for potential visual field asymmetries in looking behavior across groups, we ran a Subject Group x AOI (Left Side versus Right Side) ANOVA. This showed neither significant main effects (Subject Group: F(<reflink idref="bib3" id="ref72">3</reflink>,<reflink idref="bib47" id="ref73">47</reflink>) = 2.54, p =.07; η<sups>2</sups> =.09; Left/Right AOI: F(<reflink idref="bib1" id="ref74">1</reflink>,<reflink idref="bib47" id="ref75">47</reflink>) = 1.89, p =.18; η<sups>2</sups> =.01) nor an interaction (F(<reflink idref="bib3" id="ref76">3</reflink>, 47) =.84, p =.48; η<sups>2</sups> =.02). This is likely because all participants looked very infrequently at the left and right AOIs, as can be seen in Figure 3.</p> <p>Graph: Figure 3. class="chapter-para">Eye gaze data for each AOI. The average percent looking time is shown for each Area of Interest (AOI), across all participant groups. All values across sum to 100% for each participant. The AOIs are illustrated in the insert image of the signer. Underlined (in red) AOIs along the x-axis indicate those that were analyzed in the ANOVAs: eye, mouth, and neck. Error bars reflect SEM.</p> <p>Using heat maps, we visualized looking patterns for each group based on video direction in Figure 4<emph>,</emph> where higher looking percentages are reflected with darker shading. Attention appeared to be more dispersed when the video was reversed. Note that, for all groups, the gaze concentration on the mouth <emph>decreased</emph> for reversed, compared to forward, possibly because video reversal causes a gaze shift to the neck and signing space containing the moving articulators (arms and hands). This effect is further explored in the <emph>Face-Chest Ratio</emph> section below.</p> <p>Graph: Figure 4. class="chapter-para">Heat Maps showing concentration of gaze points for central AOIs for each participant group. The highest concentration is reflected with the darkest regions, and few or no gaze points are shown in light regions. Empty cells indicate that looking time was less than 1%. Only the central face AOIs (eyes, mouth, and neck) were analyzed due to low looking percentages in all other AOIs.</p> <p>We observed important differences among subject groups in AOI concentrations in the heat maps (Figure 4). First, Deaf Early signers concentrated their gaze solely on the three central AOIs (eyes, mouth, and neck), and almost nowhere else. Deaf Late signers behaved similarly, but they showed higher concentration on the <emph>mouth</emph>, perhaps due to greater experience with or habit for lip-reading, given that they did not learn sign language until later in life. Compared to Deaf signers, Hearing signers' gaze was more vertically dispersed. Generally, while the Deaf groups' gaze spanned 4 equally-sized AOI boxes, the hearing groups spanned 5 or 6 AOI boxes. Hearing Late signers' gaze was distributed <emph>upwards</emph> towards the eyes and forehead, while Hearing Novice signers distributed more of their gaze <emph>downwards</emph> through the neck, upper chest, and mid-chest AOIs. Upon inspection of gaze plot videos (generated by Tobii Studio Pro, which plots eye gaze data against the video stimuli <emph>(see</emph><ulink href="http://bit.ly/gazeplotvideo">http://bit.ly/gazeplotvideo</ulink><emph>for a video example),</emph> we believe the Hearing Novice signers' heat map pattern is due to vertical (up-and-down) scanning behavior, with their gaze, traveling between the face and the hands and frequently passing through the AOIs in between.</p> <hd id="AN0143509755-19">Face-Chest Ratios</hd> <p>Because it was hypothesized that group differences might emerge based on whether participants focus more on the face versus more on the signing arms/hands, and because we wanted to examine the <emph>relative</emph> looking preferences for the face and chest (where the hands are frequently located), we computed Face-Chest Ratios (FCR) for each participant and story.6 The face numerator included AOIs between the forehead and chin, while the chest denominator included neck, upper, mid, and lower chest AOIs. Mean FCR values are charted in Figure 5. The ANOVA revealed no main effect of Subject Group (F(<reflink idref="bib3" id="ref77">3</reflink>,<reflink idref="bib47" id="ref78">47</reflink>) = 1.09, p =.36; η<sups>2</sups> =.06). However, there was a significant main effect of Video Direction (F(<reflink idref="bib1" id="ref79">1</reflink>,<reflink idref="bib47" id="ref80">47</reflink>) = 17.7; p =.0001; η<sups>2</sups> =.04) and a marginal two-way Subject Group x Video Direction interaction (F(<reflink idref="bib3" id="ref81">3</reflink>,<reflink idref="bib47" id="ref82">47</reflink>) = 2.36; p =.08; η<sups>2</sups> =.015). Reversed videos were associated with less positive FCR values in all groups<emph>,</emph> indicating that gaze was shifted downward towards the chest region for Reversed (see Figure 5).