JCPSLP Vol 22 No 1 2020

Journal of Clinical Practice in Speech-Language Pathology Journal of Clinical ractic i Spe ch-L l

Volume 13 , Number 1 2011 Volume 22 , Number 1 2020

Expanding possibilities: Foci on reading and interdisciplinary practices

In this issue:

Statistical Learning and Reading



Oral vocabulary and reading comprehension

Graphemic Buffer Impairment in Aphasia

Research within Health in Queensland

The Value of Allied Health Assistants

Speech-language pathology in the Northern Territory Speech-language pathology assessment in diagnostic evaluation of ASD Health and wellbeing outcomes after returning to work /study following acquired brain injury

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Expanding possibilities: Foci on reading and interdisciplinary practices

From the editor Leigha Dark


1 From the editor 3 An introduction to research on statistical learning and reading – Joanne Arciuli 10 Oral vocabulary and reading comprehension: What intervention studies have taught us – Danielle Colenbrander 15 An overlooked cause of writing impairment in people with aphasia: Characteristics, assessment and treatment of graphemic buffer impairment – Trudy Krajenbrink, Saskia Kohnen, and Lyndsey Nickels 22 Developing a prioritised agenda to drive speech-language pathology: Research within Health in Queensland – Emma Finch, Elizabeth C. Ward, Linda Worrall, Kirstine Shrubsole, Bena Brown, Petrea Cornwell, Anne E. Hill, Annie J. Hill, Tania Hobson, Tanya Rose, Ashley Cameron, and Nerina Scarinci 29 What value can allied health assistants bring to speech-language pathology practice? – Rachael O’Brien, Rebecca Mitchell and Nicole Byrne 34 Speech-language pathology in the Northern Territory: Shifting the focus from individual clinicians to intercultural, interdisciplinary team work – Bea Staley, Emily Armstrong, Rebecca Amery, Anne Lowell, Tanya Wright, Caroline Jones, Louise Taylor, and Jessica Hodson 40 Speech-language pathology assessment: Key to diagnostic evaluation of ASD in 4–7 year-olds with average cognition – Kate Broome and Vanessa Sarkozy 48 An exploratory prospective study of the association between return to work/study and health and well-being outcomes after acquired brain injury – Emma J. Schneider, Kate Lawlor, Ester Roberts, Kelly McMahon, Lauren Solomon, Nicole Austin, and Natasha L. Lannin 53 Speech-language pathology in Australian residential aged-care facilities – Skye A. Sewell and Suzanne C. Hopf 62 What’s the evidence? Interdisciplinary

W elcome to this mid-year issue of JCPSLP. The events of the first half of this year must be acknowledged as being unusual, unexpected and challenging on a global scale. We’ve seen adaptations, accommodations, limitations, and restrictions. But we’ve also seen transformations, innovations, new conversations and connections. In the spirit of adapting and innovating in a rapidly changing landscape, we bring you a combined issue with contributions aligned with the March 2020 theme “A focus on reading” and the July 2020 theme “Interdisciplinary research and practice”. The unifying idea of “Expanding possibilities” is fitting in these times as we look to new ways of delivering services and partnering with individuals, families and communities. We hope you find something new and inspiring to challenge you and take forward into your practice. Before outlining the inclusions for this issue, I would like to take the opportunity to sincerely thank Jae-Hyun Kim for his contributions to the journal during his term as editor. Addressing themes including “The role of speech pathologists in the justice system”, “Measurement and evaluation in practice” and “Multimodal communication”, Jae along with the authors and editorial team have curated high quality and thought-provoking issues. This is Jae’s final issue and it has been a pleasure collaborating to bring it to fruition. I look forward to continuing in the role of interim editor until March 2021 and supporting the transition of the next editor into the role. We commence this issue with submissions that explore a focus on reading. Joanne Arciuli provides a thorough, comprehensive and accessible introduction to the research on statistical reading and learning. Danielle Colenbrander follows with an article exploring what we can learn from intervention studies in the areas of oral vocabulary and reading comprehension. Trudy Krajenbrink, Saskia Kohnen, and Lyndsey Nickels consider an overlooked cause of writing impairment in people with aphasia – graphemic buffer impairment – and describe characteristics, assessment and management approaches. Facilitating the transition from a focus on reading to interdisciplinary collaboration in research and practice, Emma Finch and colleagues outline the process of developing a prioritised agenda to drive speech-language pathology practice, showcasing research occurring within Queensland Health. In the next article Rachael O’Brien, Rebecca Mitchell, and Nicole Byrne share the findings of a literature review that addresses the question: What value can allied health assistants bring to speech- language pathology practice? Focusing on the role, training, and collaborative activities of allied health assistants and speech pathologists, a balanced, narrative review of existing literature is presented. Continuing with the theme of interdisciplinary collaboration, Bea Staley and colleagues discuss three examples of speech-language pathology service provision in the Northern Territory,

service provision in community-based services for children with disabilities – Stephanie Weir

67 Resource review 69 Top 10 literacy tips and resources – Jenny Baker 71 Top 10 tips for inter-disciplinary

collaboration between speech pathologists and educators – Haley Tancredi and Jaedene Glasby


