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Reduced Implicit but Not Explicit Knowledge of Cross-Situational Statistical Learning in Developmental Dyslexia

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Title: Reduced Implicit but Not Explicit Knowledge of Cross-Situational Statistical Learning in Developmental Dyslexia
Language: English
Authors: Kligler, Nitzan, Yu, Chen, Gabay, Yafit
Source: Cognitive Science. Sep 2023 47(9).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 30
Publication Date: 2023
Sponsoring Agency: National Institutes of Health (NIH) (DHHS)
Contract Number: R01HD093792
Document Type: Journal Articles
Reports - Research
Descriptors: Dyslexia, Language Acquisition, Vocabulary Development, Learning Processes, Adults, Pictorial Stimuli, Speech Communication, Correlation, Novelty (Stimulus Dimension), Familiarity, Young Adults, Visual Perception, Auditory Perception, Knowledge Level
DOI: 10.1111/cogs.13325
ISSN: 0364-0213
1551-6709
Abstract: Although statistical learning (SL) has been studied extensively in developmental dyslexia (DD), less attention has been paid to other fundamental challenges in language acquisition, such as cross-situational word learning. Such investigation is important for determining whether and how SL processes are affected in DD at the word level. In this study, typically developed (TD) adults and young adults with DD were exposed to a set of trials that contained multiple spoken words and multiple pictures of individual objects, with no information about word-referent correspondences provided within a trial. Nonetheless, cross-trial statistical relations could be exploited to learn word-referent mappings. The degree of within-trial reference uncertainty and the novelty of to-be-learned objects (novel or familiar) were varied under different learning conditions. The results show that across all conditions, young adults with DD were significantly impaired in their ability to exploit cross-trial regularities in co-occurring visual-auditory streams to discover word-referent mappings. Observed impairments were most pronounced when within-trial reference uncertainty was the highest. Subjective measures of knowledge awareness revealed greater development of implicit but not explicit knowledge in the TD group than in the DD group. Together, these findings suggest that the SL deficit in DD affects fundamental language learning challenges at the word level and points to greater reliance on explicit processes due to impaired implicit associative learning among individuals with DD. Such a deficit is likely to influence spoken language acquisition, and in turn affect literacy skills, in people with DD.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1393996
Database: ERIC
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  Value: <anid>AN0172347578;cgn01sep.23;2023Sep28.06:04;v2.2.500</anid> <title id="AN0172347578-1">Reduced Implicit but not Explicit Knowledge of Cross‐Situational Statistical Learning in Developmental Dyslexia </title> <p>Although statistical learning (SL) has been studied extensively in developmental dyslexia (DD), less attention has been paid to other fundamental challenges in language acquisition, such as cross‐situational word learning. Such investigation is important for determining whether and how SL processes are affected in DD at the word level. In this study, typically developed (TD) adults and young adults with DD were exposed to a set of trials that contained multiple spoken words and multiple pictures of individual objects, with no information about word‐referent correspondences provided within a trial. Nonetheless, cross‐trial statistical relations could be exploited to learn word‐referent mappings. The degree of within‐trial reference uncertainty and the novelty of to‐be‐learned objects (novel or familiar) were varied under different learning conditions. The results show that across all conditions, young adults with DD were significantly impaired in their ability to exploit cross‐trial regularities in co‐occurring visual–auditory streams to discover word‐referent mappings. Observed impairments were most pronounced when within‐trial reference uncertainty was the highest. Subjective measures of knowledge awareness revealed greater development of implicit but not explicit knowledge in the TD group than in the DD group. Together, these findings suggest that the SL deficit in DD affects fundamental language learning challenges at the word level and points to greater reliance on explicit processes due to impaired implicit associative learning among individuals with DD. Such a deficit is likely to influence spoken language acquisition, and in turn affect literacy skills, in people with DD.</p> <p>Keywords: Developmental dyslexia; Cross‐situational statistical learning; Statistical learning; Referential ambiguity; Implicit–explicit knowledge</p> <hd id="AN0172347578-2">Introduction</hd> <p>The world surrounding us offers an abundance of statistical patterns that, once successfully recognized, can be used to guide behavior (Conway, [<reflink idref="bib11" id="ref1">11</reflink>]). The ability to detect and use statistical patterns embedded in the environment is related to statistical learning (SL), which has been shown to play a critical role in different aspects of development, especially in language acquisition (Thiessen, Kronstein, & Hufnagle, [<reflink idref="bib103" id="ref2">103</reflink>]). Rapidly expanding research suggests that listeners can utilize statistical regularities for segmenting words from fluent speech (Saffran, Aslin, & Newport, [<reflink idref="bib83" id="ref3">83</reflink>]; Saffran, Johnson, Aslin, & Newport, [<reflink idref="bib84" id="ref4">84</reflink>]) and for discovering which cues in their linguistic environment are important for making phonological distinctions (Hayes‐Harb, [<reflink idref="bib34" id="ref5">34</reflink>]; Yoshida, Pons, Maye, & Werker, [<reflink idref="bib121" id="ref6">121</reflink>]). The role of SL in language acquisition has been further supported by evidence showing that individual differences in SL performance predict variability in various linguistic outcomes (Arciuli & Simpson, [<reflink idref="bib3" id="ref7">3</reflink>]; Misyak, Christiansen, & Tomblin, [<reflink idref="bib63" id="ref8">63</reflink>]; von Koss Torkildsen, Arciuli, & Wie, [<reflink idref="bib115" id="ref9">115</reflink>]).</p> <p>Due to its essential role in typical language acquisition, SL has received considerable attention within the field of language disorders, among them developmental dyslexia (DD; for reviews, see Arciuli & Conway, [<reflink idref="bib2" id="ref10">2</reflink>]; Lee, Cui, & Tong, [<reflink idref="bib54" id="ref11">54</reflink>]; Schmalz, Altoè, & Mulatti, [<reflink idref="bib88" id="ref12">88</reflink>]; Singh & Conway, [<reflink idref="bib95" id="ref13">95</reflink>]). DD is a developmental language disorder characterized by difficulty in acquiring reading, writing, and spelling skills despite adequate educational opportunities. Impairments among individuals with DD are not limited to the linguistic domain (for a review, see Démonet, Taylor, & Chaix, [<reflink idref="bib14" id="ref14">14</reflink>]), leading researchers to postulate a domain‐general deficit in detecting statistical patterns in sensory input (Nicolson & Fawcett, [[<reflink idref="bib65" id="ref15">65</reflink>], [<reflink idref="bib68" id="ref16">68</reflink>]]). Indeed, independent research investigations point to SL impairments in DD (Ballan, Durrant, Manoach, & Gabay, [<reflink idref="bib5" id="ref17">5</reflink>]; Dobó, Lukics, Szőllősi, Németh, & Lukács, [<reflink idref="bib18" id="ref18">18</reflink>]; Gabay, Schiff, & Vakil, [<reflink idref="bib29" id="ref19">29</reflink>]; Howard, Howard, Japikse, & Eden, [<reflink idref="bib40" id="ref20">40</reflink>]; Lum, Ullman, & Conti‐Ramsden, [<reflink idref="bib57" id="ref21">57</reflink>]; Stoodley, Harrison, & Stein, [<reflink idref="bib100" id="ref22">100</reflink>]). These impairments have been demonstrated across a diverse range of SL paradigms (Ballan et al., [<reflink idref="bib5" id="ref23">5</reflink>]; Bogaerts, Szmalec, Hachmann, Page, & Duyck, [<reflink idref="bib9" id="ref24">9</reflink>]; Dobó et al., [<reflink idref="bib18" id="ref25">18</reflink>]; Gabay, Vakil, Schiff, & Holt, [<reflink idref="bib31" id="ref26">31</reflink>]; Lum et al., [<reflink idref="bib57" id="ref27">57</reflink>]) in different sensory modalities (Kahta & Schiff, [<reflink idref="bib44" id="ref28">44</reflink>]; Kligler & Gabay, [<reflink idref="bib48" id="ref29">48</reflink>]; Pavlidou & Williams, [<reflink idref="bib73" id="ref30">73</reflink>]; Pavlidou, Williams, & Kelly, [<reflink idref="bib74" id="ref31">74</reflink>]), in multiple domains (Gabay et al., [<reflink idref="bib29" id="ref32">29</reflink>]; Hedenius, Lum, & Bölte, [<reflink idref="bib36" id="ref33">36</reflink>]), and with different developmental trajectories (Kerkhoff, De Bree, De Klerk, & Wijnen, [<reflink idref="bib46" id="ref34">46</reflink>]; Tong, Leung, & Tong, [<reflink idref="bib105" id="ref35">105</reflink>]). Despite some inconsistent results in the literature (for discussions, see Schmalz et al., [<reflink idref="bib88" id="ref36">88</reflink>]; van Witteloostuijn, Boersma, Wijnen, & Rispens, [<reflink idref="bib111" id="ref37">111</reflink>]), a recent meta‐analysis involving 59 studies that compared SL in individuals with DD and typical readers across different SL learning paradigms pointed to converging evidence of an apparent SL weakness in individuals with DD (Lee et al., [<reflink idref="bib54" id="ref38">54</reflink>]).</p> <p>This SL deficit has been shown to affect language learning tasks, such as speech segmentation and speech categorization. Compared to typical readers, adults with DD are less able to segment words from continuous input across speech and nonspeech stimuli, and similar observations have been made within the visual domain (Gabay, Thiessen, & Holt, [<reflink idref="bib30" id="ref39">30</reflink>]; Kligler & Gabay, [<reflink idref="bib48" id="ref40">48</reflink>]; Sigurdardottir et al., [<reflink idref="bib94" id="ref41">94</reflink>]; Singh, Walk, & Conway, [<reflink idref="bib96" id="ref42">96</reflink>]; Tong, Zhang, & He, [<reflink idref="bib104" id="ref43">104</reflink>]; but also see van Witteloostuijn, Boersma, Wijnen, & Rispens, [<reflink idref="bib112" id="ref44">112</reflink>]). Furthermore, individuals with DD exhibit reduced sensitivity to the distributional frequency of speech cues, compared to typical readers (Vandermosten, Wouters, Ghesquière, & Golestani, [<reflink idref="bib113" id="ref45">113</reflink>]), including reduced sensitivity to distributional information when complex nonspeech sound categories are acquired incidentally (Gabay & Holt, [<reflink idref="bib27" id="ref46">27</reflink>]). The SL abilities of individuals with DD were found to be correlated with their phonological and reading impairments (Gabay & Holt, [<reflink idref="bib27" id="ref47">27</reflink>]; Gabay et al., [<reflink idref="bib30" id="ref48">30</reflink>]; Kligler & Gabay, [<reflink idref="bib48" id="ref49">48</reflink>]).