</p> <p>Graph: Figure 5. class="chapter-para">Average Face-Chest Ratios (FCR) for each participant group. FCR values at around zero mean participants look equally at the Face and Chest regions outlined in the insert figure of the signer. An FCR greater than zero means a bias for face-looking over chest-looking. For all four groups, and both video direction conditions, there is a preference to look at the face. However, FCR is significantly lower during reversed stories, indicating video reversal is associated with a shift downward in looking behavior and possibly increased looking at the chest region across all groups. Error bars denote SEM. The belly area was not included because this captured less than 1% of total gaze.</p> <hd id="AN0143509755-20">Correlations Amongst AoA, Behavior, and Eye Gaze</hd> <p>Correlations among all metrics (AoA, Years Signing, Gist, Lexical Recall, percent looking time at eye, mouth, and neck AOIs, and Face-Chest Ratio) are presented in Table 6. Surprisingly, no correlation was found between any demographic or behavioral measure and any eye gaze, with the exception of a marginally significant positive correlation between Years Signing and mouth-looking during Reversed stories (r =.25, p =.07).</p> <p>Table 6. Correlations amongst subject characteristics (AoA and Years Signing) and behavioral measures (Gist and Lexical Recall) with eye gaze metrics (percent Looking for each AOI and the Face-Chest Ratios) for all subjects</p> <p> <ephtml> <table><thead><tr><th colspan="8">Forward (High Intelligibility). </th></tr></thead><tbody><tr><td /><td>AoA of ASL </td><td>Years Signing </td><td>Lexical Recall </td><td>Eyes </td><td>Mouth </td><td>Neck </td><td /></tr><tr><td>Eyes </td><td>0.10 </td><td>−0.10 </td><td>−0.13 </td><td /><td /><td /><td /></tr><tr><td>Mouth </td><td>−0.06 </td><td>0.22 </td><td>0.12 </td><td>−.62*** </td><td /><td /><td /></tr><tr><td>Neck </td><td>−0.13 </td><td>−0.04 </td><td>0.05 </td><td>−.43** </td><td>−.40** </td><td /><td /></tr><tr><td>Face-Chest Ratio </td><td>0.07 </td><td>0.12 </td><td>−0.03 </td><td>0.43** </td><td>0.44** </td><td>−.97*** </td><td /></tr><tr><td colspan="5"><italic>Forward Gist was omitted because performance was at ceiling.</italic></td><td /><td /><td /></tr><tr><td colspan="8">Reversed (Low Intelligibility) </td></tr><tr><td /><td>AoA of ASL </td><td>Years Signing </td><td>Gist </td><td>Lexical Recall </td><td>Eyes </td><td>Mouth </td><td>Neck </td></tr><tr><td>Eyes </td><td>0.08 </td><td>−0.03 </td><td>−0.03 </td><td>−0.14 </td><td /><td /><td /></tr><tr><td>Mouth </td><td>−0.09 </td><td>0.25 </td><td>0.10 </td><td>0.14 </td><td>−.54*** </td><td /><td /></tr><tr><td>Neck </td><td>−0.09 </td><td>−0.11 </td><td>0.0 </td><td>0.08 </td><td>−.50*** </td><td>−0.39** </td><td /></tr><tr><td>Face-Chest Ratio </td><td>−0.01 </td><td>0.23 </td><td>0.04 </td><td>−0.03 </td><td>0.48*** </td><td>0.45*** </td><td>−.96*** </td></tr></tbody></table> </ephtml> </p> <hd id="AN0143509755-21">Discussion</hd> <p>We all arrive at a language task -- reading a book, listening to a speaker, watching a signer -- with a set of gaze behaviors that are amenable and responsive to the quality of the linguistic input and our prior language experiences. For example, gaze behavior during reading changes when the text is more difficult to comprehend, due to various perceptual or linguistic reasons ([<reflink idref="bib46" id="ref83">46</reflink>]). In this study, we addressed two main questions: Does language expertise impact gaze patterns during natural sign watching? Do signers adjust gaze behavior depending on whether or not they understand the story? To manipulate ease of comprehension (or "intelligibility"), we explored a novel stimulus manipulation—video reversal—and investigated whether language expertise affected the magnitude to which signers adjusted their eye gaze during the reversed condition. We hypothesized that we would observe group differences based on whether participants focused more on the face region compared to regions below the face where the hands occur more frequently, and that these eye gaze behaviors would change if the sign language input was more difficult to understand.