Pathways to comprehension: The role of supra-lexical monitoring in narrative and informational text understanding

Pathways to comprehension: The role of supra-lexical monitoring in narrative and informational text understanding | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pathways to comprehension: The role of supra-lexical monitoring in narrative and informational text understanding Smadar Zohar Patael, Ori Levin, Mor Levy, Amalia Bar-On This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9574360/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Understanding how readers extract meaning from different text genres provides a critical test for models of reading comprehension. The present study integrates the Lexical Quality Hypothesis (Perfetti, 2007 ) and the Combinatorial Model of reading acquisition (Share, 2025 ) to examine how lexical knowledge, decoding processes, and supra-lexical monitoring jointly support comprehension across narrative and informational texts in Hebrew. Ninety-four Hebrew-speaking fourth graders completed a comprehensive battery assessing vocabulary, morpho-lexical knowledge, reading accuracy and speed, supra-lexical monitoring (via a Garden Path paradigm), and comprehension of narrative and informational texts. Path analysis revealed both shared and genre-specific pathways, explaining substantial variance in comprehension (41% for narrative, 51% for informational). A common pathway emerged in which supra-lexical monitoring contributed directly to comprehension in both text types, linking word-level processes to higher-level meaning construction. Beyond this shared mechanism, distinct patterns were observed: narrative comprehension was primarily supported by vocabulary and monitoring, whereas informational comprehension relied on a broader constellation including morpho-lexical knowledge and reading speed. These findings highlight supra-lexical monitoring as a central regulatory mechanism in reading comprehension and demonstrate how readers flexibly adapt the relative contributions of lexical and decoding processes to meet genre-specific demands. The study advances an integrated account of comprehension by showing how shared and differential pathways emerge within a unified framework during the transition from learning to read to reading for learning. reading comprehension lexical quality morphological awareness supra-lexical monitoring narrative text informational text Figures Figure 1 Introduction Reading comprehension is a complex, multidimensional ability that relies on an interplay of decoding, linguistic, cognitive, and metacognitive processes. Several theoretical models describe how these processes support the construction of meaning. The Simple View of Reading conceptualizes comprehension as the product of decoding and linguistic understanding (Hoover, 2023 ; Hoover & Gough, 1990 ), a framework that has received broad empirical support across languages and developmental stages (e.g., Bellocchi et al., 2025 ; Catts et al., 2005 ; Joshi et al., 2015 ). Although the Simple View frames these components as distinct, subsequent research has shown that the relationships among them are dynamic and reciprocal (e.g., Duke & Cartwright, 2021 ; Scarborough, 2001 ; Snow, 2018 ). Perfetti and Stafura’s ( 2014 ) framework extends this view by positioning reading comprehension as the coordinated outcome of efficient word-level processes and higher-order text integration. Central to this account is the Lexical Quality Hypothesis (Perfetti, 2007 ; Perfetti & Hart, 2002 ), which holds that readers with precise and well specified lexical representations access word meanings rapidly and consistently, thereby supporting fluent integration and inference making. Share’s recent Combinatorial Model of reading acquisition (Share, 2025 ) offers an additional conceptual layer that is relevant to comprehension. The model characterizes reading development as the integration of linguistic information across sub-morphemic, morpho-lexical, and supra-lexical levels. The supra-lexical phase highlights the reader’s ability to use context to monitor, evaluate, and refine meaning during reading, reflecting a shift toward flexible and strategically guided comprehension. Although these models conceptualize reading comprehension as a general process, extensive research shows that the operation of decoding, lexical, and higher-order processes varies across text types, particularly narrative and informational texts, which differ in their linguistic and cognitive demands (Graesser et al., 2011 ). Despite extensive research on reading comprehension across text types, existing accounts have typically focused on relations among decoding and lexical knowledge, while the role of supra-lexical processes has received comparatively less attention within integrated models. As a result, it remains unclear how word-level processes and higher-order, context-driven regulation operate jointly within a unified framework, particularly across genres. In addition, monitoring processes have often been assessed using domain-general executive function measures, leaving open the question of whether reading-specific, context-based monitoring uniquely contributes to comprehension. This issue is especially relevant in orthographies such as Hebrew, where pervasive lexical ambiguity increases reliance on contextual information during reading. To address these gaps, the present study integrates the Lexical Quality Hypothesis and the Combinatorial Model within a unified empirical framework. Specifically, we examine how lexical knowledge (vocabulary and morpho-lexical knowledge), decoding (accuracy and rate), and supra-lexical monitoring jointly contribute to the comprehension of narrative and informational texts in Hebrew-speaking fourth graders. This developmental stage marks the transition from “learning to read” to “reading to learn” (Chall, 1983 ; Hoover & Gough, 1990 ; National Reading Panel, 2000 ), during which decoding becomes increasingly automatized and higher-order linguistic and regulatory processes play a more central role in comprehension (Cain & Oakhill, 2008 ; Catts et al., 2005 ; Kim et al., 2021 ). Examining these components within a unified framework across text genres enables a direct comparison of shared and genre-specific pathways to comprehension, providing a more comprehensive account of how readers coordinate word-level and supra-lexical processes during this critical stage of reading development. Narrative and informational text comprehension Narrative and informational texts differ systematically in their communicative purposes. Narratives aim to entertain and convey human experience, whereas informational texts aim to present factual knowledge and explain concepts (Duke & Cartwright, 2021 ; Graesser et al., 2011 ). These differing purposes are reflected in their structural organization. Narratives typically follow event-based structures that unfold sequentially over time, supported by temporal and causal connections (Berman & Slobin, 1994 ). Informational texts, in contrast, employ expository structures that organize ideas according to logical relations such as cause and effect or comparison (Berman, 2008 ; Meyer & Ray, 2017 ). At the linguistic level, narratives tend to rely on familiar, high-frequency vocabulary that supports the representation of characters and events, whereas informational texts show higher lexical density and greater reliance on abstract and domain-specific terminology. They also typically involve greater syntactic complexity, requiring readers to process more compact and conceptually dense expressions (Berman, 2016 ; Berman & Nir-Sagiv, 2009 ; Fang & Schleppegrell, 2010 ; Ravid & Berman, 2010 ). Together, these differences contribute to distinct cognitive demands across text types. Across development, narrative texts are generally easier to understand than informational texts. Meta-analytic evidence indicates a small to moderate narrative advantage in both general and inferential comprehension (Clinton et al., 2020 ; Mar et al., 2021 ). Informational texts also appear to place greater demands on executive control and inference generation, with readers producing fewer bridging and elaborative inferences and more knowledge-based errors (Kraal et al., 2018 ; Miller et al., 2013 ). Genre differences appear across reading modalities (Dickens & Meisinger, 2017 ) and persist even when cohesion is increased (McNamara et al., 2011 ; van Silfhout et al., 2015 ). Among young readers, these differences remain even after controlling for vocabulary, inferencing, and working memory (Kim et al., 2021 ; Wu et al., 2020 ). Among older students, the gap is reduced but not eliminated, suggesting that the magnitude of genre effects depends on readers’ linguistic, cognitive, and motivational