JCPSLP Volume 22, Number 1 2020

inviting us to reflect on the shift of focus from individual clinicians to intercultural, interdisciplinary teamwork. In their article, Kate Broome and Vanessa Sarkozy explore the contribution of speech-language pathology assessment within the context of a multidisciplinary team, to the timely and accurate diagnosis of autism spectrum disorder in 4–7-year-old children with average cognition. Impact on efficiency of service provision is explored and a new model of service provision proposed. In the penultimate article, Emma Schneider and colleagues share the outcomes of an exploratory prospective study on the association between return to work/study and health and well-being outcomes after acquired brain injury. And finally, Skye Sewell and Suzanne Hopf round out the included articles with a review of speech-language pathology service provision within Australian residential aged-care facilities. In this issue, we’ve included a selection of the regular columns, supplementing both themes on reading and interdisciplinary practice. In “What’s the evidence?” Stephanie Weir explores the evidence on the topic of interdisciplinary service provision in community-based services for children with disabilities. Three “Resource reviews” offer critique of diverse, contemporary resources

including the ABC website, and new texts on qualitative research and paediatric traumatic brain injury. In our two “Top 10” columns, Jenny Baker, shares her “go to” resources to support work in the areas of language and literacy, while Helen Tancredi and Jaedene Glasby outline resources that support their interdisciplinary collaboration within education settings. We are always keen to hear from you, the readership, as to your ideas for the journal. If you are interested in contributing to the journal by way of peer reviewing an article submission, critiquing a journal article for “Around the journals”, sharing your “Top 10” resources for your work context, or exploring different perspective on a theme through the “Viewpoints” column, please contact the editor at or the publications team at As always, we would like to extend sincere thanks to the authors who choose to share their work in JCPSLP, and the fabulous editorial committee and publication team without whom the issues would not come together. Take care, stay well, look after each other, and we look forward to bringing you another full issue in November, with the theme “Learning from our clients”.

Betty Conway, Near Tempe Downs, My Country © Betty Nungarrayi Conway/Copyright Agency, 2020

Invitation & call for papers

Speech Pathology Australia’s 2021 Conference Planning Committee invites you to the 2021 National Conference from 30 May–2 June in Darwin. The theme Local Contexts, Global Practice was selected to support speech pathologists' thinking and talking about their local work contexts as well as the broader global practices we may engage in. We hope participants will use this time together to consider how the profession might move towards culturally safe and evidence-based practices that promote multiculturalism, multilingualism, equitable service provision and communication rights locally and globally. In your submission we ask you to consider your work, as it relates to the theme, and the aspirations outlined in Speech Pathology Australia 2030: • communication accessible communities • access for all • timely services across the lifespan • clients and communities driving service delivery • skilled and confident families and carers • collaborative professional partnerships • quality services, innovation and continual pursuit of knowledge

diverse and dynamic workforce. We invite you to join us in Darwin to share, engage, showcase, challenge, problem-solve, create, look to the future and innovate around speech pathology practices locally and globally. While the rest of Australia is getting chilly, our weather is guaranteed to be perfect with clear evening skies and warm days. We look forward to seeing you there!

Abstract submission available at Wednesday 3 June 2020


Closing date for submission of papers, workshops and posters Tuesday 15 September 2020


Authors notified of successful papers, workshops and posters Monday 14 December 2020



JCPSLP Volume 22, Number 1 2020

Journal of Clinical Practice in Speech-Language Pathology

Expanding possibilities: Foci on reading and interdisciplinary practices

An introduction to research on statistical learning and reading Joanne Arciuli

Statistical learning (SL) is a form of implicit learning. It is thought that SL plays a role in a range of mental activities including reading. There are several different bodies of evidence to consider when thinking about the link between statistical learning and reading. These include corpus analyses, behavioural studies, and computational modelling which have provided converging evidence that the reading of single words and nonwords appears to proceed via principles of SL. In addition, there have been group comparisons investigating whether individuals with and without dyslexia differ in their capacity for SL. There have also been studies of whether individual differences in the capacity for SL relate to variability in reading ability in the general population. Lastly, some researchers have begun to consider principles of SL when designing classroom- based and other activities for beginning readers to see if this facilitates learning. Although there is ongoing discussion and debate regarding the nature of SL and the extent of its contribution to reading, clinicians may find it valuable to know about SL and the range of methodologies being utilised in this field of research. This invited paper summarises key points from the narrative review by Arciuli (2018) with discussion of additional studies. A guide to statistical learning and reading ability Children must learn to read. In an alphabetic language such as English, learning to read often begins with explicit instruction in the home environment and at preschool (e.g., to encourage children to recognise and reproduce the letters comprising their name). Once children start to tackle the reading aloud of a variety of individual words, they will likely be receiving formal instruction regarding regularities. Some of these regularities pertain to how letters map onto sounds (e.g., k maps onto /k/ as in kitten ) and how adjacent letters are combined within written words (e.g., ck