</p> <hd id="AN0143509755-22">Story Intelligibility</hd> <p>First, we analyzed how well groups understood the stories in forward and reversed conditions. As expected, Deaf Early, Deaf Late, and Hearing Late signers understood quite well videos of classic fairy tales told in ASL in the natural, forward condition. Hearing Novice signers (who had taken 3 or 4 ASL classes within the last 2 years) understood these stories less well. However, when the video was reversed, all four groups experienced significantly decreased comprehension. Reversal impaired signers' abilities both to discern the "gist" of the story and to recall specific signs that appeared in the story. This reversal effect is primarily due to the fact that reversing word order renders narratives ungrammatical and nonsensical. We note with interest that the reversal manipulation did not make signed narratives <emph>entirely</emph> incomprehensible, unlike what would be expected for reversed speech. For reversed signed narratives, the average reduction in Gist was ~ 45 percent and Lexical Recall ~ 14 percent (and these values did depend on the participants' language expertise, which we turn to next). This might be because, for individual words, reversal only affects a subset of signs where path is irreversible (PASS-OUT or BELIEVE) while many other signs might be relatively unaffected because they have no motion path (MOTHER and EAT) or they are reversible when signed (PLAY is the same when reversed). Even for badly-affected words such as BELIEVE, handshapes and location features are still preserved which perhaps more experienced signers can utilize and "piece together" to decipher reversed narratives.</p> <p>The magnitude of this reversal effect appeared to depend on whether the signer was expert versus novice. Statistical results indicated significant main effects of subject group for both Gist and Lexical Recall, and these group differences were primarily driven by group differences for reversed stimuli. Corroborating this, correlations across all participants revealed strong links between AoA and their capacity to understand reversed stories for both Gist and Lexical Recall measures. In sum, it appears that this particular video manipulation engages cognitive processes that are sensitive to age of ASL acquisition. Based on these findings, we think that video reversal is useful for further exploring acquisition-related questions. Such results are congruent with past findings that processing of sign language is highly dependent on AoA ([<reflink idref="bib14" id="ref84">14</reflink>]; [<reflink idref="bib26" id="ref85">26</reflink>]; [<reflink idref="bib27" id="ref86">27</reflink>]; [<reflink idref="bib30" id="ref87">30</reflink>]; [<reflink idref="bib31" id="ref88">31</reflink>]; [<reflink idref="bib32" id="ref89">32</reflink>]; [<reflink idref="bib33" id="ref90">33</reflink>]; [<reflink idref="bib36" id="ref91">36</reflink>]).</p> <p>Differences in vocabulary size and language proficiency unquestionably impacts one's ability to comprehend language and explains to some degree why early versus late AoA signers differed in the processing of distorted or unintelligible stimuli. However, the two groups may have also employed different processing strategies during comprehension. [<reflink idref="bib30" id="ref92">30</reflink>]) has suggested that late AoA produces "a shallower level of language processing" (p. 26). Specifically, late deaf learners appear to be "hypersensitive" to surface features including visual and sublexical phonemic properties in sign language, and consequently have less cognitive resources available for higher-level semantic and syntactic processing ([<reflink idref="bib31" id="ref93">31</reflink>]; [<reflink idref="bib30" id="ref94">30</reflink>]). With this in mind, did early versus late learners of ASL rely on different levels of language organization and processing strategies during the video-watching task? Performance on Gist and Lexical Recall measures was significantly correlated; participants who understood the story were able to correctly recall more lexical items. However, Gist appeared to be more strongly affected by AoA than Lexical Recall as evidenced by larger decreases in accuracy with later AoA. While video reversal does affect all levels of language organization, we believe it most profoundly affected syntactic and semantic processing, as evidenced by the stronger effect of late AoA on the Gist task.