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and a review of acquired dyslexia cases (Ramus, 2003) – added to the persuasiveness of the phonological deficit hypothesis. Imaging results converged to show associations between reading problems and failures to engage left hemisphere language areas (Shaywitz et al., 2004; Simos et al., 2007; Turkeltaub et al., 2003). Although the cause of phonological problems is uncertain, there is evidence that they originate prior to literacy: Among children at risk for dyslexia, preliterate language skills predict their phonological skills and subsequent reading skills (Hulme et al., 2015; Snowling et al., 2003). Moreover, interventions can improve children’s oral language skills and their prospects for reading (Hulme et al., 2020).
Other work has suggested that phonological problems may reflect lower level deficits in, for example, temporal coding in the auditory system (Tallal, 1980) or the perception of speech (Noordenbos & Serniclaes, 2015; although others have questioned these ideas (e.g., Strong et al., 2011; Snowling et al., 2019). Further, it has been proposed that automatized naming problems (e.g., & Wolf, 2011), when added to a phonological deficit, produce a “double deficit” (Wolf & Bowers, 1999) and Ziegler et al. (2019) concluded that most children show phonological deficits while also showing weaknesses in nonphonological tasks, especially letter detection. Although there are potentially multiple causes of disruption to the word‐identification system, the phonological deficit hypothesis is supported by extensive evidence and is now the standard theory. Indeed, a phonological deficit is part of the definition of dyslexia provided by the International Dyslexia Association (https://dyslexiaida.org/definition‐of‐dyslexia/).
Advance 2. Comprehending while Reading
It should be contentious to consider a subsystem of reading called “reading comprehension.” If learning to read words unlocks the resources of spoken language comprehension, then anything special about reading ends at word identification. “The Simple View of Reading” (Gough & Tunmer, 1986; Hoover & Gough, 1990) expresses this assumption and continues to accumulate evidence (Catts, 2018; Hjetland et al., 2020; Lonigan et al., 2018; Nation, 2019). Moreover, reading comprehension builds on spoken language experience. Preschool measures of oral language predict school‐entry indicators of word level skills that predict later comprehension skills (Hulme et al., 2015).
Nevertheless, comprehension is a distinctive subsystem of reading, even if it derives from general language comprehension. Moreover, excluding reading comprehension as part of reading would ignore the largest body of research on skilled comprehension. Much of what is known about language comprehension – including such basic aspects as sentence comprehension – comes from reading research (see Liversedge et al., this volume).
Whereas word identification operates with a restricted set of knowledge sources (graph forms (e.g., letters), phonology, and morphology), comprehension operates with every knowledge source one can imagine. To simplify the resulting complexity, we refer to the RSF comprehension subsystem, extracted here as Figure 1.3.
The lexicon plays a pivotal role. The output of the word‐identification system, the word’s pronunciation and meaning features, is the input to the comprehension system. A word’s meaning is directly integrated into ongoing comprehension and its pronunciation helps secure the word’s identity, thus supporting processes of structure building, integration, and, when needed, repair.
Figure 1.3 The comprehension system of the Reading Systems Framework.
From global top‐down structures to actual comprehension
Text comprehension results from word‐by‐word, phrase‐by‐phrase, and sentence‐by‐sentence processes that are challenging to study. So, research started at the other end – where global structures could be seen as shaping local word and sentence processes. Early artificial intelligence (AI) systems started with global organizers for restricted situational comprehension (Schank & Abelson, 1977). Similarly, approaches within psychology and education also emphasized situated conceptual structures or schemata (Anderson & Pearson, 1984). Evidence for global top‐down guidance came from studies showing that a nearly incomprehensible text could be understood with a helpful title (Bransford & Johnson, 1972) and that a text lacking referential specificity could be understood as being about either music or card playing depending on whether the reader was a student in music education or physical education (Anderson et al., 1977).
Other approaches focused on more generalized mental structures (e.g., story grammars, Mandler & Johnson, 1977; Stein & Glenn, 1979) that guide narrative comprehension. Trabasso and colleagues (1984) argued that people seek causality in reading stories and showed that causal expectations predict how readers understand sentences (Trabasso & Suh, 1993). In Reading Systems Framework terms, these approaches focus on the general knowledge component and largely ignore comprehension processes. They provide demonstrations of global influence without dealing with the nuts and bolts of comprehension.
Text comprehension from the bottom up
Kintsch and van Dijk (1978) approached text comprehension as a cyclical process, with every text element activating meanings on the way to a coherent representation of the text as a whole. The Construction Integration model (Kintsch, 1988, Kintsch & Rawson, 2005) proposed two phases of comprehension: An initial construction phase, prompted by word meaning, spreads activation across memory of both text elements and general knowledge in a passive, automatic process.1 A companion integration phase uses the overlap of meaning among the activated elements to constrain what information remains for the next cycle. Multiple integration phases lead to a coherent representation of the text.
The Construction Integration model moved text comprehension research toward a processing approach, incorporating memory‐based, word‐meaning, and sentence level components. The structure building framework (Gernsbacher, 1990, 1997) emphasized the complementary processes of memory‐based meaning mapping and structure building. Later models retained this focus on bottom‐up, memory‐based processes, including the Resonance Model (Myers & O’Brien, 1998) and the more recent Resonance, Integration, and Validation Model (Cook & O’Brien, 2014).
Global influences continued to be emphasized in constructivist theories that assume readers are driven to construct coherence and search for meaning (Graesser et al., 1994). Top‐down influences were elaborated more specifically as mental structures to guide the reader’s construction of coherence, for example, dimensions of time, space, and causality in the Event‐Indexing Model (Zwaan et al., 1995). The Landscape model combined the automatic bottom‐up processes of memory‐based models with the top‐down influences of constructionist theories (van den Broek et al., 2005; van den Broek et al., 1999). In this model, a coherent mental representation emerges from both text and external knowledge activation patterns that increase and diminish over the course of reading a text. Comprehension results from the mixing of automatic passive processes with reader‐initiated strategic processes determined by the reader’s standard for coherence and goals in a particular reading situation (van den Broek et al., 1995; van den Broek & Helder, 2017; see van den Broek & Kendeou, this volume).
The situation model: Knowledge and inferences
Text comprehension results in memories at multiple levels, two at minimum: the text surface and the mental‐model (Johnson‐Laird, 1983). Research generally has followed the three‐way distinction of van Dijk and Kintsch (1983): surface level, text‐base, and situation model. This three‐way distinction adds a level of language‐based