also maps onto /k/ as in kick ). They may also be instructed to attend to some regularities that pertain to non-adjacent letters within written words (e.g., vowels in certain consonant frames change when combined with a silent e: mat vs mate ). These are just some examples of the kinds of regularities that are taught via explicit instruction. Over time, as children are exposed to a greater amount of text, it is thought that other regularities will be learned implicitly. For example, a recent study by Steacy et al. (2019) provided insight into regularities concerning context dependent vowel pronunciation during children’s reading aloud of English monosyllables. Additional studies and reviews of regularities in the context of reading and spelling include Chetail (2017), Pacton, Fayol, and Perruchet (2005); Pacton, Perruchet, Fayol, and Cleeremans (2001), Senechal, Gingras, and L’Heureux (2016), and Treiman (2018), among others. As discussed in more detail below, large-scale corpus analyses have revealed regularities in the way letters are combined within written words and how these combinations relate to patterns of lexical stress in a number of alphabetic languages including English. To illustrate, Arciuli and Cupples (2006) reported an extensive list of these kinds of regularities (e.g., the majority of disyllabic words ending in -an have first syllable stress while the majority of disyllabic words ending in -uct have second syllable stress). It is not possible for educators and clinicians to convey all of these kinds of regularities to children explicitly. Most of us, children and adults alike, do not have conscious awareness of these regularities. Lesser known regularities that are not taught explicitly In languages such as English, lexical stress is critical for meaning. This is the case during comprehension of spoken words but also during reading. Take for example a word like zebra . In English, this word has first syllable stress. Second syllable stress turns it into a nonsense word and renders it meaningless. Some early research indicated that there might be orthographic cues to placement of lexical stress in the final part of English words (e.g., Kelly, Morris, & Verrekia, 1998; Smith, Baker, & Groat, 1982; Zevin & Joanisse, 2000) but there was no large-scale corpus analysis showing the extent of these cues. Arciuli and Cupples (2006) analysed more than 7,000 disyllabic words from the CELEX database (Baayen, Pippenbrock, & Gulikers, 1993). Their results revealed clear evidence that certain letter sequences in words’ endings are probabilistically associated with certain



Joanne Arciuli


JCPSLP Volume 22, Number 1 2020

Given the abovementioned studies have revealed rich sources of regularities, and sensitivity to these cues in humans and connectionist computational models, it is interesting to consider whether SL might help us to understand why some children struggle to learn to read. Of course, it is well established that a number of factors can affect children’s progress when learning to read. It is unlikely that dyslexic individuals lack any capacity for SL whatsoever and unlikely that atypical SL would be found to be the overarching feature of dyslexia given what we already know about this disorder. However, we might ask whether SL plays some kind of role in atypical reading development. Group comparisons of SL in dyslexic versus non-dyslexic individuals Decades of research suggests that phonological processing difficulties play a significant role in dyslexia (e.g., Vellutino, Fletcher, Snowling, & Scanlon, 2004). However, difficulties in other areas could also contribute to dyslexia (e.g., Gathercole, Alloway, Willis, & Adams, 2006; Nicolson, Fawcett, Brookes, & Needle, 2010; Wolf & Bowers, 1999, among others). SL might be one of these other areas of difficulty. In its broadest sense, SL refers to the ability to detect regularities and is linked with implicit learning, procedural learning, motor learning, sequence learning (adjacent and non-adjacent dependencies), and serial order learning. Current theorising suggests that SL is an ability that emerges from multiple sub abilities (e.g., Arciuli, 2017; Reber, 2013; Sawi & Rueckl, 2019; Thiessen, Kronstein, & Hufnagle, 2013), although it does appear to be separable from what we know as “intelligence” (e.g., Conway, Baurnschmidt, Huang, & Pisoni, 2010; Kaufman et al., 2010; Kidd, 2012; Kidd & Arciuli, 2016; Siegelman & Frost, 2015; Tong, Leung, & Tong, 2019; Torkildsen, Arciuli, & Wie, et al., 2019). As explained by Arciuli and Conway (2018), there is no single agreed upon way to measure SL. Rather, there are a number of tasks that have been used to explore SL including the triplet task (Saffran, Aslin, & Newport, 1996), artificial grammar learning (Reber, 1967), the serial reaction time task (Nissen & Bullemer, 1987), and the Hebb repetition task (Hebb, 1961), among others. It is not clear whether each of these tasks draws on the same sub abilities thought to comprise SL. Those interested in a fuller explanation of each of these tasks and accompanying graphical depictions are referred to Arciuli and Conway (2018). As well as differences across tasks, each of these tasks can be altered in a myriad of ways (e.g., participant instructions, modality of presentation, presentation times, complexity of the regularities, number of times participants are exposed to the regularities, etc.). In addition, dependent variables from these tasks differ greatly (e.g., some measure learning as it is happening, some measure learning immediately after it has taken place, some dependent variables rely on motor processes or explicit judgements, etc.). Thus, different tasks, task alterations, and a multitude of dependent variables may draw on the underlying sub abilities of SL in different ways. A meta-analysis of studies using serial reaction time tasks by Lum, Ullman and Conti-Ramsden (2013) concluded that dyslexic individuals exhibit impaired SL relative to non-dyslexic individuals, although there was heterogeneity in effect sizes across studies and some studies showed no statistically significant group differences. There was evidence that the link between SL and dyslexia is affected by age with smaller effects reported in studies of adult participants.