</p> <hd id="AN0172347578-3">Cross‐situational statistical learning (CSSL)</hd> <p>Language learning involves more than simply identifying word boundaries or categorizing speech sounds. Another fundamental learning problem that listeners encounter at the word level is the issue of correctly extracting possible meanings from extralinguistic context and mapping them to perceptual representations that have been formed and temporarily stored (word‐to‐world mapping problem; Cunillera, Laine, Càmara, & Rodríguez‐Fornells, [<reflink idref="bib12" id="ref50">12</reflink>]). This word learning process is crucial in language acquisition, as it clearly underlies language ability, that is, the ability to create conceptual representations linked to arbitrary sounds and symbols. Word‐to‐world mapping is challenging because the number of mappings between words and potential referents is infinite (the referential ambiguity problem; Quine, [<reflink idref="bib77" id="ref51">77</reflink>]). Prior studies have shown that learners can reduce referential ambiguity by utilizing a variety of linguistic (Gleitman, [<reflink idref="bib32" id="ref52">32</reflink>]), social (Baldwin, [<reflink idref="bib4" id="ref53">4</reflink>]), and attentional cues (Smith & Samuelson, [<reflink idref="bib98" id="ref54">98</reflink>]), as well as by accumulating evidence across individual ambiguous exposures through a process known as CSSL (Smith & Yu, [<reflink idref="bib97" id="ref55">97</reflink>]) in which learners take advantage of the distributional properties of both visual and auditory information. In a CSSL experiment, learners typically perceive a set of potential candidates when they hear a word. A single exposure is insufficient to identify the correct word–object mapping. Rather, by combining information across multiple exposures, listeners can determine the more likely referent by integrating multiple candidate sets over time. Ample evidence shows that infant (Smith & Yu, [<reflink idref="bib97" id="ref56">97</reflink>]), child (Suanda, Mugwanya, & Namy, [<reflink idref="bib101" id="ref57">101</reflink>]), and adult listeners (Roembke & McMurray, [<reflink idref="bib82" id="ref58">82</reflink>]; Yu & Smith, [<reflink idref="bib122" id="ref59">122</reflink>]) are capable of accumulating statistical evidence across individually ambiguous learning contexts with multiple novel words and multiple novel objects. Furthermore, prior research suggests a relationship between CSSL and language‐related skills (Hu, [<reflink idref="bib41" id="ref60">41</reflink>]; McGregor et al., [<reflink idref="bib60" id="ref61">60</reflink>]; McGregor, Rost, Arenas, Farris‐Trimble, & Stiles, [<reflink idref="bib59" id="ref62">59</reflink>]; Penaloza et al., [<reflink idref="bib75" id="ref63">75</reflink>]). Nevertheless, whether and how CSSL is affected in DD is currently unclear.</p> <p>Like other SL challenges, CSSL can occur incidentally without informing participants about the relations between words and referents (Kachergis, Yu, & Shiffrin, [<reflink idref="bib43" id="ref64">43</reflink>]), thus leading some researchers to define these learning challenges as implicit learning (Kim, Seitz, Feenstra, & Shams, [<reflink idref="bib47" id="ref65">47</reflink>]). Yet the extent to which CSSL and other fundamental SL phenomena are entirely implicit remains a matter of debate (Shanks, [<reflink idref="bib90" id="ref66">90</reflink>]). One way of assessing the "implicitness" of a learning process is to examine whether participants develop explicit (conscious)/implicit (unconscious) knowledge about statistical regularities. Implicit and explicit knowledge are acquired differently, through the involvement of two different memory systems. The procedural memory system supports the acquisition of skills, habits, and stimulus–response associations, whereas the declarative memory system is responsible for the acquisition of semantic and episodic knowledge (Packard & Knowlton, [<reflink idref="bib72" id="ref67">72</reflink>]). The declarative system has been shown to underlie explicit knowledge, while implicit knowledge is supported by both declarative and procedural memory systems (Ullman, Earle, Walenski, & Janacsek, [<reflink idref="bib109" id="ref68">109</reflink>]). These two memory systems are presumed to function differently in developmental language disorders (Krishnan, Watkins, & Bishop, [<reflink idref="bib51" id="ref69">51</reflink>]). Consistent with the domain‐general account of language learning, the procedural deficit hypothesis suggests that language deficits in DD likely arise from a selective impairment in procedural memory functions (Nicolson & Fawcett, [<reflink idref="bib67" id="ref70">67</reflink>]; Ullman et al., [<reflink idref="bib109" id="ref71">109</reflink>]). This account is supported by the involvement of the procedural memory system in language acquisition (Ullman, [<reflink idref="bib108" id="ref72">108</reflink>]). Furthermore, individuals with dyslexia often demonstrate impairments in procedural and implicit learning tasks (Gabay et al., [<reflink idref="bib28" id="ref73">28</reflink>]; Hedenius et al., [<reflink idref="bib37" id="ref74">37</reflink>]; Hedenius, Lum, & Bölte, [<reflink idref="bib35" id="ref75">35</reflink>]; Howard et al., [<reflink idref="bib40" id="ref76">40</reflink>]; Vicari, Marotta, Menghini, Molinari, & Petrosini, [<reflink idref="bib114" id="ref77">114</reflink>]). Since SL is a form of learning that relies more on the procedural memory system than on the declarative memory system (for a review, see Sawi & Rueckl, [<reflink idref="bib85" id="ref78">85</reflink>]), it is possible that impaired SL in DD reflects procedural learning deficiencies, yet this is still open to discussion (Bogaerts, Siegelman, & Frost, [<reflink idref="bib8" id="ref79">8</reflink>]).</p> <p>One of the complexities in this debate is that SL tasks, like many other tasks considered to be "procedural/implicit," involve a mixture of implicit and explicit processes (Packard & Goodman, [<reflink idref="bib71" id="ref80">71</reflink>]; Sun, Slusarz, & Terry, [<reflink idref="bib102" id="ref81">102</reflink>]), consistent with striatal and hippocampal brain activity observed when people learn to extract statistical regularities (Durrant, Taylor, Cairney, & Lewis, [<reflink idref="bib20" id="ref82">20</reflink>]; Karuza et al., [<reflink idref="bib45" id="ref83">45</reflink>]; Orpella, Mas‐Herrero, Ripollés, Marco‐Pallarés, & de Diego‐Balaguer, [<reflink idref="bib70" id="ref84">70</reflink>]; Schapiro, Turk‐Browne, Norman, & Botvinick, [<reflink idref="bib87" id="ref85">87</reflink>]). Hence, an independent assessment of implicit and explicit knowledge during an SL task may contribute to this discussion. If impaired SL in DD reflects a procedural memory dysfunction, people with DD will be less likely to develop implicit representations than typically developed (TD) readers, whereas their explicit representations should be similar to or even more enhanced than those of TD learners. Measures of knowledge awareness may therefore provide a better understanding of the cognitive mechanisms involved in SL among people with DD and of the nature of the resulting knowledge.</p> <hd id="AN0172347578-4">Measuring implicit and explicit knowledge</hd> <p>Knowledge awareness can be accessed in several ways, for example, by verbal reports or direct (free generation tasks) and indirect (assessing performance) tests (Dienes & Seth, [<reflink idref="bib17" id="ref86">17</reflink>]; Rebuschat, [<reflink idref="bib81" id="ref87">81</reflink>]). Among these approaches, a well‐established way of dissociating conscious and unconscious processes is to collect subjective measures of awareness (confidence ratings). Two measures commonly used to assess unconscious/conscious knowledge are the guessing score and the zero correlation score (Dienes, Altmann, Kwan, & Goode, [<reflink idref="bib16" id="ref88">16</reflink>]). According to the first criterion (guessing score), knowledge is below the subjective threshold of consciousness when performance is above chance in situations in which participants state they were guessing. According to the second criterion (zero‐correlation criterion), performance is based on conscious knowledge if participants are more confident of their correct choices than of their errors. Another criterion is based on signal detection theory (Kunimoto, Miller, & Pashler, [<reflink idref="bib53" id="ref89">53</reflink>]). According to this approach, correct choices made with high confidence can be classified as hits, while incorrect choices made with high confidence can be classified as false alarms. Then, a Type II d' can be computed to represent participants' awareness of their own performance. If participants are aware of the knowledge they used to make a choice, they presumably believe their choices are correct and should respond with high confidence. In contrast, if participants are unaware of their knowledge, they will randomly assign high‐ and low‐confidence ratings to correct and incorrect choices. An important feature of this method is that the use of signal detection analysis ensures that the measure's sensitivity is not influenced by the participants' own report criteria and is independent of response bias (Tunney & Shanks, [<reflink idref="bib107" id="ref90">107</reflink>]). The use of such types of subjective measures of awareness has shown that SL and other SL‐related phenomena, such as CSSL, involve the development of explicit and implicit knowledge (Bertels, Franco, & Destrebecqz, [<reflink idref="bib7" id="ref91">7</reflink>]; Franco, Cleeremans, & Destrebecqz, [<reflink idref="bib24" id="ref92">24</reflink>]; Hamrick, Rebuschat, Rebuschat, & Williams, [<reflink idref="bib33" id="ref93">33</reflink>]). Even though SL has been studied extensively in DD, the nature of the resulting knowledge has rarely been assessed.</p> <hd id="AN0172347578-5">The present study</hd> <p>The purpose of the present research was to investigate the ability of young adults with DD to make word‐referent mappings and learn word meanings under diverse levels of ambiguity and uncertainty, resembling the way word learning occurs in real‐world learning environments. CSSL plays a critical role in language acquisition. Hence, CSSL impairments are likely to contribute to language deficits observed in language disorders (Ahufinger, Guerra, Ferinu, Andreu, & Sanz‐Torrent, [<reflink idref="bib1" id="ref94">1</reflink>]; McGregor et al., [<reflink idref="bib60" id="ref95">60</reflink>]). If SL deficits in DD (Lee et al., [<reflink idref="bib54" id="ref96">54</reflink>]; Nicolson & Fawcett, [<reflink idref="bib68" id="ref97">68</reflink>]; Singh & Conway, [<reflink idref="bib95" id="ref98">95</reflink>]) also extend to the word level, we can expect that TD readers will outperform readers with DD during CSSL. If people with DD have problems in learning cross‐situational statistical regularities, we can expect their performance to deteriorate as SL challenges increase. To explore this possibility, we examined a CSSL task in young adults with DD and TD, while manipulating the SL challenge by varying the degree of within‐trial ambiguity as in prior research (Yu & Smith, [<reflink idref="bib122" id="ref99">122</reflink>]). We hypothesized that people with DD would perform worse than TD learners when SL challenges increase (i.e., when within‐trial ambiguity is highest).</p> <p>A second aim of the present study was to determine what kind of representations (implicit vs. explicit) are acquired by participants with DD and TD readers when they learn the meaning of words cross‐situationally. This examination is particularly important to determine whether a procedural memory function plays a role in the SL impairments observed in DD, based on the notion that individuals with DD are more likely to rely on explicit learning strategies to overcome their implicit learning impairments (Nicolson & Fawcett, [<reflink idref="bib66" id="ref100">66</reflink>]; Ullman & Pullman, [<reflink idref="bib110" id="ref101">110</reflink>]). This issue has been rarely studied in DD using subjective measures of awareness and has the potential to reveal valuable information about the type of representations acquired by individuals with DD during SL processes. In the present study, we asked participants to provide confidence judgments of their decisions to assess their development of explicit and implicit knowledge in the context of CSSL (Franco et al., [<reflink idref="bib24" id="ref102">24</reflink>]). If a procedural memory dysfunction contributes to SL impairments in DD (Nicolson & Fawcett, [<reflink idref="bib66" id="ref103">66</reflink>]; Ullman & Pullman, [<reflink idref="bib110" id="ref104">110</reflink>]), we expect to observe differences in the development of implicit but not explicit knowledge across the two groups.