profiles (Cruz Neri et al., 2023 ; Eason et al., 2012 ). However, genre effects are not absolute. When content is matched across genres, informational texts sometimes support comparable or even superior learning outcomes, both in recall of identical content and in conceptual understanding (Cervetti et al., 2009 ; Neuman et al., 2025 ). These findings suggest that genre effects depend on factors such as readers’ age and the nature of the comprehension task. Contribution of lexical and morpho-lexical knowledge to comprehension across the two text types Lexical knowledge is consistently identified as a central component of reading comprehension, contributing to both efficient semantic access and higher-order integration processes (Kim et al., 2021 ; Perfetti, 2007 ; Perfetti & Stafura, 2014 ). A large body of empirical research across languages and developmental stages shows that vocabulary predicts comprehension even after accounting for decoding (e.g., Ouellette, 2006 ; Protopapas et al., 2013 ; Quinn et al., 2015 ). With respect to text genre, evidence across age groups and research designs suggests that vocabulary contributes to comprehension in both narrative and informational texts to a comparable degree. For example, vocabulary has been found to predict comprehension to a similar degree in both genres among elementary school students (Santos et al., 2017 ), to longitudinally predict later comprehension outcomes across genres (Wu et al., 2020 ), and to show similar associations in older students as well (Cruz Neri et al., 2023 ). Some studies nevertheless report somewhat stronger vocabulary effects for informational text comprehension, particularly from the middle elementary grades onward (Liebfreund, 2021 ; Yildirim et al., 2011 ). Because informational comprehension is closely tied to background knowledge, vocabulary may appear especially predictive when lexical knowledge overlaps with the conceptual knowledge required for understanding the text (Best et al., 2008 ). Consistent with this interpretation, vocabulary measures containing items related to informational content tend to show stronger associations with informational comprehension (Hannon, 2022 ). Beyond vocabulary, morphological knowledge has also emerged as an important contributor to reading comprehension. A recent meta-analysis of 44 studies with children aged 6 to 16 reported a strong overall association between morphological awareness and comprehension (r ≈ .565), an effect that strengthens across development as texts contain more morphologically complex vocabulary (Liu et al., 2024 ). Morphological awareness contributes both directly, by enabling readers to extract semantic and relational information from complex words, and indirectly through its effects on word reading and vocabulary growth (Deacon et al., 2014 ; Foorman et al., 2012 ; Zhang et al., 2023 ). Importantly, this contribution is not reducible to vocabulary knowledge, as it explains unique variance in comprehension even after controlling for vocabulary, phonological awareness, and word reading (Levesque et al., 2017 ; Tong et al., 2011 ). The contribution of morphology to comprehension has been documented across alphabetic languages such as English (Deacon et al., 2014 ; Nagy et al., 2006 ), French (Rassel et al., 2021 ), and Spanish (Simpson et al., 2019 ), as well as in non-alphabetic orthographies such as Chinese (Tong et al., 2017 ). In Hebrew, a morphologically rich Semitic language, awareness of root and pattern structures has also been shown to support text comprehension (Primor et al., 2011 ; Ravid & Mashraki, 2007 ; Vaknin-Nusbaum et al., 2015 ). Despite extensive research on morphology and reading comprehension, little is known about whether its contribution varies across text genres. To date, only one study has examined morphology in relation to genre specific comprehension (Primor et al., 2011 ). In this study of Hebrew speaking fourth graders, morphological awareness explained modest but significant variance in comprehension, predicting narrative comprehension among children with reading disabilities and informational text comprehension among typically developing readers. No research has examined genre differences while simultaneously modeling morphological awareness, vocabulary, and decoding abilities, leaving an important gap in understanding how these skills support comprehension across text types. Contribution of decoding abilities to comprehension across the two text types A growing body of research indicates that the contribution of decoding to reading comprehension is moderated by several interrelated factors, most prominently readers’ age, with a marked decline in the decoding–reading comprehension relation around ages 9 to 10 (García & Cain, 2014 ). In their meta-analytic study, García and Cain ( 2014 ) also identified the type of decoding measure as a key moderator of this relationship. Among young readers, reading accuracy showed the strongest correlations with comprehension, whereas speed-based measures showed weaker associations. As decoding accuracy approaches ceiling levels with development, a progression that often occurs earlier in alphabetic systems with relatively transparent grapheme–phoneme correspondences (Joshi, 2018 ), its predictive power diminishes, and measures indexing processing efficiency, such as timed word reading or text-level fluency, become more informative (Padeliadu & Antoniou, 2014 ; Protopapas et al., 2007 ). When genre is considered, the pattern becomes more complex. Studies using untimed, word-level accuracy measures have shown that narrative comprehension is predicted by decoding, whereas informational text comprehension is more strongly associated with world knowledge (Best et al., 2008 ; Hannon, 2022 ). In contrast, when decoding is assessed using timed word-level measures that integrate accuracy and speed, early decoding efficiency predicts growth in informational, but not narrative, comprehension, suggesting a role for automatized lexical access in processing informational texts (Wu et al., 2020 ). Studies employing text-level measures of reading fluency, which assess accuracy and speed within connected text, have not consistently found genre-specific effects. Across languages and age groups, decoding-related skills measured in this way tend to predict comprehension similarly across narrative and informational texts (e.g., Padeliadu & Antoniou, 2014 ; Primor et al., 2011 ; Santos et al., 2017 ; Uysal & Bilge, 2018 ). These findings suggest that, beyond developmental factors, inconsistencies in literature reflect differences in the level of measurement (word vs. text) and in the nature of the construct assessed (accuracy vs. integrated fluency). Higher-Order Supra-Lexical Processes: The Case of Hebrew Reading is not solely a matter of accurate word identification or lexical access but also involves the integration of contextual information. The addition of the supra-lexical layer in the Combinatorial Model (Share, 2025 ) reframes reading as a process of meaning construction guided by contextual information. At this level, readers integrate linguistic information across words, sentences, and discourse, while continuously revising and regulating interpretations in response to contextual cues. Such cues become particularly important when readers encounter lexical ambiguity, in which a single orthographic form corresponds to multiple meanings. This occurs with homophonic homographs that share pronunciation but differ in meaning, (e.g., bat ), and with heterophonic homographs (e.g., present ), which differ in both meaning and pronunciation. Although heterophonic homographs are relatively rare in many non-Semitic languages (Perfetti & Hart, 2002 ), they are common in Hebrew and Arabic due to their Abjadic writing systems, which provide limited marking of vowels (Share, 2008 ). Hebrew-speaking children initially learn to read a transparent version of the script, the pointed system, in which phonology is represented almost fully through consonantal letters, vowel letters, and vowel diacritics. After approximately three to four years of schooling, they transition to the unpointed script, where diacritics are removed and phonological information, especially vowels, is only partially encoded (e.g., Share & Bar-On, 2018 ). Reading this opaque script requires reliance on two complementary strategies. One is morpho-orthographic identification, in which readers use the consonantal root and pattern system of Hebrew to constrain lexical candidates and recover missing phonological information (Bar-On & Ravid, 2011 ). The second is reliance on contextual information. Because unpointed Hebrew contains many heterophonic homographs, readers must integrate syntactic, semantic, and discourse cues to determine the appropriate