patterns of lexical stress in English. Following Kelly’s (2004) suggestion that words’ beginnings might also hold cues to lexical stress, Arciuli and Cupples (2007) conducted a large- scale corpus analysis of CELEX and identified additional probabilistic orthographic cues to lexical stress. Subsequent cross-linguistic research has revealed pervasive probabilistic orthographic cues to stress in the initial and final parts of polysyllabic words in large-scale corpus analyses of Italian, Greek, Dutch, Spanish, and German as well as English (Monaghan, Arciuli & Ševa, 2016). Behavioural and electrophysiological studies have demonstrated participants’ sensitivity to these kinds of probabilistic orthographic cues (e.g., see studies of English Italian, Greek and Russian by Arciuli and Cupples [2006]; Arciuli and Cupples [2007]; Arciuli and Paul [2012]; Burani and Arduino [2004]; Grimini and Protopapas [2016]; Jouravlev and Lupker [2014]; Jouravlev and Lupker [2015]; Sulpizio and Colombo [2017], among others). As an aside, such probabilistic orthographic cues are also related to grammatical category membership (e.g., noun vs verb) in English disyllables (Arciuli & Cupples, 2006) and English trisyllables (Arciuli & Monaghan, 2009). Behavioural and neuroimaging studies show that people are sensitive to these cues (e.g., Arciuli, McMahon, & de Zubicaray, 2012; Kemp, Nisson, & Arciuli, 2009). The developmental study by Arciuli, Monaghan, and Ševa (2010) utilised a triangulation of methods to investigate probabilistic orthographic cues to lexical stress: corpus analysis of children’s reading materials, behavioural testing of 5–12 year olds to determine sensitivity to these cues at different ages, and computational modelling to explore incremental and implicit learning of these cues following exposure to age-appropriate input. Corpus analyses of disyllabic words in the Educator’s Word Frequency Guide database (Zeno, Ivens, Millard, & Duvvuri, 1995) examined 2959 words in reading materials for 5–6 year olds, 3814 words in materials for 7–8 year olds, 4430 words in materials for 9–10 year olds, and 4594 words in materials for 11–12 year olds. Results confirmed the presence of probabilistic orthographic cues to lexical stress in children’s reading materials. Nonwords were created to test children’s sensitivity to these cues at different ages. Behavioural results demonstrated that sensitivity to these probabilistic orthographic cues to lexical stress increases with age, presumably due to more exposure to text. A computational model, which advanced earlier modelling work on adult data by Ševa, Monaghan and Arciuli (2009), utilised a single route connectionist architecture based on the principles of SL and closely simulated the child data. A study by Mousikou, Sadat, Lucas, and Rastle (2017) compared three computational models: the rule-based algorithm by Rastle and Coltheart (2000), the connectionist CDP++ model by Perry, Ziegler, and Zorzi (2010), and the connectionist model by Ševa et al. (2009). The two connectionist models outperformed the rule-based model in simulating adult human data on assignment of lexical stress “thus providing support for a statistical-learning approach” (p. 188). Other studies have focused on different kinds of lesser known regularities, unrelated to lexical stress. As mentioned, Steacy et al. (2019) investigated regularities in context dependent vowel pronunciation in English monosyllables and showed that children were sensitive to these regularities when reading aloud. Those interested in related research are referred to Treiman (2018), Senechal et al. (2016) and Pacton et al. (2005).


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Journal of Clinical Practice in Speech-Language Pathology

Witteloostuijn, Boersma, Wijnen, and Rispens (2017) reached a similar conclusion about age-related effects in their meta-analysis of artificial grammar learning studies but also raised questions about publication bias favouring the reporting of statistically significant group differences. In line with a view of SL as a property emerging from multiple sub abilities, individuals within the dyslexic population may differ in the efficiency of particular components that underpin SL. This complicates matters substantially. For instance, while Henderson and Warmington (2017) found that English-speaking adults with dyslexia performed similarly to a control group on a serial reaction time task, this was not the case when it came to performance on the Hebb repetition task. The way that artificial grammar learning tasks are administered can affect results in these kinds of comparisons across dyslexic and non-dyslexic individuals (e.g., the study of children by Schiff, Katan, Sasson, and Kahta [2017]; the study of adults by Schiff, Sasson, Star, and Kahta [2017]; and the study of adults by Kahta and Schiff [2019]). Likewise, W. He and Tong (2017) showed that the number of times Chinese children with dyslexia were exposed to regularities affected SL performance as measured by a serial reaction time task. A move away from only examining group comparisons towards inclusion of an individual differences approach may be fruitful in discovering the extent to which SL contributes to variability in reading in dyslexic and non-dyslexic individuals (e.g., Gabay, Thiessen, & Holt, 2015). In a departure from previous studies, Kleij, Groen, Segers, and Verhoeven (2019) examined SL in dyslexic and non-dyslexic individuals longitudinally from grade 5 to grade 6, and in the context of response to intervention for dyslexic children. Their study of 74 Dutch children with dyslexia and 39 typically developing peers showed that although there were no statistically significant group differences in the capacity for sequential SL (as measured by a serial reaction time task) or spatial SL (as measured by a spatial contextual cueing task), sequential SL predicted reading ability in both groups. Moreover, during a literacy intervention, dyslexic children who exhibited faster learning on the sequential SL task tended to show greater improvement in pseudoword reading. A recent study of Chinese by Tong and colleagues (2019) included 35 children with dyslexia and 37 children without dyslexia. A triplet task was used to measure visual SL. Their results, like Kleij et al.’s (2019), revealed a relationship between the capacity for SL and reading ability in Chinese in an analysis that included both groups of children. Unlike Kleij et al. they also found statistically significant group differences with dyslexic children showing poorer SL. In considering these different findings across SL studies – some indicating a link between dyslexia and poorer SL ability while others show no such link – it is worth considering methodological differences across studies with regard to participant-related variables, task-related variables, and language-related variables. The next section discusses studies of individual differences in SL in the general population. Individual differences in SL One of the first studies of whether individual differences in the capacity for SL relate to variability in reading proficiency in the general population was conducted by Arciuli and Simpson (2012) who utilised a visual SL task created earlier by Arciuli and Simpson (2011). The SL task is a version of the classic triplet paradigm originally devised to examine infants’ ability to learn aurally presented sequences of syllables (Saffran et al., 1996). Following adaptations of the triplet task using visually presented stimuli in adult studies (e.g.,