</p> <p>Our final aim was to examine how CSSL in DD is affected in second‐language‐like (i.e., learning new words for familiar objects) and first‐language‐like situations (i.e., learning new words for novel objects; Prehn‐Kristensen et al., [<reflink idref="bib76" id="ref105">76</reflink>]; Yu & Smith, [<reflink idref="bib122" id="ref106">122</reflink>]). Given that direct word‐to‐concept mappings are less probable during the early phases of learning words in a second language but rather are based on word‐to‐word associations (Hernandez, Li, & MacWhinney, [<reflink idref="bib38" id="ref107">38</reflink>]; Kroll & Stewart, [<reflink idref="bib52" id="ref108">52</reflink>]), the distinction between familiar and novel objects is likely to matter. We used novel objects that learners had never seen before (Experiment 1) and familiar objects with known semantic categories (Experiment 2) as potential referents to examine possible group differences in the context of learning challenges that mimic second‐language or first‐language situations. People with DD struggle to learn native and second languages (Di Betta & Romani, [<reflink idref="bib15" id="ref109">15</reflink>]; Schneider, [<reflink idref="bib89" id="ref110">89</reflink>]; Sparks, Ganschow, & Pohlman, [<reflink idref="bib99" id="ref111">99</reflink>]). If impaired SL processes contribute to these difficulties, impairments in CSSL should be observed under both first‐ and second‐language conditions.</p> <hd id="AN0172347578-6">Experiment 1</hd> <p></p> <hd id="AN0172347578-7">Methods</hd> <p></p> <hd id="AN0172347578-8">Participants</hd> <p>The research sample consisted of two groups, a group of young adults with DD (<emph>N</emph> = 34) and a TD group (<emph>N</emph> = 34), with an age range of 18–33 years. All participants were monolingual Hebrew speakers with no known hearing, neurological, linguistic, attentional, or intellectual impairments, and all came from families of middle to high socioeconomic status. The DD group was recruited mainly through the Yahel Learning Disabilities Center at Haifa University in Israel. The presence of a comorbid neurodevelopmental disorder such as attention deficit hyperactivity disorder (ADHD), a specific language impairment, or any sensory or neurological disability was an exclusion criterion. The inclusion criteria for the DD group were: (<reflink idref="bib1" id="ref112">1</reflink>) a formal diagnosis of DD by a qualified psychologist; (<reflink idref="bib2" id="ref113">2</reflink>) a score of at least one standard deviation below the average of local norms on tests of phonological decoding (nonword reading). Since there are no standardized reading tests for adults in Hebrew, the selection was based on local norms acquired from an independent sample, using similar criteria as in other studies conducted with Hebrew readers with dyslexia (Weiss, Katzir, & Bitan, [<reflink idref="bib119" id="ref114">119</reflink>]). Scores of one standard deviation below the mean of the local norms were chosen following the standard practice in the Hebrew literature (Breznitz & Misra, [<reflink idref="bib10" id="ref115">10</reflink>]; Shany & Breznitz, [<reflink idref="bib91" id="ref116">91</reflink>]); (<reflink idref="bib3" id="ref117">3</reflink>) lack of attentional problems (according to the Adult ADHD Self‐Report Scale [ASRS]; Konfortes, [<reflink idref="bib50" id="ref118">50</reflink>]). Based on these criteria, one participant with DD was excluded from the final sample. The TD group included participants who had no trouble with reading (e.g., at or above the inclusion criteria of the DD group on the nonword reading test) and were at the same level of cognitive ability as the DD group as measured by the Similarities subset of the Wechsler Adult Intelligence Scale (Wechsler, [<reflink idref="bib118" id="ref119">118</reflink>]). The Institutional Review Board at the University of Haifa approved the study, which was conducted in accordance with the Declaration of Helsinki, with written informed consent provided by all participants. Participants received compensation for their participation in the study (120 Israeli shekels, equivalent to approximately $30).</p> <hd id="AN0172347578-9">Cognitive/language batteries</hd> <p>Participants underwent a series of cognitive tests designed to evaluate their cognitive ability (Similarities subset), verbal short‐term memory (digit span test; Wechsler, [<reflink idref="bib118" id="ref120">118</reflink>]), rapid automatized naming skills (i.e., RAN tests; Breznitz & Misra, [<reflink idref="bib10" id="ref121">10</reflink>]), phonological processing (phoneme segmentation, phoneme deletion, and spoonerism), reading skills (Shatil, [[<reflink idref="bib92" id="ref122">92</reflink>]]), and attentional functions (ASRS; Konfortes, [<reflink idref="bib50" id="ref123">50</reflink>]). This examination was included to ensure that the TD and DD groups differed in reading and phonological skills but not in attention or cognitive abilities. Table 1 provides details of these tasks. The participants' performance on these tests is summarized in Table 2. Results indicate that the groups did not differ in age or cognitive abilities. However, compared to the TD group, the DD group displayed a reading disability profile compatible with the symptomatology of DD. This group differed significantly from the TD group on both rate and accuracy measures of word reading and decoding skills. Moreover, the DD group demonstrated deficits in the three key phonological domains: phonological processing (spoonerism, phoneme segmentation, phoneme deletion), verbal short‐term memory (digit span), and rapid naming (rapid automatized naming).</p> <p>1 Table Psychometric tests</p> <p> <ephtml> <table><thead><tr><th>Ability</th><th align="center">Test</th><th align="center">Description</th></tr></thead><tbody><tr><td>Intellectual ability</td><td>SimilaritiesWechsler Adult Intelligence Scale (WAIS‐III; Wechsler, <xref ref-type="bibr" rid="bibr118">1997</xref>)</td><td>In this task, participants are asked how two words are alike/similar</td></tr><tr><td>Verbal short‐term memory</td><td>Digit Span Wechsler Adult Intelligence Scale (WAIS‐III; Wechsler, <xref ref-type="bibr" rid="bibr118">1997</xref>)</td><td>In this task, participants are required to recall the numbers presented auditorily in the order they were presented by the examiner. The maximum total raw score is 28. Task administration is discontinued after failure to recall two trials with a similar number of digits. The test reliability coefficient is 0.9</td></tr><tr><td>Decoding</td><td>1‐min test of words and 1‐min test of nonwords (Shatil, <xref ref-type="bibr" rid="bibr92">1995</xref>)</td><td>These tests aim to assess reading skills. The 1‐min test of words contains nonvowelized words of an equivalent level of complexity. The 1‐min test of nonwords contains increasingly complex vowelized nonwords. Each test requires the participant to read aloud as quickly and accurately as possible within 1 min. The maximum raw score for the 1‐min test of words is 168. The maximum raw score for the 1‐min test of nonwords is 86</td></tr><tr><td>Phonological processing</td><td>Phoneme deletion(Breznitz & Misra, <xref ref-type="bibr" rid="bibr10">2003</xref>)</td><td>In this test, participants are required to repeat nonwords without a specific phoneme as rapidly as possible. The nonwords are presented auditorily and vary in complexity, with a maximum total raw score of 25</td></tr><tr><td /><td>Phoneme segmentation test(Breznitz & Misra, <xref ref-type="bibr" rid="bibr10">2003</xref>)</td><td>This measure assesses the participant's ability to break a word into its component phonemes. For example, the word fo has two phonemes /f/ /o/. The maximum raw score is 16</td></tr><tr><td /><td>Spoonerism task (developed by Peleg & Ben‐Dror)</td><td>Participants are required to switch the first syllables of two word pairs and then to synthesize the segments to provide new words. The maximum raw score is 12</td></tr><tr><td>Naming skills</td><td>Rapid automatized naming (RAN)(Breznitz & Misra, <xref ref-type="bibr" rid="bibr10">2003</xref>)</td><td>Participants are required to orally name visually presented items as rapidly as possible. The exemplars are drawn from a constant category (RAN colors, RAN categories, RAN numerals, and RAN letters). This requires retrieval of a familiar phonological code for each stimulus and coordination of phonological and visual (color) or orthographic (letter) information quickly on time. The reliability coefficient of these tests ranges from 0.98 to 0.99</td></tr><tr><td>Attention</td><td>Adult attention deficit hyperactivity disorder (ADHD) Self‐Report Scale (ASRS) measure</td><td>An 18‐item questionnaire based on the Diagnositic and Statistical Manual of Mental Disorders (DSM‐IV) criterion for identifying ADHD in adults. The questions refer to the past 6 months. The ASRS rating scale includes 0–5 rating (very often = 5 points, often = 4 points, sometimes = 3 points, rarely = 2 points, never = 1 point). A total score of more than 51 points is used to identify ADHD</td></tr></tbody></table> </ephtml> </p> <p>2 Table Demographic and psychometric data of the TD and DD groups—Experiment 1</p> <p> <ephtml> <table><thead><tr><th>Measurement</th><th align="center">TD Group <italic>M</italic> (<italic>SD</italic>)</th><th align="center">DD Group <italic>M</italic> (<italic>SD</italic>)</th><th align="center"><italic>t</italic>‐Value</th><th align="center"><italic>p</italic></th></tr></thead><tbody><tr><td>Age</td><td>24.23 (1.94)</td><td>25.21 (3.12)</td><td>−1.31</td><td>.19</td></tr><tr><td>Decoding</td><td /><td /><td /><td /></tr><tr><td>Oral words recognition (accuracy)</td><td>107.79 (15.29)</td><td>68.91 (22.76)</td><td>8.14</td><td>.00</td></tr><tr><td>Oral words recognition (speed)</td><td>108.76 (15.07)</td><td>74.52 (21.24)</td><td>7.55</td><td>.00</td></tr><tr><td>Oral nonwords recognition (accuracy)</td><td>60.58 (8.75)</td><td>26.94 (8.72)</td><td>15.63</td><td>.00</td></tr><tr><td>Oral nonwords recognition (speed)</td><td>64.97 (8.54)</td><td>42.70 (9.94)</td><td>9.75</td><td>.00</td></tr><tr><td>Naming skills</td><td /><td /><td /><td /></tr><tr><td>Naming letters</td><td>21.45 (2.85)</td><td>25.27 (4.17)</td><td>−4.33</td><td>.00</td></tr><tr><td>Naming objects</td><td>32.55 (5.56)</td><td>40.55 (7.04)</td><td>−5.12</td><td>.00</td></tr><tr><td>Naming numbers</td><td>17.33 (2.90)</td><td>21.61 (3.29)</td><td>−5.58</td><td>.00</td></tr><tr><td>Naming colors</td><td>28.27 (5.21)</td><td>32.73 (6.43)</td><td>−3.09</td><td>.00</td></tr><tr><td>Phonological processing</td><td /><td /><td /><td /></tr><tr><td>Phoneme segmentation (time)</td><td>72.82 (16.83)</td><td>123.21 (59.99)</td><td>−4.64</td><td>.00</td></tr><tr><td>Phoneme segmentation (accuracy)</td><td>15.21 (0.78)</td><td>11.94 (3.89)</td><td>4.73</td><td>.00</td></tr><tr><td>Phoneme deletion (time)</td><td>102.82 (24.38)</td><td>176.52 (42.46)</td><td>−8.64</td><td>.00</td></tr><tr><td>Phoneme deletion (accuracy)</td><td>23.58 (1.41)</td><td>18.48 (5.88)</td><td>4.83</td><td>.00</td></tr><tr><td>Spoonerism (time)</td><td>122.48 (44.18)</td><td>272.55 (110.24)</td><td>−7.25</td><td>.00</td></tr><tr><td>Spoonerism (accuracy)</td><td>18.64 (1.27)</td><td>14.03 (4.44)</td><td>5.72</td><td>.00</td></tr><tr><td>Short verbal working memory</td><td /><td /><td /><td /></tr><tr><td>Digit span</td><td>12.00 (3.06)</td><td>9.67 (2.31)</td><td>3.49</td><td>.00</td></tr><tr><td>Intellectual abilities</td><td /><td /><td /><td /></tr><tr><td>Similarities</td><td>11.73 (2.46)</td><td>11.24 (1.98)</td><td>0.88</td><td>.38</td></tr><tr><td>Attentional functions</td><td /><td /><td /><td /></tr><tr><td>ASRS</td><td>35.03 (6.13)</td><td>33.06 (9.06)</td><td>1.02</td><td>.30</td></tr></tbody></table> </ephtml> </p> <hd id="AN0172347578-10">Stimuli and design</hd> <p>The task and stimuli were all adapted from Yu and Smith ([<reflink idref="bib122" id="ref124">122</reflink>]; Experiment 1). The stimuli were slides containing pictures of uncommon objects taken from the Novel Object and Unusual Name database (Horst & Hout, [<reflink idref="bib39" id="ref125">39</reflink>]) paired with auditorily presented pseudowords. The pseudowords were recorded by a female native Hebrew speaker and contained all the Hebrew consonants and vowels. The words were based on templates characteristic of the Hebrew language, and all had the same stress pattern (<emph>milra</emph>, i.e., stress on the final syllable), which is common in Hebrew.