interpretation (Bar-On et al., 2017 , 2021 ). Consistent with this perspective, and in line with the Combinatorial Model (Share, 2025 ), Share and Bar-On ( 2018 ) identified context reliance as a distinct third level in their Triplex Model of learning to read Hebrew. The pervasive lexical ambiguity created by the Abjadic script increases the likelihood of misidentification and therefore heightens the importance of efficient supra-lexical monitoring processes during reading. Supra-lexical monitoring processes Within contemporary models of reading comprehension, a key component of skilled reading is the ability to detect and repair breakdowns in understanding. In metacognitive and conflict-monitoring frameworks, this regulatory capacity comprises two coordinated processes: monitoring, the detection of mismatches between an emerging interpretation and incoming textual information (Nelson, 1990 ), and control, processes that resolve such mismatches through inhibition, reanalysis, and updating (Botvinick et al., 2001 ; Koriat & Goldsmith, 1996 ). A well-established paradigm for investigating this coordination in real time is the Garden Path (GP) sentence. Garden Path structures temporarily guide readers toward an interpretation that later proves incompatible with subsequent input, creating a point of processing conflict. Successful comprehension, therefore, requires readers to detect the conflict, inhibit the initial interpretation, and construct an alternative analysis. Because these processes occur during real-time sentence interpretation, the Garden Path paradigm provides a behavioral index of supra-lexical monitoring processes that trigger reanalysis and control within reading (Frazier & Rayner, 1982 ; Novick et al., 2005 ). Hebrew provides a particularly informative context for examining such processes. The high frequency of heterophonic homographs in unpointed Hebrew requires readers to rely on syntactic and semantic context to determine the intended interpretation (Shimron & Sivan, 1994 ). Garden Path paradigms have therefore been adapted in Hebrew to examine real-time supra-lexical monitoring during lexical ambiguity resolution (Bar-On et al., 2017 , 2019 ). In a large developmental study, Bar-On et al. ( 2017 ) asked participants ranging from second graders to adults to read aloud sentences containing heterophonic homographs that induced temporary misinterpretations. Whereas second and third graders showed little evidence of monitoring, fourth graders corrected approximately half of the induced misinterpretations, with continued improvement into adolescence. Although the Garden Path task captures readers’ ability to detect and revise misinterpretations in real time, it remains unclear whether such supra-lexical monitoring processes explain unique variance in reading comprehension beyond lexical knowledge and decoding skills. Much of the literature linking executive processes to comprehension has relied on domain-general executive function (EF) measures, such as inhibition, working memory, and cognitive flexibility, administered outside the context of reading. A comprehensive meta-analytic review of 29 studies reported a moderate overall association between EF and reading comprehension across development (Follmer, 2018 ). However, this reliance limits conclusions about the processes engaged during reading itself. Consistent with this limitation, recent studies show that reading-specific EF tasks, which embed control demands within print processing, explain unique variance in comprehension beyond traditional EF measures (Cartwright et al., 2020 ; Peng et al., 2024 ). In the present study, we therefore employ the Garden Path paradigm to capture supra-lexical monitoring processes in reading. If such processes contribute uniquely to comprehension, an open question is whether their contribution varies across text genres. Some studies suggest that executive processes may be particularly important for informational texts, which often impose greater integration and regulatory demands (Eason et al., 2012 ; Wu et al., 2020 ). However, structural models also report similar patterns across genres, with working memory showing direct effects on both narrative and informational comprehension, and inhibition and cognitive flexibility operating indirectly through vocabulary in both (Escobar & Espinoza, 2025 ). Evidence from text-based studies likewise points to genre differences in monitoring demands. These processes are typically assessed through readers’ responses to inconsistencies or inference gaps in extended texts, indexed by slowed reading, rereading, or explicit detection of comprehension problems. Informational texts generally elicit slower reading, more rereading, and lower recall than narrative texts, and effective regulation strategies such as selective rereading are more strongly associated with informational text comprehension (Kraal et al., 2018 ; Yoo, 2024 ; Zabrucky & Moore, 1999 ). Neurophysiological evidence similarly indicates greater semantic integration demands during inference generation in informational texts (Baretta et al., 2009 ). Accordingly, if supra-lexical monitoring processes make a unique contribution to reading comprehension, this contribution is expected to be stronger for informational than for narrative texts. The present study The study aims to examine how foundational lexical knowledge, decoding skills, and supra-lexical monitoring processes jointly contribute to reading comprehension at a stage when basic word identification has largely stabilized. In addition to assessing their direct contributions, the study evaluates whether supra-lexical monitoring functions as a regulatory mechanism linking word-level decoding to text-level comprehension. Specifically, the study investigates whether the relative contributions and structural relations among these components differ between narrative and informational texts. By integrating vocabulary and morpho-lexical knowledge as complementary indices of lexical quality, separating decoding into accuracy and rate components, and incorporating a reading-embedded measure of supra-lexical monitoring derived from the Garden Path paradigm, the study evaluates reading processes across multiple representational levels within a single path-analytic framework. In doing so, it addresses a key gap in the literature concerning the joint contribution of word-level and supra-lexical processes to comprehension across text genres. The ordering of variables in the proposed path model was guided by the Lexical Quality Hypothesis (Perfetti, 2007 ; Perfetti & Stafura, 2014 ) and the Combinatorial Model (Share, 2025 ). Although lexical knowledge and reading experience influence one another, lexical representations are theorized to constrain the efficiency and flexibility of word identification (Perfetti, 2007 ). Accordingly, lexical knowledge was positioned as the foundational layer of the model. Decoding skills, operationalized as accuracy and rate, were entered at the second level to capture the quality of word identification in print. At the third level, supra-lexical monitoring was included to reflect higher-level regulation during sentence-level processing. We expected lexical knowledge to contribute robustly to comprehension across genres. Decoding was expected to show a reduced but potentially genre-sensitive contribution at this developmental stage, and supra-lexical monitoring was expected to explain additional unique variance beyond lexical and decoding components. Given evidence that informational texts impose greater lexical, conceptual, and regulatory demands, we hypothesized that the relative contributions of lexical knowledge, decoding components, and supra-lexical monitoring would differ between informational and narrative comprehension. Methods Sample The sample comprised 94 fourth-grade students (53 girls) aged 9 to 11 years ( M = 10.01, SD = 0.33) from four public schools in Israel. The schools were evenly distributed between the state secular education system (49% of participants) and the state religious education system, with all schools ranked in the 1st-2nd deciles of the Israeli Ministry of Education's nurture index, indicating a medium to high socioeconomic status. Participant selection followed specific inclusion criteria. All participants demonstrated normal nonverbal intelligence, as measured by Raven's Progressive Matrices (Raven et al., 1996 ), and verbal intelligence, as measured by the vocabulary subscale of the Wechsler Intelligence test (Wechsler, 2012 ). Additionally, all participants had at least five years of Hebrew language exposure and the absence of hearing or neurodevelopmental disorders. The final sample comprised both typically developing readers and children with documented learning disabilities, capturing the