Brady & Oliva, 2008; Fiser & Aslin, 2002; Turk-Browne, Jungé, & Scholl, 2005), Arciuli and Simpson (2011) created a child-friendly task of SL using unfamiliar cartoon-like characters described as aliens. It is important that the characters are unfamiliar and cannot be described by a pre-existing label (i.e., in the way a picture of a chair is inescapably linked with the label chair ) or easily distinguished by a single feature (e.g., a green alien versus a blue alien). This allows us to ascertain learning of novel stimuli. This type of SL task usually has a familiarisation phase, which may include a cover task, followed immediately by a surprise test phase. In the task developed by Arciuli and Simpson (2011) participants are provided with a back- story that explains the purpose of the (cover) task at the beginning of the familiarisation phase. They are told that they will be playing a game where aliens from different planets are queuing to enter a spaceship – their task is to detect when two aliens from the same planet appear together (i.e., one after the other) by pressing a button on the keyboard as quickly as possible. This task is an example of a very common children’s card game played in many parts of the world ( Snap_(card_game)). Not all SL tasks include a cover task but a compelling back-story conceals the aim of learning while also encouraging children to attend to the visual stimuli during familiarisation. As described in several published studies that have used this task, 12 individual stimuli (i.e., the aliens) are grouped into four base triplets (ABC, DEF, GHI, JKL). Each base triplet is presented 24 times during familiarisation. For 6 of the 24 instances, one alien is presented twice in a row (constituting the cover task which simulates the card game commonly known as “snap”). The repetitions are counterbalanced among the aliens within the triplet so that there are no cues to triplet boundaries (e.g., for triplet ABC there are instances of AABC, ABBC, ABCC). Following Turk-Browne et al. (2005) triplet order is randomised after the following constraints – no repeated triplets (i.e., no instances of ABCABC) and no repeated pairs of triplets (e.g., ABCDEFABCDEF). In the surprise test phase, the learning of the base triplets is assessed via forced choice trials where base triplets are pitted against foil triplets. Aliens in the foil triplets never appeared together in sequence in the familiarisation phase (AEI, DHL, GKC, JBF). It is important to use a substantial number of trials as this impacts task reliability. In the task created by Arciuli and Simpson (2011; 2012) the number of test-trials is 64. For every test trial, participants are asked to identify which of the two triplets had appeared previously during familiarisation by verbal indication (the verbal indication reduces cognitive load on children to remember which button on the keyboard to press). There are no time limits on responding. The dependent variable reflecting learning of triplets is an accuracy measure: percent correct score for the 64 trials. Arciuli and Simpson (2012) used this visual SL task alongside a standardised test of word reading accuracy (WRAT-4; Wilkinson & Robertson, 2006) and reported a modest but significant relationship between individuals’ capacity for SL and reading proficiency in 38 children and in 37 adults. A regression analysis of combined child and adult data showed that SL was a predictor of reading ability after accounting for age and attention (i.e., correct hits during the cover task). Torkildsen et al. (2019) used exactly the same SL task in their study of Norwegian children, with instructions translated from English to Norwegian. The Norwegian version of the TOWRE was used as the


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standardised test of word reading (Rashotte, Torgerson, & Wagner, 1999). In an advance on Arciuli and Simpson (2012), they examined whether SL made a unique contribution in explaining variation in reading ability after taking into account a much larger range of variables known to be related to reading. Another advance included a power analysis justifying their sample size ( n = 65). Results showed a modest but significant relationship between children’s capacity for SL and their reading ability. A regression analysis showed that SL was a predictor of reading ability after accounting for a number of additional variables. Qi et al. (2019) developed two new SL tasks, an auditory and a visual version of the classic triplet task. These tasks included a novel measure of SL tied to response times during the cover task of oddball detection as well as accuracy measures derived from a surprise test phase. Results from 36 children and 36 adults showed that auditory SL rather than visual SL was related to sentence reading fluency after a number of variables were taken into account (Woodcock Johnson III; Woodcock, McGrew, & Mather, 2001). This result was observed in response time data rather than accuracy data. Additional analyses of the child data showed that the relationship between SL and nonword reading (WRMT; Woodcock, 1998) was mediated by phonological processing abilities. Another individual differences study used an SL task modelled after the triplet paradigm, but different to Arciuli and Simpson’s task, to examine 27 English-speaking adults and their L2 literacy acquisition in Hebrew (Frost, Armstrong, Siegelman, & Christiansen, 2013). Results revealed a relationship between the capacity for SL and reading proficiency. A neuroimaging study by Yu et al. (2019) used the same SL task reported by Frost, Siegelman, Narkiss, and Afek. (2013) in their investigation of adult readers of Chinese: 12 native readers and 12 non-native readers. Results revealed a link between SL and both L1 and L2 literacy acquisition, albeit in different reading networks of the brain. As an aside, in addition to studies of individual differences that compare performance on independent tests of SL and reading, there is research showing that SL plays a role in learning to read Chinese (He, W., & Tong, 2017; Yin & McBride, 2015; 2018). Some other studies have not found a link between independent tests of SL and reading ability. Nigro, Jiménez- Fernández, Simpson, and Defior (2015) used a novel visual SL task to examine 28 Spanish-speaking children. They did not find a link between SL and reading ability. They hypothesised that there may be a weaker link between the capacity for SL and variability in reading proficiency in a shallow orthography such as Spanish. However, they also emphasised low statistical power in their study. See also Schmalz, Moll, Mulatti, and Schulte-Korne (2019) who examined the link between SL and reading in 84 German- speaking adults using two novel visual SL tasks: a serial reaction time task and an artificial grammar learning task. Results reported no relationship between performance on these SL tasks and reading ability in German. In line with renewed interest in psychometric properties of psychological measures (e.g., Hedge, Powell, & Sumner, 2017), the reliability of SL tests has become a point of consideration (e.g., Siegelman et al., 2018; Kalra, Gabrieli, & Finn, 2019). Some recent studies have reported reliability. For example, internal consistency has been reported for some of the SL tasks mentioned in this narrative review (Torkildsen et al. [2019] reported Cronbach’s alpha of 0.81; Tong et al. [2019] reported Cronbach’s alpha of 0.56; Qi et al. [2019] reported Cronbach’s alpha ranging from 0.71 to 0.89; Kleij