</p> <p>Each condition included 54 unique objects and 54 unique pseudowords divided into three sets of 18 words and referents. Training trials were generated by randomly pairing each word with a picture, and the learner had to discover these word–picture pairs. In each of the three training conditions, different numbers of words and referents were presented within a learning trial. The 2 × 2 condition contained two words and two pictures (see Fig. 1a for illustration); on each trial in the 3 × 3 condition, three words and three pictures were presented; and on each trial in the 4 × 4 condition, four words and four pictures were presented. No indication was given as to which picture went with which word. Each trial began with a simultaneous visual presentation of the referents on a computer screen. Words were then presented auditorily via the computer's speakers. There was no systematic relationship between the temporal order of spoken names and the spatial location of the referents on the screen.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CGN/01sep23/cogs13325-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cogs13325-fig-0001.jpg" title="1 (a) Learning trials in a cross‐situational statistical learning (SL) task in which the learners hear two words while viewing two objects. Participants are not informed which word is mapped to which object, creating a referentially ambiguous situation, but they know that statistically there are four possible mappings. As learners encounter more and more learning situations, eventually the correct mapping that the object is called Argel will obtain the strongest association because the label, and its correct referent are likely to co‐occur more consistently than other pairs. (b) An example of a test trial in which learners are required to choose which of four objects is associated with the word. (c) Type of objects used in Experiments 1 and 2." /> </p> <p></p> <p>Individual trials in the three conditions were formed by selecting two, three, or four word‐referent pairs from the 18 pairs of word referents. Each word and each referent were presented six times in each condition, for a total of 54, 36, and 27 trials in the 2 × 2, 3 × 3, and 4 × 4 conditions, respectively. Because multiple words and referents were presented in each trial, the learner may have experienced spurious associations that make learning from these ambiguous individual trials difficult. Specifically, on average, each word co‐occurred with 5.09 incorrect referents in the 2 × 2 condition, 8.78 incorrect referents in the 3 × 3 condition, and 12.22 incorrect referents in the 4 × 4 condition. These numbers reflect within‐trial ambiguity in the three conditions. During training, the probability of the correct referent being given its name, p(a|A), was 1.0 in all conditions. In contrast, the average probability of irrelevant but co‐occurring referents was.205,.231, and.247 in the 2 × 2, 3 × 3, and 4 × 4 conditions, respectively. For example, in the 4 × 4 condition, all the spurious co‐occurrences were first counted (in each trial, and for each item, there were three nonreferents in this condition), resulting in an array of 18 cells, with the target referent co‐occurring with the word six times. Incorrect referent probability was calculated by dividing the number of nonreferent co‐occurrences by the number of target referent co‐occurrences (in this case six). This procedure was conducted for each object and averaged across all 17 incorrect items. Despite the considerable differences in within‐trial uncertainty across the conditions, the strength of the spurious correlations varied only moderately among them. Across the conditions, the number of repetitions of each unique word and referent and the total time of the training session were kept constant. Thus, the total number of trials differed across conditions, as did the duration of each trial. The order of trials within each condition was determined randomly. The order of the three conditions was counterbalanced across participants.</p> <hd id="AN0172347578-12">Procedure</hd> <p>A 14‐inch screen was used to display the visual objects to be learned. Spoken words were presented via headphones. Participants were instructed that their task is to learn words and referents, but they were not told that there was only one referent per word. They were told that multiple words and pictures would co‐occur in each trial and that their task was to figure out, across the trials, which word went with which picture. Training in each condition was followed by a four‐alternative forced‐choice test of learning. In the test, participants heard one word, were shown four pictures, and were asked to indicate which picture was associated with the word they heard (see Fig. 1b). The target picture and the three foils were all taken from the set of 18 training pictures. To assess the development of explicit and implicit knowledge, we asked participants to use a binary scale to evaluate whether they had guessed or remembered the missing object on each test trial. The experiment was controlled by MATLAB software and lasted approximately half an hour. Participants completed the experiment in two sessions. In the first session, they completed the background testing, and in the second session, they completed the CSSL task.</p> <hd id="AN0172347578-13">Analysis</hd> <p></p> <hd id="AN0172347578-14">Power analysis</hd> <p>Previous research (Yu & Smith, [<reflink idref="bib122" id="ref126">122</reflink>]) using the CSSL task employed in the present study revealed robust CSSL effects (Cohen's <emph>d</emph> = 1.425). Furthermore, in the study by Gabay et al. ([<reflink idref="bib30" id="ref127">30</reflink>]), a large effect size was observed when comparing DD and control participants on a similar but not identical SL task (partial eta squared of 0.25). Nevertheless, because no previous study used the task employed in the current study with young adults with DD, we erred on the side of caution in predicting only medium effect sizes (<emph>d</emph> = 0.5, <emph>f</emph> = 0.25, or <emph>η<subs>p</subs></emph><sups>2</sups> = 0.06) to test within‐ and between‐variables interactions (e.g., an interaction between within‐trial variability and group). A power analysis (calculated using Gpower software; Faul, Erdfelder, Lang, & Buchner, [<reflink idref="bib22" id="ref128">22</reflink>]) indicated that in order to detect within‐ and between‐group interaction effects, a total sample of 28 participants is needed to obtain statistical power at a 0.80 level with an alpha of 0.05. Therefore, the total sample of 68 participants (Experiment 1) and 55 participants (Experiment 2) provided adequate power.</p> <hd id="AN0172347578-15">Data analysis—CSSL performance</hd> <p>Learning in the CSSL task was indexed by the probability that participants would correctly choose the target picture after hearing a word during a test trial. A generalized linear mixed‐effects model was used, implemented in the lme4 package (Bates, Maechler, & Bolker, [<reflink idref="bib6" id="ref129">6</reflink>]) in R (Team, [<reflink idref="bib78" id="ref130">78</reflink>]) using a logistic linking function (Jaeger, [<reflink idref="bib42" id="ref131">42</reflink>]) to account for the binominal nature of the dependent variable. Fixed effects were ambiguity level (<reflink idref="bib2" id="ref132">2</reflink>, 3, 4), listener group (TD vs. DD), and all interactions. The random‐effects structure was composed of random intercepts for participants and items (i.e., auditory word). This was the maximal random effect structure to which the model‐fitting algorithm converged. After that, we estimated the expected marginal means and conducted a contrast analysis using the emmeans package (Lenth et al., [<reflink idref="bib55" id="ref133">55</reflink>]) to examine whether accuracy on the test was above chance level (25%), with Bonferroni correction for multiple comparisons. The purpose of this was to determine whether learning occurred in each group. All contrast analyses were carried out on the response scale using the delta method as implemented in the emmeans package.</p> <hd id="AN0172347578-16">Confidence judgments</hd> <p>Confidence judgments were measured with three scores: a guessing score, a zero‐correlation score, and a Type II d' score as in prior research (Bertels et al., [<reflink idref="bib7" id="ref134">7</reflink>]). Not all the participants contributed equally to all of three scores (see Tables 3 and 5). For example, each measurement was only calculated for participants who provided the relevant confidence response (e.g., the guessing score requires participants to indicate they were guessing on at least some of the trials). Therefore, logistic/linear mixed effects models were used.</p> <p>3 Table Number of participants included in the confidence measures analyses in Experiment 1</p> <p> <ephtml> <table><thead><tr valign="bottom"><th align="left">Measure</th><th align="center">Level</th><th align="center">Number of DD Readers</th><th align="center">Number of TD Readers</th></tr></thead><tbody><tr><td align="left">Guessing score</td><td>Level 2</td><td>12</td><td>3</td></tr><tr><td>Level 3</td><td>14</td><td>13</td></tr><tr><td>Level 4</td><td>20</td><td>23</td></tr><tr><td align="left">Zero Correlation score (A/B)</td><td>Level 2A</td><td>21</td><td>30</td></tr><tr><td>Level 2B</td><td>14</td><td>6</td></tr><tr><td>Level 3A</td><td>13</td><td>30</td></tr><tr><td>Level 3B</td><td>13</td><td>10</td></tr><tr><td>Level 4A</td><td>23</td><td>30</td></tr><tr><td>Level 4B</td><td>13</td><td>12</td></tr><tr><td align="left">Type II d'</td><td>Level 2</td><td>22</td><td>16</td></tr><tr><td>Level 3</td><td>27</td><td>22</td></tr><tr><td>Level 4</td><td>20</td><td>30</td></tr></tbody></table> </ephtml> </p> <hd id="AN0172347578-17">Guessing score to assess implicit knowledge</hd> <p>We first examined whether CSSL occurred above chance on trials in which participants stated that they were guessing. Guessing score was calculated as follows: <ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0001" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>G</mi><mi>u</mi><mi>e</mi><mi>s</mi><mi>s</mi><mi>i</mi><mi>n</mi><mi>g</mi><mspace width="0.33em" /><mi>S</mi><mi>c</mi><mi>o</mi><mi>r</mi><mi>e</mi><mo linebreak="badbreak">=</mo><mfrac><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>guessing</mi></mrow></mrow><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>guessing</mi></mrow><mo>+</mo><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>WR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>guessing</mi></mrow></mrow></mfrac></mrow><annotation encoding="application/x-tex">$$\begin{equation*}Guessing\ Score = \frac{{{\mathrm{no}}.