full range of reading and language abilities. The research protocol was approved by the authors’ institutional ethics committee and the national education authority (Approval No. 8790). Written informed consent was obtained from both participants and their parents before study enrolment. For the current study, the following measures were selected from a larger battery of tests. Measures Reading comprehension tests . Two reading comprehension tests were administered during separate assessment sessions: one using an informational text and the other using a narrative text. In the absence of standardized reading comprehension tests in Hebrew, texts were selected from the national large-scale assessment (National Authority for Measurement and Evaluation in Education, 2014 ). Both texts were presented in unpointed Hebrew, reflecting the developmental stage of fourth-grade students who no longer rely on diacritical marks (Bar-On & Ravid, 2011 ). Students were instructed to read both texts silently and answer written questions. The informational text, titled "The Invention of the Hot Air Balloon," focused on the scientific and historical content of hot air balloons. The narrative text, titled "A Real Hero," centered on a moral dilemma and character development involving a child's decision to rescue puppies on the way to school, despite risking punishment for being late. Both texts included two accompanying illustrations to support comprehension. The comprehension assessment included both original questions from the Meitzav and questions developed specifically for this study. Both tests contained a comparable number of questions with comparable questioning formats, combining open-ended and multiple-choice items designed to evaluate multiple levels of comprehension according to Kintsch's model of text representation (Kintsch, 1988 ; Kintsch & Kintsch, 2005 ). Internal consistency was acceptable for both measures (Cronbach’s α = .77 for the informational text; α = .73 for the narrative text). Each test featured a scoring guide (rubric) developed in two stages: initial scoring based on a sample of approximately 20 student responses and 15 responses from native-speaking adults, followed by refinement based on the full range of responses. The questions demonstrated good inter-rater reliability (0.81–0.99). Vocabulary test . vocabulary knowledge was assessed using the Collocation Completion (Manshari & Bar-On, 2020 ). Collocations are word combinations that frequently occur together in a language (such as "heavy rain," "good luck", “hand-writing”), which provide an ecologically valid measure of lexical knowledge because they demonstrate a deeper understanding of how words are typically used together in natural language. This test was designed to assess vocabulary in school-age children and contained 30 items. Students were required to complete collocations by providing the missing word at the end of a sentence. For example, in English this would be similar to completing "The cars stopped at the traffic ____" (light). Scoring awarded 0 points for an incorrect response, 1 point for a response that was semantically appropriate but not the conventional collocation (e.g., "signal") or contained morphological/phonological errors (e.g., "lite"), and 2 points for the correct conventional response ("light"). The test was divided into two parts (each containing 15 sentences) and administered in two separate sessions. Morpho-lexical test . Morpho-lexical knowledge was assessed by the Derived Word Completion Test (Lahmi-Kakon et al., 2020 ). The test examines the derivation of verbs, adjectives, and verbal nouns through completing words in short sentences containing a prime word from which the target word must be derived. It contained 16 items where students completed sentences with words derived from the same root as a highlighted word. For example, "The teachers decided on a uniform, but the students opposed the teachers' _____" [decision]). Scoring awarded 0 points for an incorrect response (unrelated root), 1 point for morphological errors (correct root but incorrect pattern), and 2 points for the correct response (appropriate derivation). Scores were expressed as a percentage of the maximum possible score. Reading tests. Reading accuracy and speed measures were based on oral reading of four texts from the standardized "Alef to Tav" battery for evaluating reading and writing abilities in Hebrew (Shany et al., 2006 ). Participants were asked to read four texts: two pointed texts (an informational text containing 199 words and a narrative text containing 105 words) and two unpointed texts (an informational text containing 208 words and a narrative text containing 310 words). Participants were instructed to read aloud as quickly and accurately as possible. The accuracy measure was calculated as the percentage of words read correctly, while reading speed was determined by the number of words read per minute. The reliability coefficients were high, with Cronbach's alpha of 0.90 for reading accuracy and 0.97 for reading speed. Supra-lexical monitoring (Context-related processes). Supra-lexical monitoring (hereafter, monitoring) was assessed using a Garden Path (GP) test adapted from Bar-On et al. ( 2017 ). This paradigm captures readers’ ability to use contextual information to detect and revise interpretations that become inconsistent with ongoing sentence input, thereby indexing online regulation of meaning during reading. The test consisted of 16 Hebrew heterophonic-homographic words (e.g., מדבר, which can be read as /midbar/ [desert] or /medaber/ [speaking]) embedded in 32 sentences representing two conditions: Non-Garden Path (NGP) sentences, where both preceding and following contexts supported the target pronunciation (e.g., "המטיילים עברו הר גבוה ומדבר רחב" [The hikers crossed a high mountain and a wide desert]), and Garden Path (GP) sentences, where preceding context directed readers toward one pronunciation that proved incorrect as the sentence continued (e.g., "האיש הולך ומדבר רחב לפניו" [The man walks and a wide desert is before him]). Each target homographic word appeared once in an NGP sentence and once in a GP sentence. The sentences were divided into two balanced blocks, with each word appearing only once per block and each block containing both GP and NGP sentences as well as four additional filler sentences without target words. These blocks were administered to participants in separate individual sessions to prevent practice effects. Participants were instructed to read the sentences aloud and were told they could correct their reading if necessary. Monitoring assessed participants' ability to detect and correct reading errors across both sentence types. While Garden Path (GP) sentences were specifically designed to induce reading errors due to misleading contexts, errors also occurred in Non-Garden Path (NGP) sentences, particularly for less skilled readers. Therefore, monitoring abilities were assessed across all sentences to provide a comprehensive evaluation of error detection and correction capabilities. Four monitoring levels were defined: 0 point for no error detection, 1 point for detection without correction, where participants noticed the error (e.g., pausing or saying "this sounds strange") but did not correct it, 2 points for delayed correction after completing the sentence, and 3 points for immediate correction during reading. For each participant, the maximum possible monitoring score was calculated by multiplying the total number of reading errors (across both GP and NGP sentences) by 3, representing the highest level of monitoring efficiency. The monitoring score was then calculated as the sum of all monitoring points divided by this maximum possible score, yielding a weighted proportion that reflects the participant's error correction efficiency while accounting for individual differences in error rates. Together, detection and correction performance provide an index of monitoring efficiency during real-time reading. Procedure Data collection was conducted as part of a larger research project examining the relationships between decoding abilities, linguistic knowledge, executive functions, and reading comprehension. In total, 32 tests were administered across five sessions, each lasting approximately 45 minutes. Two of these sessions were conducted individually (including reading assessments and the Garden Path task), while the remaining sessions were administered in group settings (including reading comprehension tests, lexical tests, and Raven's Progressive Matrices). Data collection was carried out by seven researchers, all of whom were certified speech-language pathologists. All sessions took place during regular school hours within the school premises. Data analysis Path analysis was