</p> <p>We hypothesize that lexical recall likely is a "shallower" task involving short-term memory than is the Gist task. That is, for the lexical recall task, signers, regardless of AoA, are similarly capable of attending to surface phonological features and of retrieving these features from memory when prompted. During video reversal, many of these features are still preserved (e.g. handshape and location features are still evident, even if presented out of order; [<reflink idref="bib60" id="ref95">60</reflink>]), so these features, even altered, can be retrieved during a lexical recall task. The gestalt ("gist") of the story, however, is lost to late-AoA signers who may have fewer cognitive resources for recovering syntactic and semantic features due to their greater reliance on phonological features. [<reflink idref="bib25" id="ref96">25</reflink>]) has suggested that late learners rely more heavily on semantic information compared to early learners. Semantic information is profoundly altered in reversed video; without that information, late learners have greater difficulty identifying the "gist" of the story. Early signers, by contrast, are able to better cope with incomplete, distorted, or unintelligible language signals due to more robust linguistic representations—both top-down and bottom-up processing streams—afforded by early language acquisition ([<reflink idref="bib5" id="ref97">5</reflink>]; [<reflink idref="bib31" id="ref98">31</reflink>]; [<reflink idref="bib34" id="ref99">34</reflink>]). The use of two different story comprehension measures—Gist and Lexical Recall—support past research suggesting that late learners differently allocate cognitive resources for different levels of language processing compared to early learners.</p> <p>One might ask which mattered more: Hearing Status, Years Signing, or AoA. While teasing these apart was not the primary objective of this study, results from the Gist measure suggest AoA might be more key. First, Deaf Late signers were less able to understand the content of reversed stories than Deaf Early signers. These two groups were both deaf and had similar years of signing, while having different AoA. Deaf Late and Hearing Late signers have similar AoA and also performed similarly on the comprehension measures, despite being different in hearing status and years of signing. Together, these group comparisons suggest that ASL acquisition in infancy or early childhood allows one to be <emph>most resilient</emph> to the effects of video reversal. Future studies may benefit from the inclusion of a "Hearing Early" group, that is, hearing people who grew up with deaf signing parents (e.g. children of deaf parents (CODAs)) to further tease apart the effects of hearing status and childhood language acquisition.</p> <hd id="AN0143509755-23">Eye Gaze</hd> <p>As expected, all groups directed their gaze predominately at the face. The high degree of focus on the face mirrors what others have reported ([<reflink idref="bib1" id="ref100">1</reflink>]; [<reflink idref="bib11" id="ref101">11</reflink>]; [<reflink idref="bib15" id="ref102">15</reflink>]; [<reflink idref="bib29" id="ref103">29</reflink>]; [<reflink idref="bib35" id="ref104">35</reflink>]). This is also supported by the Face-Chest Ratio (FCR) data; all groups showed positive FCRs indicating greater face-looking than chest-looking (which includes neck to lower chest). One important, but not unexpected, finding was greater mouth-looking than eye-looking among all signers, replicating the findings of [<reflink idref="bib1" id="ref105">1</reflink>]) and [<reflink idref="bib29" id="ref106">29</reflink>]). This finding may be in part due to the use of non-manual mouthing in our story stimuli. [<reflink idref="bib15" id="ref107">15</reflink>], however, reported deaf signers focused more on the eyes than on the mouth. As mentioned earlier, we suggest the difference lies in the use of live versus video recorded stimuli. In [<reflink idref="bib15" id="ref108">15</reflink>], deaf participants watched the storyteller while both were in the same room and looking directly at each other. This setting may involve stronger focus on the eyes which Emmorey et al. suggested is an expression of social cues and raises intriguing questions about how eye contact may differ between live versus "televised" (i.e. video chat) dyadic sign language communication. Furthermore, their approach to manipulating complexity did not, in fact, make the narratives more difficult to understand, as was done in the present study, but rather they increased the number of grammatically complex structures. In their study, native versus novice signers did not differ in their comprehension of the stories, while our manipulation did affect comprehension for those groups.</p> <p>Based on the heat maps (Figure 4), one might ask, though, why was the neck even a significant area of interest for all groups as this is not a canonical place of articulation in ASL? We believe it is caused by the signer's head nodding and body tilts, which sometimes places the mouth very close to the chin and neck region if the model nods her head forward. Even though the AOI position was dynamic, it is possible that rapid and frequent head nodding and head movement might briefly shift gaze downward, causing fixations to be calculated as falling within the neck AOI. More importantly, we also speculate the hands might have what we call a "gravitational pull" on observers' eye gaze. This speculation is based on the fact that the hands appear below the face more often than they do above the face.7 Also, less grammatical information is conveyed via the forehead (above the face), while the hands, often located below the face, contain a great deal of fine-grained linguistic information. Therefore, we should expect an asymmetric distribution of eye gaze along the vertical body midline, with greater gaze below the face.