{\mathrm{\ of\ CR\ while\ guessing}}}}{{{\mathrm{no}}.{\mathrm{\ of\ CR\ while\ guessing}} + {\mathrm{no}}.{\mathrm{\ of\ WR\ while\ guessing}}}}\end{equation*}$$</annotation></semantics></math> </ephtml></p> <p>If participants are not completely aware of the knowledge used to make a choice, they are expected to perform better when they state they are guessing than when they state they know. Therefore, a guessing score above chance (0.25) indicates that participants developed implicit knowledge. We first examined whether estimated group scores differed from chance (= 0.25). All contrast analyses were carried out on the response scale using the delta method as implemented in the emmeans package. The guessing scores were then entered into a mixed effect logistic regression model, with level (<reflink idref="bib2" id="ref135">2</reflink>, 3, 4), group, and their interaction as fixed effects, and random intercepts for each participant, to determine whether the two groups differed in the guessing score as a function of level.</p> <hd id="AN0172347578-18">Zero correlation score to assess explicit knowledge</hd> <p>Participants who are at least partly aware of the information they used in the task are expected to be more confident about their correct choices than about their incorrect choices. The zero correlation scores were calculated as follows[<reflink idref="bib1" id="ref136">1</reflink>]: <ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0002" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>Z</mi><mi>e</mi><mi>r</mi><mi>o</mi><mspace width="0.33em" /><mi>c</mi><mi>o</mi><mi>r</mi><mi>r</mi><mi>e</mi><mi>l</mi><mi>a</mi><mi>t</mi><mi>i</mi><mi>o</mi><mi>n</mi><mspace width="0.33em" /><mi>s</mi><mi>c</mi><mi>o</mi><mi>r</mi><mi>e</mi><mspace width="0.33em" /><mi>A</mi><mo linebreak="badbreak">=</mo><mfrac><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow></mrow><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow><mo>+</mo><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>guessing</mi></mrow></mrow></mfrac></mrow><annotation encoding="application/x-tex">$$\begin{equation*}Zero\ correlation\ score\ A = \frac{{{\mathrm{no}}.{\mathrm{\ of\ CR\ while\ knowing}}}}{{{\mathrm{no}}.{\mathrm{\ of\ CR\ while\ knowing}} + {\mathrm{no}}.{\mathrm{\ of\ CR\ while\ guessing}}}}\end{equation*}$$</annotation></semantics></math> </ephtml><ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0003" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>Z</mi><mi>e</mi><mi>r</mi><mi>o</mi><mspace width="0.33em" /><mi>c</mi><mi>o</mi><mi>r</mi><mi>r</mi><mi>e</mi><mi>l</mi><mi>a</mi><mi>t</mi><mi>i</mi><mi>o</mi><mi>n</mi><mspace width="0.33em" /><mi>s</mi><mi>c</mi><mi>o</mi><mi>r</mi><mi>e</mi><mspace width="0.33em" /><mi>B</mi><mo linebreak="badbreak">=</mo><mfrac><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>WR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow></mrow><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>WR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow><mo>+</mo><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>WR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>guessing</mi></mrow></mrow></mfrac></mrow><annotation encoding="application/x-tex">$$\begin{equation*}Zero\ correlation\ score\ B = \frac{{{\mathrm{no}}.{\mathrm{\ of\ WR\ while\ knowing}}}}{{{\mathrm{no}}.{\mathrm{\ of\ WR\ while\ knowing}} + {\mathrm{no}}.{\mathrm{\ of\ WR\ while\ guessing}}}}\end{equation*}$$</annotation></semantics></math> </ephtml></p> <p>If participants performed better when they stated that they knew (Zero A) than when they stated that they were guessing (Zero B), the result could be taken as an indication that participants developed explicit knowledge. To test this, a linear mixed effect regression model was used, with zero‐correlation type (Zero A vs. Zero B), level (<reflink idref="bib2" id="ref137">2</reflink>, 3, 4), and group, and their interactions as fixed effects and random intercepts for each participant. Here, we were interested only in the main effects or interactions involving the zero‐correlation type.</p> <hd id="AN0172347578-19">Type II d' to assess participants' awareness of their own performance</hd> <p>The Type II d' score was calculated as follows: <ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0004" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>H</mi><mi>I</mi><mi>T</mi><mo linebreak="badbreak">=</mo><mfrac><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>CR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow></mrow><mrow><mi>Total</mi><mspace width="0.33em" /><mi>CR</mi></mrow></mfrac></mrow><annotation encoding="application/x-tex">$$\begin{equation*}HIT = \frac{{{\mathrm{no}}.{\mathrm{\ of\ CR\ while\ knowing}}}}{{{\mathrm{Total\ CR}}}}\end{equation*}$$</annotation></semantics></math> </ephtml><ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0005" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi><mi>a</mi><mi>l</mi><mi>s</mi><mi>e</mi><mspace width="0.33em" /><mi>A</mi><mi>l</mi><mi>a</mi><mi>r</mi><mi>m</mi><mo linebreak="badbreak">=</mo><mfrac><mrow><mi>no</mi><mo>.</mo><mrow><mspace width="0.33em" /><mi>of</mi><mspace width="0.33em" /><mi>WR</mi><mspace width="0.33em" /><mi>while</mi><mspace width="0.33em" /><mi>knowing</mi></mrow></mrow><mrow><mi>Total</mi><mspace width="0.33em" /><mi>WR</mi></mrow></mfrac></mrow><annotation encoding="application/x-tex">$$\begin{equation*}False\ Alarm = \frac{{{\mathrm{no}}.{\mathrm{\ of\ WR\ while\ knowing}}}}{{{\mathrm{Total\ WR}}}}\end{equation*}$$</annotation></semantics></math> </ephtml><ephtml> <math display="block" altimg="urn:x-wiley:03640213:media:cogs13325:cogs13325-math-0006" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mrow><mi>Type</mi><mspace width="0.33em" /><mi>II</mi><mspace width="0.33em" /><msup><mi mathvariant="normal">d</mi><mo>′</mo></msup><mspace width="0.33em" /><mi>score</mi></mrow><mo linebreak="badbreak">=</mo><mi mathvariant="bold">Z</mi><mfenced open="(" close=")"><mi mathvariant="bold">HIT</mi></mfenced><mo linebreak="goodbreak">−</mo><mi mathvariant="bold">Z</mi><mfenced open="(" close=")"><mi mathvariant="bold">FA</mi></mfenced></mrow><annotation encoding="application/x-tex">$$\begin{equation*}{\mathrm{Type\ II\ d^{\prime}\ score}} = {{\bf Z}}\left({{{\bf HIT}}} \right)-{{\bf Z}}\left({{{\bf FA}}} \right)\end{equation*}$$</annotation></semantics></math> </ephtml></p> <p>Explicit knowledge should consistently result in Type II d' values greater than zero and implicit knowledge should result in Type II d' values close to zero. Thus, a Type II d' score that differs from zero indicates the development of explicit knowledge. We first examined whether the estimated Type II d' scores for each group differed from zero using emmneas in R. These scores were then entered into a linear mixed effect regression model, with level (<reflink idref="bib2" id="ref138">2</reflink>, 3, 4), group, and their interaction as fixed effects, and random intercepts for each participant, to determine whether the two groups differed in their Type II d' scores. Here, we were interested only in the main effects or interactions involving the Type II d' scores.</p> <hd id="AN0172347578-20">Results and discussion</hd> <p></p> <hd id="AN0172347578-21">CSSL performance</hd> <p>The results (see Fig. 2a) showed a significant effect of level [χ2 (<reflink idref="bib2" id="ref139">2</reflink>) = 88.65, <emph>p</emph> <.001], such that the probability of success decreased as a function of level as shown by a linear contrast [z = −9.38, <emph>p</emph> <.001]. There was also a significant effect of group [χ2 (<reflink idref="bib1" id="ref140">1</reflink>) = 23.45, <emph>p</emph> <.001], such that the performance of the DD group (<emph>p</emph> =.72) was significantly poorer than that of the TD group (<emph>p</emph> =.91). The two‐way interaction of level and listener group was not significant [χ2 (<reflink idref="bib2" id="ref141">2</reflink>) = 1.82, <emph>p</emph> =.404]. Emmeans contrasts indicated that both the DD and TD groups exhibited CSSL above the level of chance (25%; all Bonferroni adjusted <emph>p</emph>s <.0001).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CGN/01sep23/cogs13325-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cogs13325-fig-0002.jpg" title="2 Proportion of correct responses on the cross‐situational SL task in Experiment 1 (a) and Experiment 2 (b) as a function of level (referential ambiguity) and group (typically developed [TD] vs. developmental dyslexia [DD]). Note. Error bar represents one standard error." /> </p> <p></p> <hd id="AN0172347578-23">Binary confidence judgments</hd> <p></p> <hd id="AN0172347578-24">Guessing score</hd> <p>The guessing score (see Fig. 3a) differed significantly from chance (25%) for both the TD and the DD groups (both Bonferroni adjusted <emph>p</emph>s <.0009). This pattern points to the development of implicit knowledge. Mixed effects model analysis indicated a significant difference in the guessing score across the two groups [χ2 (<reflink idref="bib1" id="ref142">1</reflink>) = 6.146, <emph>p</emph> =.013], such that the DD group (<emph>p</emph> =.37) exhibited a guessing score lower than that of the TD group (<emph>p</emph> =.56). There was also a significant main effect of level [χ2 (<reflink idref="bib2" id="ref143">2</reflink>) = 7.61, <emph>p</emph> =.02], such that the guessing score decreased as referential ambiguity increased based on a linear contrast [<emph>z</emph> = −2.841, <emph>p</emph> =.004]. None of the remaining effects were significant.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CGN/01sep23/cogs13325-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cogs13325-fig-0003.jpg" title="3 Guessing scores in Experiment 1 (a) and Experiment 2 (b) as a function of level (referential ambiguity) and group (TD vs. DD).Note. Error bar represents one standard error." /> </p> <p></p> <hd id="AN0172347578-26">Zero correlation score</hd> <p>Only main effects or interaction with zero score type are reported. A mixed effects model revealed a significant main effect of zero type score [χ2 (<reflink idref="bib1" id="ref144">1</reflink>) = 48.62, <emph>p</emph> <.0001], with better performance on the CSSL task when participants stated that they knew [p(ZeroA) =.83] than when they stated they were guessing [<emph>p</emph>(ZeroB) =.39], indicating the development of explicit knowledge (see Fig. 4a). None of the other effects were significant.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CGN/01sep23/cogs13325-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cogs13325-fig-0004.jpg" title="4 Zero correlation scores in Experiment 1 (a) and Experiment 2 (b) as a function of level (referential ambiguity) and group (TD vs. DD).Note. Error bar represents one standard error." /> </p> <p></p> <hd id="AN0172347578-28">Type II d' score</hd> <p>The Type II d' scores of the TD and DD groups differed significantly from zero (both Bonferroni adjusted <emph>p</emph>s <.0001), pointing to the development of explicit knowledge (see Fig. 5a). Mixed model analysis did not reveal any main effects or interactions when the Type II d' scores of the two groups were compared as a function of referential ambiguity (all <emph>p</emph> >.11).