conducted to examine the relationships among lexical knowledge (vocabulary and morpho-lexical knowledge), reading skills (accuracy and speed), monitoring, and comprehension of narrative and informational texts. The model specified a theoretically driven sequence in which lexical knowledge predicted reading (accuracy and rate) skills and monitoring, and reading skills predicted monitoring, and all three domains were modeled as direct predictors of the two comprehension outcomes. The analysis was conducted in IBM AMOS (Version 30; IBM Corp.) using maximum likelihood with robust standard errors. Model fit was evaluated using standard indices (χ², CFI, TLI), and direct and indirect effects were examined. Results Descriptive statistics and correlations among all study variables are presented in Table 1. Performance levels were comparable across the two lexical measures and across the two comprehension tasks, suggesting balanced task difficulty across measures. Variability within each domain was similar, with no evidence of ceiling or floor effects. Reading accuracy was uniformly high, whereas reading speed and monitoring showed greater dispersion, reflecting individual differences in fluency and contextual regulation typical of fourth-grade readers. Mean scores on both lexical and reading measures were aligned with previous studies and established Hebrew norms (Bar-On et al., 2017 ; Lahmi-Kakon et al., 2020 ; Manshari & Bar-On, 2020 ; Shany et al., 2006 ). Together, these patterns confirm the reliability and ecological validity of the measures used in the present model. The correlation analysis revealed strong associations among the linguistic measures, with lexical and morpho-lexical knowledge closely related to each other and both moderately associated with reading comprehension. Reading accuracy and speed were also interrelated and showed moderate links with comprehension performance. The monitoring measure correlated with both comprehension tasks, suggesting shared variance across genres. Finally, comprehension of narrative and informational texts was positively and substantially related. Table 1: Descriptive Statistics and Correlations Among Study Variables Variable M SD 1 2 3 4 5 6 Lexical knowledge 1. Vocabulary [% correct] 70.92 17.95 — 2. Morpho-lexical Knowledge [% correct] 70.82 17.6 .72*** — Reading Variables 3. Reading Accuracy [% correct words] 96.49 2.99 .53*** .52*** — 4. Reading Speed [Words per minute (wpm)] 106.49 24.47 .48*** .39*** .62*** — Context Variables 5. Supra-lexical monitoring [% efficient corrections] 55.92 19.23 .54*** .47*** .54*** .38*** — Reading Comprehension 6. Informational Text [% correct answers] 66.25 21.23 .63*** .62*** .56*** .52*** .51*** — 7. Narrative Text [% correct answers] 66.94 18.12 .61*** .55*** .48*** .43*** .49*** .58*** Note. All measures are based on Hebrew tasks (see Method). *** p < .001 Path analysis examined the direct and indirect pathways through which linguistic and reading variables contribute to narrative and informational text comprehension in unpointed Hebrew. The path analysis model demonstrated an excellent fit to the data χ2(7) = 7.705, p = .359, CFI = 0.977, RMSEA = 0.033. The standardized path coefficients are presented in Table 2 and Fig. 1 . The path analysis revealed distinct pathways for narrative and informational text comprehension. Table 2 Direct, Indirect, and Total Effects of Linguistic, Reading, and Supra-lexical monitoring Variables on Narrative and Informational Text Comprehension Narrative Informational text Direct Indirect Total Direct Indirect Total Lexical knowledge 1. Vocabulary .495** .105* .600** .258* .186* .443** 2. Morpho-lexical Knowledge -- .02* .02* .260* .015* .28* Reading Variables 3. Reading Accuracy -- .08* .08* -- -- -- 4. Reading Speed -- -- -- .211* -- .211* Context Variables 5. Supra-lexical monitoring .220* -- .220* .175* -- .175* * p < .05, ** p < .01, *** p < .001 For narrative text comprehension, vocabulary was a strong predictor, showing both direct effects ( β = 0.495, p < 0.01) and indirect effects through monitoring ( β = 0.105, p < 0.05), yielding a total effect ( β = 0.600, p < 0.01). Monitoring directly influenced narrative comprehension ( β = 0.220, p < 0.05). Notably, morpho-lexical knowledge did not show significant direct or indirect effects on narrative text comprehension. The model explained 41% of the variance in narrative comprehension. For informational text comprehension, a broader set of predictors was involved. Vocabulary showed direct ( β = 0.258, p < 0.05) and indirect effects ( β = 0.186, p < 0.05), though with a smaller total effect ( β = 0.443, p < 0.01) than for narrative texts. However, unlike narrative comprehension, morpho-lexical knowledge predicted informational text comprehension through both direct ( β = 0.260, p < 0.05) and indirect effects ( β = 0.015, p < 0.05). Additionally, reading speed directly contributed ( β = 0.211, p < 0.05). Monitoring contributed significantly ( β = 0.175, p < 0.05), confirming its importance across genres. The model explained 51% of the variance in informational comprehension. With respect to relations among the predictor variables, reading accuracy significantly predicted monitoring (β = 0.344, p < 0.01). Lexical knowledge showed both direct (β = 0.357, p < 0.01) and indirect effects (β = 0.123, p < 0.05) on monitoring. Overall, the model revealed both shared and distinct pathways to comprehension across genres, with monitoring contributing directly to comprehension in both text types. Discussion The present study examined how lexical knowledge, decoding skills, and supra-lexical monitoring processes contribute to reading comprehension of narrative and informational texts among Hebrew-speaking fourth graders. The resulting model demonstrated excellent fit and explained substantial variance in comprehension across both text genres, highlighting the importance of integrating these processes within a single explanatory framework. Importantly, the pattern of findings aligns closely with the multi-level architecture proposed in the Combinatorial Model, with lexical knowledge supporting word identification processes, and supra-lexical monitoring coordinating the integration of meaning during reading. In this sense, a central contribution of the study lies in identifying supra-lexical monitoring as a regulatory mechanism linking lower-level reading processes with higher-level comprehension. Importantly, performance levels on the narrative and informational comprehension tasks were highly comparable, with nearly identical mean accuracy scores (narrative: M = 66.94%, SD = 18.12; informational: M = 66.25%, SD = 21.23). This pattern is not fully consistent with much of the literature, which often reports lower performance for informational texts due to their greater lexical and conceptual demands, although findings are not entirely uniform. In the present context, however, this equivalence constitutes a methodological advantage, as it rules out differences in task difficulty as an explanation for the observed divergence in predictive pathways. Instead, the findings point to systematic differences in how readers allocate linguistic and cognitive resources when processing texts that vary in discourse structure, lexical density, and conceptual demands. Overall, the model accounted for more variance in informational text comprehension than in narrative comprehension (51% vs. 41%, respectively), suggesting that informational texts recruit a broader and more differentiated constellation of linguistic and reading-related skills, consistent with their higher lexical density, morphological complexity, and conceptual demands. At the same time, narrative and informational comprehension were strongly correlated at the bivariate level (r = .58, p < .001), indicating a substantial shared foundation. However, once lexical, decoding, and monitoring variables were entered into the model, this association was markedly reduced (to approximately r ≈ .20), suggesting that much of the apparent overlap between genres reflects common underlying mechanisms rather than a unitary comprehension ability. These findings support a view of reading comprehension as grounded in shared lexical and supra-lexical processes, while also revealing genre-specific configurations that reflect the distinct linguistic demands of narrative and informational texts. In the sections that follow, we examine these shared and unique contributors in turn, beginning with the role of lexical knowledge as the core engine of comprehension. Lexical knowledge as a central resource for reading comprehension The present findings confirm the central role of lexical knowledge in reading comprehension across text genres, in line with extensive previous research and with both the Lexical Quality Hypothesis (Perfetti, 2007 ; Perfetti & Stafura, 2014 ) and Kim’s Direct and Indirect Effects Model (DIER, Kim et al., 2021 ). Consistent with previous studies showing that vocabulary predicts comprehension beyond decoding in both narrative and informational texts (Cruz Neri et al., 2023 ; Protopapas et al., 2013 ; Santos et al., 2017 ; Wu et al., 2020 ), lexical knowledge in the present model emerged as a strong predictor of comprehension across genres. Vocabulary showed substantial total effects on comprehension, with a stronger contribution to the narrative text (β = .60, p < .01) and a moderate but robust contribution to the informational text (β = .44, p < .01). Morpho-lexical knowledge made a significant and selective contribution to informational text comprehension (total effect β = .28, p < .05), while showing no meaningful contribution to narrative comprehension. These effects included both direct and indirect paths mediated through supra-lexical monitoring, indicating that vocabulary knowledge supports comprehension through efficient semantic access and higher-order integration. The pattern of results, however, diverges from much of the existing literature regarding genre differences in lexical contributions. Several studies have reported comparable vocabulary effects across narrative and informational texts (Santos et al., 2017 ; Wu et al., 2020 ), whereas others have found stronger vocabulary effects for informational texts, particularly from the middle elementary grades onward (Hannon, 2022 ; Liebfreund, 2021 ; Yildirim et al., 2011 ). This divergence is plausibly related to the nature of the vocabulary measures used. Studies reporting an informational advantage have often relied on vocabulary tasks emphasizing academic or content-specific lexical knowledge, thereby increasing overlap between the vocabulary assessment and the demands of informational texts (Best et al., 2008 ; Hannon, 2022 ). In the present study, vocabulary was assessed using a collocation completion task designed to capture the breadth and conventionality of lexical knowledge in context, indexing readers’ sensitivity to how words typically co-occur in natural language. This type of knowledge is characteristic of the literate lexicon that develops during the school years, reflecting increasing exposure to written language and sensitivity to conventionalized word combinations (Ellis, 2008 ; Nippold, 2007 ). The items in the task span a wide range of lexical registers and discourse contexts, including everyday expressions (e.g., “helplessness”, “handwriting”), lexical items common in children’s literature (e.g., “royal throne” “(they live) happily ever after”), and collocations with a more informational or academic flavor (e.g., "side effects” “earthquake”). As such, this measure does not target a specific genre or content domain but rather reflects general lexical quality. This broad sampling of lexical knowledge likely explains why vocabulary showed strong effects across both genres and particularly robust effects for narrative comprehension, where rapid access to familiar and conventionalized lexical combinations facilitates fluent meaning construction and supports the building of coherent event-based representations (Graesser et al., 1994 ; Nation, 2001 ; Wray, 2002 ). The inclusion of a morpho-lexical measure extends the assessment of lexical quality beyond surface familiarity and usage-based knowledge. The task assesses readers’ ability to derive words from a shared base, reflecting their capacity to analyze morphological structure and to exploit systematic form–meaning relations in support of comprehension (Deacon et al., 2014 ; Nagy et al., 2006 ). The task items include derivations that are frequently used to condense information and express abstract relations, such as passive verb forms (e.g., We have tried to catch the mouse. At the end of the day, he was caught ), derivational adjectives (e.g., a country with many mountains is mountainous ), and complex noun constructions based on action nouns (e.g., The jackals howled all night. We could not sleep because of the jackals’ howling ). Because informational discourse relies heavily on morphologically complex forms of this kind (Berman, 2008 ; Berman & Nir-Sagiv, 2009 ; Fang & Schleppegrell, 2010 ), it is therefore not surprising that morpho-lexical knowledge showed a selective contribution to informational text comprehension. These findings point to a division of labor between vocabulary and morpho-lexical knowledge: whereas vocabulary supports comprehension across genres, morpho-lexical knowledge appears to be especially relevant for informational texts. This pattern highlights the importance of considering the internal structure of the lexicon when modeling genre-specific comprehension. Beyond their contribution to comprehension, both lexical measures were also related to reading processes themselves. In the model, morpho-lexical knowledge contributed to reading accuracy, supporting the view that morphological analysis facilitates word identification in unpointed Hebrew by constraining possible lexical candidates and supporting morpho-orthographic identification (Bar-On & Ravid, 2011 ; Share & Bar-On, 2018 ). Vocabulary knowledge, in turn, was associated with supra-lexical monitoring efficiency, indicating that readers with stronger vocabulary skills exhibit more efficient conflict detection and meaning revision (e.g., Cartwright et al., 2020 ; McNamara et al., 2011 ). In line with DIER model (Kim et al., 2021 ), these findings reinforce the idea that lexical knowledge supports reading comprehension both directly, by enabling efficient meaning construction, and indirectly, by shaping the quality of word identification and the effectiveness of supra-lexical regulation. Contribution of decoding skills to reading comprehension Decoding skills were assessed through oral reading of connected texts rather than isolated words. This choice reflects the characteristics of Hebrew orthography, in which word identification in the unpointed script relies heavily on contextual information, making connected text a more ecologically valid medium for assessing reading processes. At the same time, the use of text-level measures raises the possibility that decoding indices may incorporate higher-level processes. To address this concern, reading accuracy and reading speed were analyzed separately, allowing us to distinguish between components of word identification within connected text and to avoid conflating them into a single fluency measure. Overall, decoding-related reading skills played a relatively limited role in explaining individual differences in reading comprehension in the present sample. This pattern is consistent with models proposing that decoding accuracy becomes less predictive of comprehension in the middle elementary grades, as variability in comprehension increasingly reflects higher-level linguistic and regulatory processes (Cain & Oakhill, 2008 ; Catts et al., 2005 ; García & Cain, 2014 ; Kim et al., 2021 ). Within this overall pattern, the only direct decoding effect emerged for reading speed, and only for informational text comprehension. This selective effect suggests that processing efficiency continues to matter under conditions of increased linguistic density and conceptual load (Best et al., 2008 ; Eason et al., 2012 ). From the perspective of Kintsch’s construction–integration framework (Kintsch, 1988 ), informational comprehension places heavier demands on building and integrating a dense textbase representation, where efficient processing of successive propositions is critical. When processing demands are high, slower reading may constrain the reader’s ability to maintain and integrate multiple informational units. Narrative comprehension, by contrast, relies more strongly on the construction of a situation model grounded in causal and temporal relations among events, which can be supported by lexical knowledge and background schemas even when reading proceeds relatively slowly. In contrast to reading speed, reading accuracy did not exert a direct effect on comprehension in either genre. At this stage of development, most children have already achieved reliable word identification, as evidenced by uniformly high accuracy scores (M = 96.49%, SD = 2.99), leaving little variability in decoding accuracy to account for individual differences in reading comprehension. Reading accuracy, however, showed a significant indirect contribution to comprehension through monitoring ability. This pattern indicates that accurate word identification serves as a foundational skill that supports readers’ ability to detect and resolve inconsistencies during reading. It may also reflect differences in readers’ orientation to accuracy, such that those who attend more closely