</p> <p>We observed an important difference in the gaze behavior of Deaf Early and Deaf Late groups. Deaf Late signers had a higher focus on the mouth, possibly due to greater lipreading (either out of habit or necessity) as an effect of later AoA. This is somewhat corroborated in part by [<reflink idref="bib42" id="ref109">42</reflink>]) eye tracking study of classroom interpreting which found deaf and hard-of-hearing signers with less sign experience looked more at the speaking instructor while deaf and hard-of-hearing experienced signers looked more at the signing interpreter. That is also consistent with [<reflink idref="bib15" id="ref110">15</reflink>] which finds that beginner ASL signers focus on the mouth too, possibly to extract English information conveyed via the lips. Future research could explore the role of mouthing in gaze behavior during sign watching.</p> <p>Most importantly, this study confirmed that video reversal changed eye gaze behavior, possibly reflecting increased cognitive load and the demands of processing less intelligible input. The effect of video reversal on sign watching was to reduce focus on the face and distribute gaze over a larger vertical region of the signer's midline. Specifically, gaze shifted below the mouth towards the neck and chest region. Remarkably, gaze analyses did <emph>not</emph> reveal significant interactions between Subject Group and Video Direction which we had originally predicted. This suggests that all groups' gaze changed in the same way regardless of AoA or language experience. However, visual inspection of the data (see Figure 5) show Hearing Novice signers had the <emph>largest</emph> downward shift for reversed stimuli. Furthermore, the heat maps in Figure 4 showed that Hearing Novice signers clearly distributed their gaze downward for normal videos, and especially so for reversed videos. This behavior is likely due to their relative unfamiliarity with various sign linguistic features, necessitating more fixations closer to the manual articulators as to place them within their foveal instead of parafoveal vision. This might also be tied to their greater reliance on a "shallower" level of processing, as described earlier; i.e. hearing novice signers' overt attention is drawn to surface phonological features (e.g. handshape and location features).</p> <p>We did not observe these effects for Deaf Early, Deaf Late, and Hearing Late signers, despite AoA differences in these groups. That suggests an important finding: there appears to be no critical period for "sign-watching" unlike the well-supported critical period for acquiring a first language ([<reflink idref="bib30" id="ref111">30</reflink>]; [<reflink idref="bib31" id="ref112">31</reflink>]; [<reflink idref="bib39" id="ref113">39</reflink>]). That is, with at least five years of signing experience, and as long as that person signs frequently and gains mastery of the language, they can demonstrate "efficient" gaze behavior similar to Deaf Early signers. Hence, while we argue that perceptual efficiency is crucial for maximal or efficient comprehension, it is linguistic ability and knowledge—and not gaze control or eye movement behavior—that is subject to age-related critical periods of exposure.</p> <p>Surprisingly, there was no correlation between gaze behavior and accuracy on either task. While it is the case that reversal impacts accuracy, and reversal impacts gaze, we could not find evidence for a direct relationship between eye gaze and comprehension. However, we do have data from a companion study [<reflink idref="bib6" id="ref114">6</reflink>] that suggests such a relationship. We collected baseline measures of Hearing Novice signers' eye gaze behavior and story comprehension while watching narratives. Then we explicitly instructed them to focus their attention on the "lower part of the face" when watching more narratives. When the novice signers did so, their story comprehension scores increased significantly. While language proficiency obviously is the largest factor in comprehension of signed narratives, gaze behavior may nonetheless play a small, but not insignificant, role in comprehension. This relationship, however, may exist among new signers