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/CGN/01sep23/cogs13325-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="cogs13325-fig-0005.jpg" title="5 Type II d' scores in Experiment 1 (a) and Experiment 2 (b) as a function of level (referential ambiguity) and group (TD vs. DD).Note. Error bar represents one standard error." /> </p> <p></p> <p>The results of Experiment 1 show that both DD and TD participants can use statistical information to learn new words as indicated by their above chance CSSL performance. Yet people with DD do this less effectively than TD participants, regardless of the level of referential ambiguity. Analysis of the confidence ratings revealed that both groups developed explicit and implicit knowledge about word‐referent pairs, yet implicit knowledge was developed to a greater extent in the TD group than in the DD group. When they believed they were guessing, TD participants were more likely to perform better on the CSSL task than DD participants.</p> <hd id="AN0172347578-30">Experiment 2</hd> <p>In the second experiment, we aimed to determine whether CSSL impairments in DD under conditions that mimic learning in native‐language situations (association between novel phonological words and novel objects) also extend to second‐language‐like situations (association between novel word labels and pre‐existing word semantic relations). Unlike Experiment 1, in this experiment, we used familiar objects as referents. As language acquisition difficulties in DD are not limited to native language (Di Betta & Romani, [<reflink idref="bib15" id="ref145">15</reflink>]; Schneider, [<reflink idref="bib89" id="ref146">89</reflink>]; Sparks et al., [<reflink idref="bib99" id="ref147">99</reflink>]), we predicted that the performance of the DD group would be impaired relative to that of TD participants even when the references are highly familiar objects.</p> <hd id="AN0172347578-31">Methods</hd> <p></p> <hd id="AN0172347578-32">Participants</hd> <ulist> <item>31 TD vs. 22 DD participants (51 of them had also participated in Experiment 1) were participated in the Experiment 2. The inclusion and exclusion criteria were similar to those of Experiment 1. Participants' performance on the cognitive/linguistic tests is summarized in Table 4.</item> <item>4 Table Demographic and psychometric data of the DD and TD groups—Experiment 2</item> </ulist> <p> <ephtml> <table><thead><tr><th>Measurement</th><th align="center">TD Group <italic>M</italic> (<italic>SD</italic>)</th><th align="center">DD group <italic>M</italic> (<italic>SD</italic>)</th><th align="center"><italic>t</italic>‐Value</th><th align="center"><italic>p</italic></th></tr></thead><tbody><tr><td>Age</td><td>24.23 (1.92)</td><td>25.33 (3.21)</td><td>−1.40</td><td>.17</td></tr><tr><td>Decoding</td><td /><td /><td /><td /></tr><tr><td>Oral words recognition (accuracy)</td><td>111.32 (16.95)</td><td>68.59 (25.36)</td><td>7.35</td><td>.00</td></tr><tr><td>Oral words recognition (speed)</td><td>112.35 (16.76)</td><td>74.09 (23.35)</td><td>6.95</td><td>.00</td></tr><tr><td>Oral nonwords recognition (accuracy)</td><td>62.26 (9.59)</td><td>27.95 ()7.90</td><td>13.76</td><td>.00</td></tr><tr><td>Oral nonwords recognition (speed)</td><td>66.06 (9.35)</td><td>42.32 (10.51)</td><td>8.65</td><td>.00</td></tr><tr><td>Naming skills</td><td /><td /><td /><td /></tr><tr><td>Naming letters</td><td>21.26 (2.95)</td><td>26.00 (4.61)</td><td>−4.55</td><td>.00</td></tr><tr><td>Naming objects</td><td>32.74 (5.42)</td><td>41.45 (7.51)</td><td>−4.90</td><td>.00</td></tr><tr><td>Naming numbers</td><td>17.42 (2.94)</td><td>22.41 (3.14)</td><td>−5.91</td><td>.00</td></tr><tr><td>Naming colors</td><td>27.87 (5.20)</td><td>33.41 (6.85)</td><td>−3.34</td><td>.00</td></tr><tr><td>Phonological processing</td><td /><td /><td /><td /></tr><tr><td>Phoneme segmentation (time)</td><td>72.68 (16.39)</td><td>107.41 (31.97)</td><td>−5.17</td><td>.00</td></tr><tr><td>Phoneme segmentation (accuracy)</td><td>15.26 (0.77)</td><td>12.14 (4.03)</td><td>4.12</td><td>.00</td></tr><tr><td>Phoneme deletion (time)</td><td>99.35 (20.01)</td><td>173.36 (41.58)</td><td>−8.62</td><td>.00</td></tr><tr><td>Phoneme deletion (accuracy)</td><td>23.81 (0.98)</td><td>17.64 (6.71)</td><td>5.06</td><td>.00</td></tr><tr><td>Spoonerism (time)</td><td>122.32 (45.62)</td><td>260.23 (125.12)</td><td>−5.64</td><td>.00</td></tr><tr><td>Spoonerism (accuracy)</td><td>18.68 (1.27)</td><td>14.05 (4.81)</td><td>5.12</td><td>.00</td></tr><tr><td>Short verbal working memory</td><td /><td /><td /><td /></tr><tr><td>Digit span</td><td>12.10 (2.98)</td><td>9.23 (2.42)</td><td>3.72</td><td>.00</td></tr><tr><td>Intellectual abilities</td><td /><td /><td /><td /></tr><tr><td>Similarities</td><td>11.77 (2.52)</td><td>11.32 (2.21)</td><td>0.68</td><td>.49</td></tr><tr><td>Attentional functions</td><td /><td /><td /><td /></tr><tr><td>ASRS</td><td>35.35 (5.90)</td><td>34.19 (9.61)</td><td>0.54</td><td>.59</td></tr></tbody></table> </ephtml> </p> <hd id="AN0172347578-33">Stimuli and design</hd> <p>The stimuli and design resembled Experiment 1, except that the to‐be‐learned referents were known objects. The names of the everyday objects used were lexical items from five semantic categories (vehicles, animals, foods, clothes, and objects in daily use) that are acquired early in language acquisition. The objects used as stimuli were color photos presented on a white background. The pictures were taken from the Picture Naming Test employed by Lieberman and Borovsky ([<reflink idref="bib56" id="ref148">56</reflink>]). These pictures were rated at a high level of familiarity.</p> <hd id="AN0172347578-34">Procedure</hd> <p>The procedure was similar to that used in Experiment 1. Most participants completed Experiment 2 approximately five to six months after completing Experiment 1. The rest of the participants completed only the second experiment.</p> <hd id="AN0172347578-35">Approach to analysis</hd> <p>The statistical analyses were identical to those conducted in Experiment 1. Table 5 represents the number of participants included in the confidence measure analyses. In addition, we also conducted a cross‐experiment comparison, entering the experiment as a variable in all analyses to compare learning performance in the first‐ and second‐language learning situations. Using the data from the two experiments, we also conducted within‐subject analyses to examine the potential correlations between the confidence measures and between CSSL performance and confidence measures.</p> <p>5 Table Number of participants included in the confidence measures analyses of Experiment 2</p> <p> <ephtml> <table><thead><tr><th align="left">Measure</th><th align="center">Level</th><th align="center">Number of DD Readers</th><th align="center">Number of TD Reader</th></tr></thead><tbody><tr><td align="left">Guessing score</td><td>Level 2</td><td>2</td><td>0</td></tr><tr><td>Level 3</td><td>12</td><td>6</td></tr><tr><td>Level 4</td><td>12</td><td>10</td></tr><tr><td align="left">Zero Correlation score (A/B)</td><td>Level 2A</td><td>32</td><td>34</td></tr><tr><td>Level 2B</td><td>19</td><td>6</td></tr><tr><td>Level 3A</td><td>33</td><td>21</td></tr><tr><td>Level 3B</td><td>13</td><td>18</td></tr><tr><td>Level 4A</td><td>20</td><td>31</td></tr><tr><td>Level 4B</td><td>21</td><td>27</td></tr><tr><td align="left">Type II d'</td><td>Level 2</td><td>19</td><td>8</td></tr><tr><td>Level 3</td><td>21</td><td>16</td></tr><tr><td>Level 4</td><td>20</td><td>24</td></tr></tbody></table> </ephtml> </p> <hd id="AN0172347578-36">Results and discussion</hd> <p></p> <hd id="AN0172347578-37">Experiment 2—Familiar referents</hd> <p>CSSL performance: The results (see Fig. 2b) showed a significant effect of level [χ2 (<reflink idref="bib2" id="ref149">2</reflink>) = 46.72, <emph>p</emph> <.001], such that the probability of success decreased as a function of level, as revealed by a linear contrast [z = −9.38, <emph>p</emph> <.001]. There was also a significant effect of listener group [χ2 (<reflink idref="bib1" id="ref150">1</reflink>) = 16.89, <emph>p</emph> <.001], such that the probability of success in the DD group (<emph>p</emph> =.71) was smaller than in the TD group (<emph>p</emph> =.92). The important finding of a two‐way interaction between level and listener group [χ2 (<reflink idref="bib2" id="ref151">2</reflink>) = 8.73, <emph>p</emph> =.013] suggests that group differences varied as a function of referential ambiguity. As shown in Fig. 2b, the group differences in CSSL performance appear to be larger for the highest level of referential ambiguity. Emmeans contrasts indicated that both the DD and the TD groups exhibited CSSL at a level above chance (25%; both Bonferroni adjusted <emph>p</emph>s <.0001).</p> <hd id="AN0172347578-38">Binary confidence judgments</hd> <p></p> <hd id="AN0172347578-39">Guessing score</hd> <p>The guessing score (see Fig. 3b) differed significantly from chance (25%) for both the TD and the DD groups (both Bonferroni adjusted <emph>p</emph>s <.03). This pattern points to the development of implicit knowledge. Mixed effects model analysis indicated a significant difference in guessing scores between the two groups [χ2 (<reflink idref="bib2" id="ref152">2</reflink>) = 6.618, <emph>p</emph> =.011], such that the DD group (<emph>p</emph> =.47) exhibited a lower guessing score than the TD group (<emph>p</emph> =.81). None of the remaining effects were significant.</p> <hd id="AN0172347578-40">Zero correlation score</hd> <p>Only main effects or interactions with zero type score were reported. A mixed effects model revealed a significant main effect of zero type score [χ2 (<reflink idref="bib1" id="ref153">1</reflink>) = 33.25, <emph>p</emph> <.0001], with better performance on the CSSL task when participants stated that they knew [<emph>p</emph>(ZeroA) =.78] than when they stated they were guessing [<emph>p</emph>(ZeroB) =.41]. There was also a significant three‐way interaction of group, zero type score, and level [χ2 (<reflink idref="bib2" id="ref154">2</reflink>) = 7.42, <emph>p</emph> =.02] and a subsequent linear contrast [z = 2.72, <emph>p</emph> =.0065] suggests that participants in the TD group performed better on the CSSL task when they stated they knew than when they stated they were guessing (see Fig. 4b). This difference was most pronounced when referential ambiguity was increased. In the DD group, however, this pattern was most pronounced when referential ambiguity decreased.</p> <hd id="AN0172347578-41">Type II d'</hd> <p>The Type II d' scores of the TD group [<emph>d'</emph> =.85] and of the DD group [<emph>d</emph>' =.74] differed significantly from zero (both Bonferroni adjusted <emph>p</emph>s <.0002), suggesting the development of explicit knowledge (see Fig. 5b). Mixed model analysis did not reveal any main effects or interaction with Type II d' scores when the two groups were compared as a function of referential ambiguity (all <emph>p ></emph>.11).</p> <hd id="AN0172347578-42">Cross‐experiment comparison</hd> <p>CSSL performance: When comparing across experiments, the main effect of level [χ2 (<reflink idref="bib2" id="ref155">2</reflink>) = 132.44, <emph>p</emph> <.001] and the main effect of group [χ2 (<reflink idref="bib1" id="ref156">1</reflink>) = 38.99, <emph>p</emph> <.001] were both significant. A two‐way interaction of level by condition [χ2 (<reflink idref="bib2" id="ref157">2</reflink>) = 7.44, <emph>p</emph> =.02] also emerged. Further analysis revealed that performance was differentially modulated by level across the two experiments as revealed by a quadratic contrast (<emph>z</emph> = −2.40, <emph>p</emph> =.001). The two‐way interaction of group by level was significant [χ2 (<reflink idref="bib2" id="ref158">2</reflink>) = 6.84, <emph>p</emph> =.032], representing a critical finding. Further analysis revealed that performance decreased as referential ambiguity increased to a greater extent in the DD group than in the TD group as revealed by a linear contrast (<emph>z</emph> = −2.65, <emph>p</emph> =.008). The three‐level interaction of group, level, and experiment failed to reach significance [χ2 (<reflink idref="bib2" id="ref159">2</reflink>) = 5.42, <emph>p</emph> =.06].