et al. [2019] reported split half reliability ranging from 0.57 to 0.70). A separate study not discussed here has shown a 32 test-trial version of the Arciuli and Simpson task (2011; 2012) when administered to children has test-retest reliability of 0.57 after cover task performance is taken into account (Kidd, Smithson, Christiansen, & Arciuli, 2019). The body of research examining the link between individual differences in SL and individual differences in reading ability in the general population is growing. Researchers are paying increased attention to task reliability. Researchers are also creating new ways to measure SL in studies of reading (e.g., see the recent study by Siegelman et al. [2020] and the recent study by Snell and Theeuwes [2020]). Literacy instruction that draws on implicit learning techniques This body of research has emerged more recently than the others reviewed here. Some studies have demonstrated the efficacy of incidental learning procedures on broader reading and spelling outcomes (e.g., Protopapas et al., 2017; Tamura, Castles, & Nation, 2017). Other studies have begun to explore for the utility of manipulating the written input provided to the learner using an SL-informed approach. Far from replacing explicit instruction these approaches could supplement explicit instruction. Apfelbaum, Hazeltine, and McMurray (2013) drew on the principles of SL to facilitate literacy acquisition in a classroom setting. Their study of 224 English-speaking first graders was designed to determine whether children could learn implicitly about some regularities concerning graphemes to phoneme correspondences via exposure to words in computer tasks (e.g., vowel learning such as a in bat , i in bit , o in bot, ai in bait , ea in beat , and oa in boat ). Children were assigned to one of two groups where consonant frames were either variable or similar in the learning tasks. Children were given multiple attempts and feedback about accuracy but were not given any instruction regarding specific regularities. Results showed that children were capable of learning these regularities implicitly. Interestingly, variable consonant frames led to greater learning. Following Apfelbaum et al. (2013), Adwan- Mansour and Bitan (2017) found that variability facilitates adults’ learning of a novel script ( n = 60). They suggested that perhaps “variability reduces the effectiveness of whole word recognition and instead increases the salience of regularities, thus enhancing the extraction of letter-sound correspondences” (p. 2849). Most of the studies mentioned in this section on instructional techniques have been conducted with typically developing children and adults. It would be valuable to involve children with developmental disabilities who are struggling with literacy acquisition to ascertain whether gains can be made via these SL-informed approaches which parallel innovations in practices that support oral language acquisition (e.g., Alt, Meyers, & Ancharski, 2012; Alt, Meyers, Oglivie, Nicholas, & Arizmendi, 2014; Plante et al., 2014; Torkildsen et al., 2013). Conclusion For some languages it is not possible to explicitly teach all of the regularities between sounds and letters, and the regularities present within written words, that children need to acquire to become proficient readers. This is not to say that explicit instruction is unimportant. In fact, the opposite is true – explicit instruction is vital when children are learning


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to read. However, it is thought that implicit processes also a play a role, especially when it comes to deep orthographies such as English. SL might be one of these implicit processes and has been investigated in several different bodies of research in relation to reading. It is hoped that this brief overview will be of benefit to clinicians interested in finding out more about SL and reading. Acknowledgements The writing of this manuscript was partially supported by a SOAR fellowship granted to Joanne Arciuli by The University of Sydney. References Adwan-Mansour, J., & Bitan, T. (2017). The effect of stimulus variability on learning and generalization of reading in a novel script. Journal of Speech, Language, and Hearing Research , 60 , 2840–2851. JSLHR-L-16-0293 Alt, M., Meyers, C., & Ancharski, A. (2012). Using principles of learning to inform language therapy design for children with specific language impairment. International Journal of Language and Communication Disorders , 47 (5), 487–498. Alt, M., Meyers, C., Oglivie, T., Nicholas, K., & Arizmendi, G. (2014). Cross-situational statistically based word learning intervention for late-talking toddlers. Journal of Communication Disorders , 52 , 207–220. http://dx.doi. org/10.1016/j.jcomdis.2014.07.002 Apfelbaum, K. S., Hazeltine, E., & McMurray, B. (2013). Statistical learning in reading: Variability in irrelevant letters helps children learn phonics skills. Developmental Psychology , 49 (7), 1348–1365. Arciuli, J. (2017). The multi-component nature of statistical learning. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences , 372 (1711). Arciuli, J. (2018). Reading as statistical learning. Language, Speech, and Hearing Services in Schools , 49 , 634–643. Arciuli, J., & Conway, C. (2018). The promise – and challenge – of statistical learning for elucidating atypical language development. Current Directions in Psychological Science , 27 , 492–500. Arciuli, J., & Cupples, L. (2006). The processing of lexical stress during visual word recognition: Typicality effects and orthographic correlates. Quarterly Journal of Experimental Psychology , 59 (5), 920–948. https://doi. org/10.1080/02724980443000782 Arciuli, J., & Cupples, L. (2007). Would you rather “embert a cudsert” or “cudsert an embert’? How spelling patterns at the beginning of English disyllables can cue grammatical category. In A. Schalley D. Khlentzos (Eds.) Mental states: Language and cognitive structure (pp. 213–237). John Benjamins Publishing: Amsterdam. Arciuli, J., McMahon, K., & de Zubicaray, G. (2012). Probabilistic orthographic cues to grammatical category in the brain. Brain and Language , 123 (3), 202–210. https:// Arciuli, J., & Monaghan, P. (2009). Probabilistic cues to grammatical category in English orthography