to producing accurate word forms are also more likely to notice mismatches and initiate correction when errors occur. Importantly, the differential contributions of accuracy and speed do not reflect a trade-off between these components. Although accuracy and speed were moderately to strongly correlated (r = .62, p < .001), indicating substantial shared variance, each showed distinct pathways within the model. Contribution of supra-lexical monitoring processes Supra-lexical monitoring, as indexed by the Garden Path task, showed a significant and comparable direct contribution to both narrative and informational comprehension. Although the magnitude of this effect was modest, it remained significant after accounting for lexical knowledge and decoding, indicating that monitoring explains unique variance in comprehension beyond foundational reading skills. This finding aligns with meta-analytic evidence demonstrating a stable association between executive processes and reading comprehension across development (Follmer, 2018 ), as well as with studies showing that reading-specific executive tasks contribute uniquely to comprehension (Cartwright et al., 2020 ; Peng et al., 2024 ). The absence of a genre interaction did not support the hypothesis that monitoring would show a stronger contribution to informational than to narrative comprehension. In line with Escobar and Espinoza ( 2025 ), the present findings indicate that monitoring is not selectively tied to informational reading. While informational texts may increase demands at the level of text-base integration, narrative texts may impose regulatory demands at the level of situation-model updating, including revising causal interpretations and character intentions (Graesser et al., 1994 ; Kintsch, 1988 ; Kintsch & Kintsch, 2005 ). Thus, the absence of a genre interaction does not imply equivalent processing demands but rather suggests that supra-lexical monitoring operates across representational levels, with genre differences emerging in locus rather than magnitude. This pattern may be particularly pronounced in Hebrew, where pervasive lexical ambiguity in the unpointed script requires continuous reliance on contextual monitoring across reading situations, potentially reducing genre-based differences in the magnitude of monitoring demands. Finally, the mediating role of monitoring provides a theoretical insight. Monitoring partially mediated the relation between lower-level reading skills and comprehension, suggesting that reading and comprehension are best conceptualized as components of a continuous regulatory system rather than discrete stages. Within both the Combinatorial Model and the Lexical Quality framework, monitoring can be understood as a supra-lexical mechanism that coordinates bottom-up word identification with top-down contextual integration, enabling flexible revision when lexical interpretations conflict with context. Taken together, these findings support the view that supra-lexical monitoring functions as a bridging mechanism through which lexical quality and decoding efficiency are translated into coherent text comprehension. Conclusions, limitations and implications The present study advances an integrative account of reading comprehension by demonstrating how lexical knowledge, decoding processes, and supra-lexical monitoring jointly contribute to comprehension across text genres. The results reveal both shared and genre-specific pathways to comprehension, indicating that narrative and informational texts do not differ simply in overall difficulty, but rather impose distinct patterns of demands across representational levels, with each genre engaging different configurations of lexical, decoding, and supra-lexical processes. Crucially, supra-lexical monitoring emerged as a domain-general regulatory mechanism that operates across genres, linking lower-level reading processes with higher-level interpretation. These findings extend both the Lexical Quality Hypothesis and the Combinatorial Model by highlighting the role of context-sensitive regulation in coordinating multiple levels of reading. Several limitations of the present study should be considered alongside directions for future research. First, the sample was restricted to fourth-grade readers, and the findings therefore reflect a specific stage in the development of reading proficiency, at which basic word identification has largely stabilized but higher-level processes continue to develop. Also, the study was conducted in Hebrew, an orthography characterized by pervasive lexical ambiguity due to the unpointed script. This combination of developmental stage and orthographic characteristics may shape the role and relative importance of supra-lexical monitoring processes. Future research should therefore examine whether the observed patterns generalize across developmental stages and orthographies, including both earlier and later phases of reading acquisition and languages with different degrees of transparency and ambiguity. Second, the study relied on a single text for each genre. Although the texts were carefully selected and matched, genre-related effects may be influenced by text-specific characteristics, and the use of multiple texts per genre would allow for a more robust assessment of genre-related processing demands. Finally, supra-lexical monitoring was assessed via a single task. While the Garden Path paradigm provides a well-established measure of real-time conflict detection and revision, future studies could benefit from incorporating additional measures to capture a broader range of monitoring processes. The findings have implications for reading instructions. First, they highlight the importance of fostering supra-lexical monitoring processes in reading development. Instruction should support students’ regulation of understanding by detecting inconsistencies, revising interpretations, and using contextual information to resolve ambiguity, thereby supporting the integration of word-level and text-level processes. Second, instructional approaches should be sensitive to genre-specific demands. Rather than viewing informational texts as uniformly more difficult, educators should recognize that different text types engage different configurations of cognitive and linguistic processes. Third, the differentiated contribution of decoding components indicates that fluency instruction should move beyond general practice toward targeted support that considers the interaction between processing efficiency and text characteristics. Finally, the findings underscore the importance of integrating lexical and morphological instruction within reading curricula, particularly for supporting comprehension of informational texts. Declarations Author Contribution SP and AB contributed to the conception and design of the study, developed the theoretical framework, conducted the statistical analyses, interpreted the findings, and drafted and revised the manuscript. ML and OL contributed to data collection, coding, and data curation as graduate research students whose research projects provided the empirical basis for the present study. SP and AB jointly supervised the research process. All authors reviewed the final manuscript. Acknowledgement The authors thank Liron Lerdan, Dafna Biton, Shlomit Ostri, and Noa Morag for their careful work in data collection and coding. We are also grateful to Haya Fogel-Grinvald for statistical consultation and support with the analyses. Finally, we gratefully acknowledge the late Dr. Ronit Levy, who contributed to the early conceptualization of the broader research project from which this study emerged. Her thoughtful perspective and intellectual contribution helped shape the initial thinking behind this work. Data Availability The data that support the findings of this study are not publicly available due to privacy and ethical restrictions involving child participants and school-based assessment data. Data may be made available from the corresponding author upon reasonable request and subject to applicable ethical approvals and data-sharing agreements. References Baretta, L., Tomitch, L. M. B., MacNair, N., Lim, V. K., & Waldie, K. E. (2009). Inference making while reading narrative and expository texts: An ERP study. Psychology & Neuroscience , 2 (2), 137–145. https://doi.org/10.3922/j.psns.2009.2.005 Bar-On, A., Dattner, E., & Braun-Peretz, O. (2019). Resolving homography: The role of post-homograph context in reading aloud ambiguous sentences in Hebrew. Applied Psycholinguistics , 40 , 1405–1420. https://doi.org/10.1017/S0142716419000316 Bar-On, A., Dattner, E., & Ravid, D. (2017). Context effects on heterophonic-homography resolution in learning to read Hebrew. Reading and Writing , 30 (3), 463–487. https://doi.org/10.1007/s11145-016-9685-1 