</p> <hd id="AN0172347578-43">Binary confidence measures</hd> <p></p> <hd id="AN0172347578-44">Guessing score</hd> <p>Both groups exhibited guessing scores above chance level (all <emph>p</emph> <.001). A mixed effects model revealed a significant main effect of group [χ2 (<reflink idref="bib1" id="ref160">1</reflink>) = 12.5, <emph>p</emph> =.004], with the DD group exhibiting a reduced guessing score (<emph>p</emph> =.42) than among TD readers (<emph>p</emph> =.69). There was also a significant main effect of level [χ2 (<reflink idref="bib2" id="ref161">2</reflink>) = 12.42, <emph>p</emph> =.002], such that the guessing score decreased as referential ambiguity increased as revealed by a significant linear contrast [z = −.4.38, <emph>p</emph> <.001]. Finally, there was also a significant main effect of experiment [χ2 (<reflink idref="bib1" id="ref162">1</reflink>) = 4.73, <emph>p</emph> =.029], such that the guessing score was higher in Experiment 2 (<emph>p</emph> =.64) than in Experiment 1 (<emph>p</emph> =.47). None of the remaining effects were significant.</p> <hd id="AN0172347578-45">Zero correlation score</hd> <p>Only main effects or interactions with zero score type were reported. A mixed effects model revealed a significant main effect of zero type score [χ2 (<reflink idref="bib1" id="ref163">1</reflink>) = 72.16, <emph>p</emph> <.0001], with better performance on the CSSL task when participants stated that they knew [<emph>p</emph>(ZeroA) =.81] than when they stated they were guessing [<emph>p</emph>(ZeroB) =.42]. The significant three‐way interaction of group, zero type score, and level [χ2 (<reflink idref="bib2" id="ref164">2</reflink>) = 8.736, <emph>p</emph> =.012] and the following linear contrast [z = 7.852, <emph>p</emph> =.004] suggest that participants in the TD group performed better on the CSSL task when they stated that they knew than when they stated they were guessing. This difference was most pronounced when referential ambiguity was increased. However, in the DD group, this pattern was most pronounced when referential ambiguity decreased.</p> <hd id="AN0172347578-46">Type II d' score</hd> <p>There were no significant main effects or interactions.</p> <hd id="AN0172347578-47">Correlations between confidence measures</hd> <p>There were no correlations between the guessing and zero correlation scores in either the DD or the TD groups. There was a negative correlation between Type II d' and guessing score in both the DD (<emph>r</emph> = −.56, <emph>p</emph> <.001) and TD (<emph>r</emph> = −.46, <emph>p</emph> <.001) groups. Furthermore, Type II d' score correlated positively with the zero‐correlation score (A vs. B) for both the DD (<emph>r</emph> =.94, <emph>p</emph> <.001) and the TD (<emph>r</emph> =.94, <emph>p</emph> <.001) groups.</p> <hd id="AN0172347578-48">Correlations between CSSL performance and confidence measures</hd> <p>CSSL performance was positively correlated with the development of implicit knowledge (guessing score) in both the DD (<emph>r</emph> =.81, <emph>p</emph> <.001) and the TD groups (<emph>r</emph> =.81, <emph>p</emph> =.001). Note that CSSL performance was positively correlated with participants' awareness of their own performance (Type II d' score) in the DD group (<emph>r</emph> =.35, <emph>p</emph> =.017), but not in the TD group (<emph>r</emph> =.05, <emph>p</emph> =.75). CSSL performance was not significantly correlated with the zero‐correlation score in either group (all <emph>p</emph> >.05).</p> <p>Like the results observed in Experiment 1, the results of Experiment 2 show that both DD and TD participants can use statistical information to learn new words as indicated by their above chance CSSL performance. Nevertheless, the DD group performed poorly, compared to the TD group. Furthermore, the performance of DD participants was negatively influenced by increases in referential ambiguity to a greater extent than was the performance of the TD group. As within‐trial reference uncertainty increased, the group differences became more noticeable, providing evidence that the ability to learn statistical regularities is fundamentally affected in DD. Indeed, manipulation of the statistical structure significantly influenced task performance among people with DD. As in Experiment 1, here too the analysis of the confidence ratings revealed that both groups developed explicit and implicit knowledge about word‐referent pairs, yet implicit knowledge was developed to a greater extent in the TD group than in the DD group.</p> <hd id="AN0172347578-49">General discussion</hd> <p>In this study, we examined the ability of young adults with DD and TD readers to tabulate statistical information across situations in order to discover word‐referent mappings. Compared to TD readers, young adults with DD exhibited poorer performance on CSSL tasks. As a group, participants with DD performed above chance level on the CSSL tasks in both experiments. Although people with DD were capable of exhibiting CSSL more than expected by chance, they did so less efficiently than TD readers in both experiments. Manipulating the referential ambiguity affected the performance of the DD group to a greater extent than among TD learners across experiments. Furthermore, the impairment was evident in both native (novel objects) and second (familiar objects) language‐like situations.</p> <p>Offering participants the opportunity to rate their judgments enabled us to assess the development of explicit (conscious) and implicit (unconscious) knowledge during CSSL. We observed that CSSL across the two experiments was accompanied by the development of implicit knowledge (based on guessing scores) and explicit knowledge (based on the zero‐correlation criterion and the Type II d' scores) in both the DD and the TD groups. The guessing criterion score was significantly higher in the TD group than in the DD group, indicating less development of implicit knowledge, compared to TD readers across experiments. In contrast, no group differences were observed regarding zero correlation/Type II d' scores, pointing to a similar development of explicit knowledge across the two groups. It should be noted that most participants completed Experiment 2 approximately 5 to 6 months after completing Experiment 1. This raises the possibility of practice effects or may suggest more development of explicit knowledge in Experiment 2 than in Experiment 1. If these factors contributed to task performance, they should influence both groups in a similar manner. Furthermore, CSSL performance in Experiment 2 was not better than in Experiment 1, and the guessing score across groups was higher in Experiment 2 than in Experiment 1, indicating greater development of implicit knowledge in Experiment 2. It is possible that word‐referent associations are more easily formed when referents are familiar and are therefore less subject to conscious control than associations involving novel referents.</p> <p>Taken together, these findings are consistent with prior research revealing the involvement of both implicit and explicit knowledge in CSSL (Franco et al., [<reflink idref="bib24" id="ref165">24</reflink>]; Hamrick et al., [<reflink idref="bib33" id="ref166">33</reflink>]). They serve as the first demonstration of differences in acquired knowledge between DD and TD readers in the context of language‐related SL using subjective measures of awareness. People with DD develop less implicit knowledge when confronted with SL challenges than do TD readers, whereas their development of explicit knowledge is similar to that of TD readers and is positively correlated with their CSSL performance. These findings resonate with recent evidence revealing slower shifting and less efficient use of implicit strategies alongside intact use of explicit strategies in those with DD when learning to categorize stimuli from complex auditory category distributions (Gabay, Roark, & Holt, [<reflink idref="bib28" id="ref167">28</reflink>]). This converging evidence supports the view that learning via the implicit/procedural memory system is disrupted in DD (Nicolson & Fawcett, [<reflink idref="bib66" id="ref168">66</reflink>]; Ullman & Pullman, [<reflink idref="bib110" id="ref169">110</reflink>]).</p> <p>The current findings suggest that people with DD have impaired CSSL. Several hypotheses can be proposed regarding the locus of the deficit. The CSSL task includes a visual component, a linguistic component, and statistical information aggregation/hypothesis testing components. Impairments in any one of these processes can contribute to CSSL impairments in DD. The observation that people with DD were impaired in CSSL both when visual referents were novel and with familiar objects reduces the possibility that problems in visual aspects contribute to the observed group differences. As the perception of familiar and novel objects is likely to involve different perceptual processes (holistic vs. configural; Noudoost, Adibi, Moeeny, & Esteky, [<reflink idref="bib69" id="ref170">69</reflink>]), the finding of a similar SL impairment in DD across familiar and novel objects suggests that the visuo‐perceptual difficulties noted in DD (Gabay, Dundas, Plaut, & Behrmann, [<reflink idref="bib26" id="ref171">26</reflink>]) are not the source of the group differences. On the other hand, the linguistic component may potentially give rise to the observed group differences. People with DD have trouble processing phonological information, for example, when they are asked to discriminate between minimal word pairs that differ in phonetic contrast (Mohammed, Campbell, Macsweeney, Barry, & Coleman, [<reflink idref="bib64" id="ref172">64</reflink>]). A problem discriminating between these sounds makes it more difficult to map them to visual referents. The observation that participants with DD exhibited CSSL performance above chance reduces this possibility. We also consider this possibility less likely as in the present study, listeners heard highly phonologically distinct pseudowords as opposed to phonologically less distinct pseudowords that constitute a perceptually difficult learning challenge (see Escudero et al., [<reflink idref="bib21" id="ref173">21</reflink>]). A third possibility is that people with DD have trouble with statistical information aggregation or explicit hypothesis testing, thus affecting their CSSL performance. Research suggests that CSSL can be accomplished via explicit hypothesis testing (Trueswell, Medina, Hafri, & Gleitman, [<reflink idref="bib106" id="ref174">106</reflink>]) or/and implicit associative learning mechanisms (Dautriche & Chemla, [<reflink idref="bib13" id="ref175">13</reflink>]; Yu & Smith, [<reflink idref="bib122" id="ref176">122</reflink>]). The second possibility is more aligned with procedural memory functions that are presumed to be affected in DD (Nicolson & Fawcett, [<reflink idref="bib67" id="ref177">67</reflink>]; Ullman et al., [<reflink idref="bib109" id="ref178">109</reflink>]). Procedural memory functions are acquired incrementally via multiple exposures (Knowlton & Moody, [<reflink idref="bib49" id="ref179">49</reflink>]), similar to how object–word pairings are acquired by an associative account of CSSL. Consistent with this notion is the observation that people with amnesia who cannot acquire explicit knowledge (Schacter et al., [<reflink idref="bib86" id="ref180">86</reflink>]) show intact CSSL (Warren, Roembke, Covington, McMurray, & Duff, [<reflink idref="bib117" id="ref181">117</reflink>]). An impaired ability to learn statistical regularities in DD is supported by the observation that performance plummeted for the DD group when the SL challenge