only. We suggest that it is precisely the absence of a relationship between eye gaze and story comprehension among fluent signers is what makes them good signers! That is, they maintain the most "efficient" eye gaze behavior (focusing on the face region) even in difficult settings, because it is that behavior that is the best way to understand sign language input. Alternative analyses of eye gaze behavior that preserves temporal information (e.g. time-series analysis) as opposed to spatial information (e.g. AOIs) may better capture nuanced eye gaze behaviour in signers across different conditions and reveal key characteristics of eye gaze control that may relate to story comprehension, such as grammatical features or hand position.</p> <p>There are several limitations of the present study in its attempts to characterize eye movements in deaf and hearing signing adults. First, in examining how a range of language expertise from expert to novice impacts gaze behavior, we used self-reported proficiency, which is a very subjective way of describing one's language knowledge. Future studies should include standardized sign proficiency assessments as a more accurate measure (e.g. [<reflink idref="bib18" id="ref115">18</reflink>]). Second, future studies could aim to control the entanglement of several person-related factors such as age-at-testing, AoA, and Hearing Status which were partly confounded in the present study. It will be very important to address variation in language experiences as past studies have found mixed results which might be explained by heterogenous person-related factors across these studies. Finally, our stimuli involved widely-known fairy tales and a narrator whose retelling involved mouthing and many non-manual markers on the face and body (as would be expected by any talented sign language storyteller). Both factors certainly might impact gaze behavior; future studies could address topic familiarity (i.e. widely-known fairy tales versus original, never-before-seen content) and the degree to which the use of mouthing and other nonmanual markers on the face and body may affect eye gaze.</p> <p>In sum, this study represents one of the first careful characterizations of eye gaze behavior among different types of signers and accompanied by language comprehension reports. When we consider the inalienable role of vision in the comprehension of a visual language, it is surprising how under-studied these important visual processes are. The present study demonstrates how sensory, language, and text factors all contribute to eye gaze behavior during sign-watching. We have shown evidence for what appears to be "efficient" eye gaze behavior among fluent signers, and conversely, what "inefficient" sign-watching looks like among new signers. Importantly, this "efficient" eye gaze behavior persists even in low-intelligibility settings, suggesting that it is this specific behavior that permits the most efficient perception and comprehension of sign language. These findings may extend to other real-world instances of low intelligibility such as sign watching through smart phones, from far distances or different unusual angles, while in moving vehicles or walking, or if the viewer has reduced visual acuity. We hope these findings will spur new theoretical advances in describing the specific cognitive processes underpinning the relationship between eye gaze and language perception.</p> <p>In addition, we have introduced video reversal as a simple, useful stimulus manipulation that could be used to study language processing. This manipulation shows that later learners of ASL have considerably more difficulty understanding reversed stories. Finally, there appears to be no critical period for learning efficient eye gaze behavior while watching sign language. However, early language learning continues to be obligatory for optimal language comprehension. These findings could support future studies testing whether we can promote specific eye gaze behaviors in deaf children and in ASL learners that support optimal language comprehension. We also encourage future studies relating deaf people's eye gaze during sign-watching to their eye gaze <emph>during reading</emph>, as there is evidence that deaf people have more efficient control of eye gaze during reading compared to age- and skill-matched hearing people ([<reflink idref="bib4" id="ref116">4</reflink>]; [<reflink idref="bib3" id="ref117">3</reflink>]).</p> <hd id="AN0143509755-24">Acknowledgements</hd> <p>Special gratitude to Cindy O'Grady Farnady for her help in creating the stimuli and Aubrey Adiao for scheduling our participants. We are grateful to Sarah C. Tyler for her instrumental help and all the Deaf and Hearing people who participated in this study.