of Memory and Language , 63 (2), 180–196. https://doi. org/10.1016/j.jml.2010.03.005 Arciuli, J., & Paul, R. (2012). Sensitivity to probabilistic orthographic cues to lexical stress in adolescent speakers with ASD and typical peers. Quarterly Journal of Experimental Psychology , 65 , 1288–1295. Arciuli, J., & Simpson, I. C. (2011). Statistical learning in typically developing children: the role of age and speed of stimulus presentation. Developmental Science , 14(3), 464– 473. Arciuli, J., & Simpson, I. C. (2012). Statistical learning is related to reading ability in children and adults. Cognitive Science , 36 (2), 286–304. 6709.2011.01200.x Baayen, R. H., Pipenbrock, R., & Gulikers, L. (1993). The CELEX lexical database [CD-ROM]. Philadelphia, PA: University of Pennsylvania. Brady, T. F., & Oliva, A. (2008). Statistical learning using real-world scenes extracting categorical regularities without conscious intent. Psychological Science, 19 (7), 678–685. doi:10.1111/j.1467-9280.2008.02142.x Burani, C., & Arduino, L. S. (2004). Stress regularity or consistency? Reading aloud Italian polysyllables with different stress patterns. Brain and Language , 90 (1–3), 318–325. Chetail, F. (2017). What do we do with what we learn? Statistical learning of orthographic regularities impacts written word processing. Cognition , 163 , 103–120. https:// Conway, C. M., Baurnschmidt, A., Huang, S., & Pisoni, D. (2010). Implicit statistical learning in language processing: Word predictability is the key. Cognition, 114 (3), 356–371. doi:10.1016/j.cognition.2009.10.009 Fiser, J., & Aslin, R. N. (2001). Unsupervised statistical learning of higher-order spatial structures from visual scenes. Psychological Science , 12 (6), 499–504. https://doi. org/10.1111/1467-9280.00392 Frost, R., Armstrong, B. C., Siegelman, N., & Christiansen, M. H. (2015). Domain generality versus modality specificity: The paradox of statistical learning. Trends in Cognitive Sciences , 19 (3), 117–125. Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What predicts successful literacy acquisition in a second language? Psychological Science , 24 (7), 1243–1252. Fudge, E. (1984). English word stress . London: Allen & Unwin. Gabay, Y., Thiessen, E. D., & Holt, L. L. (2015). Impaired statistical learning in developmental dyslexia. Journal of Speech, Language, and Hearing Research , 58 (3), 934–945. 10.1044/2015_JSLHR-L-14-0324 Gathercole, S. E., Alloway, T. P., Willis, C., & Adams, A. M. (2006). Working memory in children with reading disabilities. Journal of Experimental Child Psychology , 93 (3), 265–285. Grimani, A., & Protopapas, A. (2016). Derivational suffixes as cues to stress position in reading Greek. Journal of Research in Reading . 9817.12092 He, W., & Tong, S. (2017). Quantity matters: Children with dyslexia are impaired in a small, but not large, number of exposures during implicit repeated sequence learning. American Journal of Speech-Language Pathology , 26 (4), 1080–1091. He, X., & Tong, X. (2017). Statistical learning as a key to cracking Chinese orthographic codes. Scientific Studies of Reading , 21 (1), 60–75.

and their influence during reading. Scientific Studies of Reading , 13 (1), 73–93. https://doi. org/10.1080/10888430802633508

Arciuli, J., Monaghan, P., & Ševa, N. (2010). Learning to assign lexical stress during reading aloud: Corpus, behavioral, and computational investigations. Journal