was greater. This pattern is in line with a meta‐analysis concluding that implicit SL impairments in DD are most pronounced when SL challenges increase (Lum et al., [<reflink idref="bib57" id="ref182">57</reflink>]). Furthermore, the observation that individuals with DD were less likely to develop implicit knowledge than were TD readers while their ability to develop explicit knowledge was similar implies that impaired implicit associative learning in DD contributed to the observed group differences. As language acquisition greatly relies on the ability to implicitly learn statistical regularities, an impaired implicit associative learning may negatively influence their ability to acquire language‐related skills. The observation that the DD group continued to exhibit impaired CSSL relative to the TD group does not exclude the possibility of reliance on explicit memory as compensation for impaired implicit associative learning. It is possible that learning words cross‐situationally is better when implicit rather than explicit mechanisms come into play. Namely, it may be easier to learn such statistical regularities by implicit statistical aggregation across situations than by employing explicit mechanisms (actively searching for regularities) as has been shown for other types of SL phenomena (Reber, [<reflink idref="bib79" id="ref183">79</reflink>], [<reflink idref="bib80" id="ref184">80</reflink>]). Indeed, CSSL performance in the present study was positively correlated with the development of implicit knowledge in both groups, such that the more participants exhibited implicit knowledge, the better their CSSL performance. Note that only in the DD group, CSSL performance positively correlated with the participants' awareness of their own performance (Type II d' scores). These findings support the notion that individuals with DD are more likely to rely on explicit/declarative memory when learning statistical regularities, possibly due to a dysfunctional procedural memory system (Nicolson & Fawcett, [<reflink idref="bib67" id="ref185">67</reflink>]; Ullman et al., [<reflink idref="bib109" id="ref186">109</reflink>]).</p> <p>Taken together, the findings of the current study are consistent with previous evidence suggesting that the ability to extract statistical information embedded in the environment is impaired in people with DD. People with DD are less able to extract syllables from fluent speech (Gabay et al., [<reflink idref="bib30" id="ref187">30</reflink>]), track distributional information to discover sound categories (Gabay & Holt, [<reflink idref="bib27" id="ref188">27</reflink>]; Gabay et al., [<reflink idref="bib28" id="ref189">28</reflink>]), or use probabilistic information in the context of incremental learning of cue–outcome associations (Gabay, [<reflink idref="bib25" id="ref190">25</reflink>]; Gabay et al., [<reflink idref="bib31" id="ref191">31</reflink>]; Massarwe, Nissan, & Gabay, [<reflink idref="bib58" id="ref192">58</reflink>]). The current findings broaden these earlier investigations by showing that SL difficulties in DD are not limited to syllable or sound linguistic levels but are also evident in other fundamental language learning challenges, such as the ability to map words to novel/familiar objects in the environment. Our investigation suggests that these impairments are present in both native‐ and second‐language‐like situations, consistent with native‐ and second‐language acquisition difficulties reported in DD (Di Betta & Romani, [<reflink idref="bib15" id="ref193">15</reflink>]; Schneider, [<reflink idref="bib89" id="ref194">89</reflink>]; Sparks et al., [<reflink idref="bib99" id="ref195">99</reflink>]). The observed findings raise the possibility that the smaller vocabulary observed in people with DD may arise not only from reduced exposure to written language, as previously suggested (Duff, Tomblin, & Catts, [<reflink idref="bib19" id="ref196">19</reflink>]), but also from a reduced ability to rely on SL mechanisms that support the pairing of sounds to objects in real‐world environments in which uncertainty and ambiguity are common. Since spoken vocabulary growth and phonemic awareness are likely to interact (Walley, Metsala, & Garlock, [<reflink idref="bib116" id="ref197">116</reflink>]), the reduced spoken vocabulary developed through SL processes may affect speech and reading‐related skills in people with DD. Furthermore, it is also possible that learning the association between spoken sounds and their visual objects can affect reading via its impact on phonetic category acquisition. For example, if a learner has difficulty deciding a priori whether vowel categories /ae/ and /E/ (that overlap in the acoustic space) belong to one or two categories, their presentation in two different word contexts (i.e., "b[ae]t" and "[E]gg") could help differentiate them (Fourtassi, [<reflink idref="bib23" id="ref198">23</reflink>]). In this way, visual information can function as a teaching signal for phonetic category learning when it is consistently aligned with statistically structured acoustic input (McMurray, [[<reflink idref="bib61" id="ref199">61</reflink>]]). Indeed, evidence suggests that pairing objects and sounds influences the phonetic sensitivity of 9‐month‐old infants (Yeung & Werker, [<reflink idref="bib120" id="ref200">120</reflink>]) and that word‐referent associations affect speech segmentation (Cunillera et al., [<reflink idref="bib12" id="ref201">12</reflink>]). In this sense, CSSL has the potential to contribute to learning to read via its influence on phonetic category acquisition.</p> <p>To conclude, across two experiments, we observed that the performance of people with DD was significantly poorer than that of TD readers and that they were less likely to develop implicit knowledge. These findings suggest that SL deficits in DD are likely to extend beyond the sound and syllable levels to the word level and are likely to arise due to impaired associative learning, thus negatively affecting the language development of people with DD.</p> <hd id="AN0172347578-50">Data Availability Statement</hd> <p>The data and materials are publicly available via the Open Science Framework at https://osf.io/kmtqy. 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  Data: Reduced Implicit but Not Explicit Knowledge of Cross-Situational Statistical Learning in Developmental Dyslexia
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kligler%2C+Nitzan%22">Kligler, Nitzan</searchLink><br /><searchLink fieldCode="AR" term="%22Yu%2C+Chen%22">Yu, Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Gabay%2C+Yafit%22">Gabay, Yafit</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Cognitive+Science%22"><i>Cognitive Science</i></searchLink>. Sep 2023 47(9).
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 30
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Institutes of Health (NIH) (DHHS)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: R01HD093792
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Dyslexia%22">Dyslexia</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Acquisition%22">Language Acquisition</searchLink><br /><searchLink fieldCode="DE" term="%22Vocabulary+Development%22">Vocabulary Development</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Processes%22">Learning Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Pictorial+Stimuli%22">Pictorial Stimuli</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+Communication%22">Speech Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Novelty+%28Stimulus+Dimension%29%22">Novelty (Stimulus Dimension)</searchLink><br /><searchLink fieldCode="DE" term="%22Familiarity%22">Familiarity</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Adults%22">Young Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+Perception%22">Visual Perception</searchLink><br /><searchLink fieldCode="DE" term="%22Auditory+Perception%22">Auditory Perception</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+Level%22">Knowledge Level</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/cogs.13325
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0364-0213<br />1551-6709
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Although statistical learning (SL) has been studied extensively in developmental dyslexia (DD), less attention has been paid to other fundamental challenges in language acquisition, such as cross-situational word learning. Such investigation is important for determining whether and how SL processes are affected in DD at the word level. In this study, typically developed (TD) adults and young adults with DD were exposed to a set of trials that contained multiple spoken words and multiple pictures of individual objects, with no information about word-referent correspondences provided within a trial. Nonetheless, cross-trial statistical relations could be exploited to learn word-referent mappings. The degree of within-trial reference uncertainty and the novelty of to-be-learned objects (novel or familiar) were varied under different learning conditions. The results show that across all conditions, young adults with DD were significantly impaired in their ability to exploit cross-trial regularities in co-occurring visual-auditory streams to discover word-referent mappings. Observed impairments were most pronounced when within-trial reference uncertainty was the highest. Subjective measures of knowledge awareness revealed greater development of implicit but not explicit knowledge in the TD group than in the DD group. Together, these findings suggest that the SL deficit in DD affects fundamental language learning challenges at the word level and points to greater reliance on explicit processes due to impaired implicit associative learning among individuals with DD. Such a deficit is likely to influence spoken language acquisition, and in turn affect literacy skills, in people with DD.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1393996
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1393996
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/cogs.13325
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 30
    Subjects:
      – SubjectFull: Dyslexia
        Type: general
      – SubjectFull: Language Acquisition
        Type: general
      – SubjectFull: Vocabulary Development
        Type: general
      – SubjectFull: Learning Processes
        Type: general
      – SubjectFull: Adults
        Type: general
      – SubjectFull: Pictorial Stimuli
        Type: general
      – SubjectFull: Speech Communication
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Novelty (Stimulus Dimension)
        Type: general
      – SubjectFull: Familiarity
        Type: general
      – SubjectFull: Young Adults
        Type: general
      – SubjectFull: Visual Perception
        Type: general
      – SubjectFull: Auditory Perception
        Type: general
      – SubjectFull: Knowledge Level
        Type: general
    Titles:
      – TitleFull: Reduced Implicit but Not Explicit Knowledge of Cross-Situational Statistical Learning in Developmental Dyslexia
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kligler, Nitzan
      – PersonEntity:
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            NameFull: Yu, Chen
      – PersonEntity:
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            NameFull: Gabay, Yafit
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      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0364-0213
            – Type: issn-electronic
              Value: 1551-6709
          Numbering:
            – Type: volume
              Value: 47
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Cognitive Science
              Type: main
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