</p> <p>Funding was provided by an NSF Award (1423500) to Bosworth; and an NIH National Eye Institute (R01-EY024623) award to Bosworth. Adam Stone was supported by a Research Supplement to Promote Diversity in Health-Related Research from the National Eye Institute (NEI/NIH).</p> <hd id="AN0143509755-25">Endnotes</hd> <ref id="AN0143509755-26"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref14" type="bt">1</bibl> <bibtext> The ability to determine whether an observer is looking at parts of an image (such as eyes, nose, and mouth of a face) is dependent on several important methodological factors; for one, if areas of interest (AOIs) are drawn very small and/or the stimulus image was small, then a study's ability to measure looking on these areas would be low. A study's measurement precision also depends on calibration and instrument precision. We recorded our own measurement error by incorporating calibration checks throughout the experiment. Knowing that our largest possible, hypothetical measurement error was 1.15° of visual angle, we drew AOI boxes larger than this and made comparisons on the signer's body that were greater than this distance. It is unknown whether older eye tracking papers took similar precautions to ensure that their measurement precision was "greater" than their measurement error.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref33" type="bt">2</bibl> <bibtext> Local time reversal is a manipulation where the recorded signal is divided into several smaller segments of fixed duration, and then each segment is played in reverse, but the order of segments is not changed (Greenberg & Arai, 2001 ; Hwang, 2011 ; Saberi & Perrott, 1999). In this case, there is still some degree of grammatical cohesion and structure for small segments. Conversely, processing of <emph>global</emph> reversals of sign language videos, where the <emph>entire</emph> recording is played backwards (as was done in this study) has, to our knowledge, never been tested.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref62" type="bt">3</bibl> <bibtext> After first viewing reversed stories for the purpose of comprehension, we asked participants, who were not yet informed about the manipulation, "What was odd about that story?" Only about half our participants could identify that our manipulation was indeed a video reversal (understanding that we did so with video playback), with the remaining people thinking we did other types of manipulations (for example, we "changed the timing" or "added pauses") or saying it was a foreign sign language. One aptly called it "a jumble of signs." In sum, by all means, the reversed story was very (but not completely) unintelligible, as we intended.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref116" type="bt">4</bibl> <bibtext> In many published studies, signers who acquired ASL at birth/during infancy are called "native" signers, but here we labeled all signers who acquired ASL by 4 years as "early signers," and this group includes native signers.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref51" type="bt">5</bibl> <bibtext> Missing data here refers to time points when no eye gaze data was collected due to saccades, smooth movement, blinks, occlusions, looking away, or moving out of eye tracker range. The means and standard deviations of percent missing data for each group was: Deaf Early (11.9 percent ± 18.5 percent), Deaf Late (11.3 percent ± 18.7 percent), Hearing Late (7.7 percent ± 12.1 percent), and Hearing Novice (10.0 percent ± 15.6 percent).</bibtext> </blist> <blist> <bibl id="bib6" idref="ref114" type="bt">6</bibl> <bibtext> As mentioned earlier, the side AOIs and the belly AOIs have very few gaze points, hence why we chose to focus on the Face versus upper Chest (below chin) region in calculating ratios. Some of the dispersion of gaze points seen for Reversed videos do extend to these peripheral areas, but the percent looking values are so small and findings were not impacted by exclusion of these peripheral AOIs.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref12" type="bt">7</bibl> <bibtext> Averaging across all stories, either hand passed over or contacted the face on only 22.7% (SD = 7.7%) of all video frames. 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Effects of Video Reversal on Gaze Patterns during Signed Narrative Comprehension