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Hebb, D. (1961). Distinctive features of learning in the higher animal. In J.F. Delafresnaye (Ed.), Brain mechanisms and learning (pp. 37–46). Oxford, UK: Blackwell. Hedge, C., Powell, G., & Sumner, P. (2017). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavioral Research Methods . doi: 10.3758/s13428-017-0935-1 Henderson, L. M. & Warmington, M. (2017). A sequence learning impairment in dyslexia? It depends on the task. Research in Developmental Disabilities , 60 , 198–210. doi: 10.1016/j.ridd.2016.11.002 Jouravlev, O., & Lupker, S. J. (2014). Stress consistency and stress regularity effects in Russian. Language, Cognition and Neuroscience , 29 (5), 605–619. https://doi.or g/10.1080/01690965.2013.813562 Jouravlev, O., & Lupker, S. J. (2015). Lexical stress assignment as a problem of probabilistic inference. Psychonomic Bulletin & Review , 22 (5), 1174–1192. https:// Kahta, S., & Schiff, R. (2019). Deficits in statistical learning of auditory sequences among adults with dyslexia. Dyslexia , 25 , 142–157. Kalra, P. B., Gabrieli, J. D. E., & Finn, A. S. (2019). Evidence of stable individual differences in implicit learning. Cognition , 190 , 199–211. cognition.2019.05.007 Kaufman, S.B., DeYoung, C.G., Gray, J.R., Jiménez, L., Brown, J., & Mackintosh, N. (2010). Implicit learning as an ability. Cognition , 1 16 , 321–340. Kelly, M. (2004). Word onset patterns and lexical stress in English. Journal of Memory and Language , 50(3), 231–244. Kelly, M., Morris, J., & Verrekia, L. (1998). Orthographic cues to lexical stress: Effects on naming and lexical decision. Memory & Cognition , 26 (4), 822–832. https://doi. org/10.1037/e536982012-107 Kemp, N., Nilsson, J., & Arciuli, J. (2009). Noun or verb? Adult readers’ sensitivity to spelling cues to grammatical category in word endings. Reading and Writing , 22 (6) 637–659. Kidd, E. (2012). Implicit statistical learning is directly associated with the acquisition of syntax. Developmental Psychology , 48 , 171–184. doi:10.1037/a0025405 Kidd, E., & Arciuli, J. (2016). Individual differences in statistical learning predict children’s comprehension of syntax. Child Development , 87 (1), 184–193. https://doi. org/10.1111/cdev.12461 Kidd, E., Smithson, M., Christiansen, M, H., & Arciuli, J. (2019). A longitudinal investigation of auditory and visual statistical learning in children. Interdisciplinary Advances in Statistical Learning Conference . San Sebastian, Spain. Kleij, S. W. v. d., Groen, M. A., Segers, E., & Verrhoeven, L. (2019). Sequential implicit learning ability predicts growth in reading skills in typical readers and children with dyslexia. Scientific Studies of Reading , 23 , 77–88. Lum, J. A., Ullman, M. T., & Conti-Ramsden, G. (2013). Procedural learning is impaired in dyslexia: Evidence from a meta-analysis of serial reaction time studies. Research in Developmental Disabilities , 34 (10), 3460–3476. doi:10.1016/j.ridd.2013.07.017 Monaghan, P., Arciuli, J. & Ševa, N. (2016). Cross- linguistic evidence for probabilistic orthographic cues to lexical stress. In J. Thomson & L. Jarmulowicz (Eds.) Linguistic rhythm and literacy (pp 215–236). Amsterdam: John Benjamins Publishing. Mousikou, P., Sadat, J., Lucas, R., & Rastle, K. (2017). Moving beyond the monosyllable in models of skilled

reading: Mega-study of disyllabic nonword reading. Journal of Memory and Language , 93 , 169–192. https://doi. org/10.1016/j.jml.2016.09.003 Nicolson, R. I., Fawcett, A. J., Brookes, R. L., & Needle, J. (2010). Procedural learning and dyslexia. Dyslexia , 16 (3), 194–212. Nigro, L., Jiménez-Fernández, G., Simpson, I. C., & Defior, S. (2015). Implicit learning of written regularities and its relation to literacy acquisition in a shallow orthography. Journal of Psycholinguistic Research, 44 (5), 571–585. requirements of learning: Evidence from performance measures. Cognitive Psychology , 19 (1), 1–32. doi: 10.1016/0010-0285(87)90002-8 Pacton, S., Fayol, M., & Perruchet, P. (2005). Children’s implicit learning of graphotactic and morphological regularities. Child Development , 76 , 324–339. Pacton, S., Perruchet, P., Fayol, M., & Cleeremans, A. (2001). Implicit learning out of the lab: The case of orthographic regularities. Journal of Experimental Psychology: General , 130 (3), 401–426. https://doi. org/10.1037/0096-3445.130.3.401 Perry, C., Ziegler, J. C., & Zorzi, M. (2010). Beyond single syllables: Large-scale modeling of reading aloud with the Connectionist Dual Process (CDP++) model. Cognitive Psychology , 61 (2), 106–151. cogpsych.2010.04.001 Plante, E., Ogilvie, T., Vance, R., Aguilar, J. M., Dailey, N. S., Meyers, C., . . . Burton, R. (2014). Variability in the language input to children enhances learning in a treatment context. American Journal of Speech-Language Pathology , 23 , 530–545. Protopapas, A., Mitsi, A., Koustoumbardis, M., Tsitsopoulou, S. M., Leventi, M., & Seitz, A. R. (2017). Incidental orthographic learning during a color detection task. Cognition , 166 , 251–271. cognition.2017.05.030 Qi, Z., Sanchez Araujo, Y., Georgan, W. C., Gabrieli, J. D., & Arciuli, J. (2018). Hearing matters more than seeing: A cross-modality study of statistical learning and reading ability. Scientific Studies of Reading , 23 , 101–115. 1–15. 1485680 Rashotte, C., Torgerson, J. K., & Wagner, R. (1999). Test of word reading efficiency . Oxford, UK: Pearson Assessment. Rastle, K., & Coltheart, M. (2000). Lexical and nonlexical print-to-sound translation of disyllabic words and nonwords. Journal of Memory and Language , 42 (3), 342–364. Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behavior , 6 (6), 855–863. 5371(67)80149-x Reber, P. J. (2013). The neural basis of implicit learning and memory: A review of neuropsychological and neuroimaging research. Neuropsychologia , 51 (10), 2026–2042. Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. S cience , 274 (5294), 1926–1928. science.274.5294.1926 Sawi, O. M., & Rueckl, J. (2019). Reading and the neurocognitive bases of statistical learning. Scientific Studies of Reading , 23 , 8–23. Schiff, R., Katan, P., Sasson, A., & Kahta, S. (2017). Effect of chunk strength on the performance of children with developmental dyslexia on artificial grammar learning Nissen, M.J. & Bullemer, P. (1987). Attentional


JCPSLP Volume 22, Number 1 2020

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