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Bosworth%2C+Rain%22">Bosworth, Rain</searchLink><br /><searchLink fieldCode="AR" term="%22Stone%2C+Adam%22">Stone, Adam</searchLink><br /><searchLink fieldCode="AR" term="%22Hwang%2C+So-One%22">Hwang, So-One</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Deaf+Studies+and+Deaf+Education%22"><i>Journal of Deaf Studies and Deaf Education</i></searchLink>. Jul 2020 25(3):283-297.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Oxford University Press. Great Clarendon Street, Oxford, OX2 6DP, UK. Tel: +44-1865-353907; Fax: +44-1865-353485; e-mail: jnls.cust.serv@oxfordjournals.org; Web site: http://jdsde.oxfordjournals.org/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 15
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2020
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Institutes of Health (DHHS)<br />National Science Foundation (NSF)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: R01EY024623<br />1423500
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Video+Technology%22">Video Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+Movements%22">Eye Movements</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Patterns%22">Behavior Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22American+Sign+Language%22">American Sign Language</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Proficiency%22">Language Proficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Comprehension%22">Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Acquisition%22">Language Acquisition</searchLink><br /><searchLink fieldCode="DE" term="%22Hearing+Impairments%22">Hearing Impairments</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Story+Telling%22">Story Telling</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1093/deafed/enaa007
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1081-4159
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Language knowledge, age of acquisition (AoA), and stimulus intelligibility all affect gaze behavior for reading print, but it is unknown how these factors affect "sign-watching" among signers. This study investigated how these factors affect gaze behavior during sign language comprehension in 52 adult signers who acquired American Sign Language (ASL) at different ages. We examined gaze patterns and story comprehension in four subject groups who differ in hearing status and when they learned ASL (i.e. Deaf Early, Deaf Late, Hearing Late, and Hearing Novice). Participants watched signed stories in normal (high intelligibility) and video-reversed (low intelligibility) conditions. This video manipulation was used because it distorts word order and thus disrupts the syntax and semantic content of narratives, while preserving most surface phonological features of individual signs. Video reversal decreased story comprehension accuracy, and this effect was greater for those who learned ASL later in life. Reversal also was associated with more dispersed gaze behavior. Although each subject group had unique gaze patterns, the effect of video reversal on gaze measures was similar across all groups. Among fluent signers, gaze behavior was not correlated with AoA, suggesting that "efficient" sign watching can be quickly learnt even among signers exposed to signed language later in life.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1256387
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1256387
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1093/deafed/enaa007
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 283
    Subjects:
      – SubjectFull: Video Technology
        Type: general
      – SubjectFull: Eye Movements
        Type: general
      – SubjectFull: Behavior Patterns
        Type: general
      – SubjectFull: American Sign Language
        Type: general
      – SubjectFull: Language Proficiency
        Type: general
      – SubjectFull: Age Differences
        Type: general
      – SubjectFull: Comprehension
        Type: general
      – SubjectFull: Adults
        Type: general
      – SubjectFull: Language Acquisition
        Type: general
      – SubjectFull: Hearing Impairments
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Story Telling
        Type: general
    Titles:
      – TitleFull: Effects of Video Reversal on Gaze Patterns during Signed Narrative Comprehension
        Type: main
  BibRelationships:
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      – PersonEntity:
          Name:
            NameFull: Bosworth, Rain
      – PersonEntity:
          Name:
            NameFull: Stone, Adam
      – PersonEntity:
          Name:
            NameFull: Hwang, So-One
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          Dates:
            – D: 01
              M: 07
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 1081-4159
          Numbering:
            – Type: volume
              Value: 25
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Journal of Deaf Studies and Deaf Education
              Type: main
ResultId 1