Bar-On, A., Oron, T., & Peleg, O. (2021). Semantic and syntactic constraints in resolving homography: A developmental study in Hebrew. Reading and Writing , 34 (8), 2103–2126. https://doi.org/10.1007/s11145-021-10129-6 Bar-On, A., & Ravid, D. (2011). Morphological analysis in learning to read pseudowords in Hebrew. Applied Psycholinguistics , 32 (3), 553–581. https://doi.org/10.1017/S014271641100021X Bellocchi, S., Priolo, D., & Bonifacci, P. (2025). The simple view of reading in monolingual and language-minority bilingual children learning to read in French or Italian: Evidence from a direct cross-linguistic comparison study. Journal of Research in Reading , 48 (3), 259–277. https://doi.org/10.1111/1467-9817.70007 Berman, R. A. (2008). The psycholinguistics of developing text construction. Journal of Child Language , 35 (4), 735–771. https://doi.org/10.1017/S0305000908008787 Berman, R. A. (2016). Linguistic literacy and later language development. In J. Perera, M. Aparici, E. Rosado, & N. Salas (Eds.), Written and Spoken Language Development across the Lifespan: Essays in Honour of Liliana Tolchinsky (Vol. 11, pp. 181–200). Springer International Publishing. https://doi.org/10.1007/978-3-319-21136-7_12 Berman, R. A., & Nir-Sagiv, B. (2009). Clause packaging in narratives: A crosslinguistic developmental study. In J. Guo, E. Lieven, N. Budwig, S. Ervin-Tripp, K. Nakamura, & S. Ozcaliskan (Eds.), Crosslinguistic approaches to the psychology of language: Research in the tradition of Dan Isaac Slobin (pp. 149–162). Psychology. Berman, R. A., & Slobin, D. I. (1994). Relating events in narrative: A crosslinguistic developmental study . Psychology. Best, R. M., Floyd, R. G., & McNamara, D. S. (2008). Differential competencies contributing to children’s comprehension of narrative and expository texts. Reading Psychology , 29 (2), 137–164. https://doi.org/10.1080/02702710801963951 Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review , 108 (3), 624–652. https://doi.org/10.1037/0033-295X.108.3.624 Cain, K., & Oakhill, J. (2008). Children’s comprehension problems in oral and written language: A cognitive perspective . Guilford Press. Cartwright, K. B., Marshall, T. R., & Hatfield, N. A. (2020). Concurrent and longitudinal contributions of a brief assessment of reading-specific executive function to reading comprehension in first and second grade students. Mind Brain and Education , 14 (2), 114–123. https://doi.org/10.1111/mbe.12236 Catts, H. W., Hogan, T. P., & Adlof, S. M. (2005). Developmental changes in reading and reading disabilities. In H. W. Catts, & A. G. Kamhi (Eds.), The connections between language and reading disabilities (pp. 25–40). Lawrence Erlbaum Associates. Cervetti, G. N., Bravo, M. A., Hiebert, E. H., Pearson, P. D., & Jaynes, C. A. (2009). Text genre and science content: Ease of reading, comprehension, and reader preference. Reading Psychology , 30 (6), 487–511. https://doi.org/10.1080/02702710902733550 Chall, J. S. (1983). Stages of Reading Development . McGraw-Hill. Clinton, V., Taylor, T., Bajpayee, S., Davison, M. L., Carlson, S. E., & Seipel, B. (2020). Inferential comprehension differences between narrative and expository texts: A systematic review and meta-analysis. Reading and Writing , 33 (9), 2223–2248. https://doi.org/10.1007/s11145-020-10044-2 Cruz Neri, N., Bernholt, S., Härtig, H., Schmitz, A., & Retelsdorf, J. (2023). Cognitive and motivational characteristics as predictors of students’ expository versus narrative text comprehension. European Journal of Psychology of Education , 39 (2), 885–905. https://doi.org/10.1007/s10212-023-00717-1 Deacon, S. H., Kieffer, M. J., & Laroche, A. (2014). The relation between morphological awareness and reading comprehension: Evidence from mediation and longitudinal models. Scientific Studies of Reading , 18 (6), 432–451. https://doi.org/10.1080/10888438.2014.926907 Dickens, R. H., & Meisinger, E. B. (2017). Examining the effects of reading modality and passage genre on reading comprehension in middle school students. Reading Psychology , 38 (3), 321–347. https://doi.org/10.1080/02702711.2016.1263701 Duke, N. K., & Cartwright, K. B. (2021). The science of reading progresses: Communicating advances beyond the simple view of reading. Reading Research Quarterly , 56 (S1), S25–S44. https://doi.org/10.1002/rrq.411 Eason, S. H., Goldberg, L. F., Young, K. M., Geist, M. C., & Cutting, L. E. (2012). Reader–text interactions: How differential text and question types influence cognitive skills needed for reading comprehension. Journal of Educational Psychology , 104 (3), 515–528. https://doi.org/10.1037/a0027182 Ellis, N. C. (2008). Usage-based and form-focused language acquisition: The associative learning of constructions, learned attention, and the limited L2 endstate. In P. Robinson, & N. C. Ellis (Eds.), Handbook of Cognitive Linguistics and Second Language Acquisition (pp. 372–405). Routledge. Escobar, J. P., & Espinoza, V. (2025). Direct and indirect effects of inhibition, working memory and cognitive flexibility on reading comprehension of narrative and expository texts: Same or different effects? Reading and Writing Quarterly , 41 (2), 176–192. https://doi.org/10.1080/10573569.2024.2400993 Fang, Z., & Schleppegrell, M. J. (2010). Disciplinary literacies across content areas: Supporting secondary reading through functional language analysis. Journal of Adolescent & Adult Literacy , 53 (7), 587–597. https://doi.org/10.1598/JAAL.53.7.6 Follmer, D. J. (2018). Executive function and reading comprehension: A meta-analytic review. Educational Psychologist , 53 (1), 42–60. https://doi.org/10.1080/00461520.2017.1309295 Foorman, B. R., Petscher, Y., & Bishop, M. D. (2012). The incremental variance of morphological knowledge to reading comprehension in grades 3–10 beyond prior reading comprehension, spelling, and text reading efficiency. Learning and Individual Differences , 22 (6), 792–798. https://doi.org/10.1016/j.lindif.2012.07.009 Frazier, L., & Rayner, K. (1982). Making and correcting errors during sentence comprehension: Eye movements in the analysis of structurally ambiguous sentences. Cognitive Psychology , 14 (2), 178–210. https://doi.org/10.1016/0010-0285(82)90008-1 García, J. R., & Cain, K. (2014). Decoding and reading comprehension: A meta-analysis to identify which reader and assessment characteristics influence the strength of the relationship in English. Review of Educational Research , 84 (1), 74–111. https://doi.org/10.3102/0034654313499616 Graesser, A. C., McNamara, D. S., & Kulikowich, J. M. (2011). Coh-metrix: Providing multilevel analyses of text characteristics. Educational Researcher , 40 (5), 223–234. https://doi.org/10.3102/0013189X11413260 Graesser, A. C., Singer, M., & Trabasso, T. (1994). Constructing inferences during narrative text comprehension. Psychological Review , 101 (3), 371–395. https://doi.org/10.1037/0033-295X.101.3.371 Hannon, B. (2022). Children’s comprehension of narrative and expository texts: The contributions of word decoding and knowledge integration skills vary within and between text types. Journal of Education and Training Studies , 10 (4), 1. https://doi.org/10.11114/jets.v10i4.5465 Hoover, W. A. (2023). The simple view of reading and its broad types of reading difficulties. Reading and Writing , 37 (9), 2277–2298. https://doi.org/10.1007/s11145-023-10471-x Hoover, W. A., & Gough, P. B. (1990). The simple view of reading. Reading and Writing , 2 (2), 127–160. https://doi.org/10.1007/BF00401799 Joshi, R. M. (2018). Simple view of reading (SVR) in different orthographies: Seeing the forest with the trees. In T. Lachmann, & T. Weis (Eds.), Reading and dyslexia: From basic functions to higher order cognition (pp. 71–80). Springer. Joshi, R. M., Ji, X. R., Breznitz, Z., Amiel, M., & Yulia, A. (2015). Validation of the Simple View of Reading in Hebrew—A Semitic Language. Scientific Studies of Reading , 19 (3), 243–252. https://doi.org/10.1080/10888438.2015.1010117 Kim, Y. S. G., Quinn, J. M., & Petscher, Y. (2021). What is text reading fluency and is it a predictor or an outcome of reading comprehension? A longitudinal investigation. Developmental Psychology , 57 (5), 718–732. https://doi.org/10.1037/dev0001167 Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review , 95 (2), 163–182. https://doi.org/10.1037/0033-295X.95.2.163 Kintsch, W., & Kintsch, E. (2005). Comprehension. Children’s reading comprehension and assessment . Routledge. Koriat, A., & Goldsmith, M. (1996). Monitoring and control processes in memory. Psychological Review , 103 , 490–517. Kraal, A., Koornneef, A. W., Saab, N., & van den Broek, P. W. (2018). Processing of expository and narrative texts by low- and high-comprehending children. Reading and Writing , 31 (9), 2017–2040. https://doi.org/10.1007/s11145-017-9789-2 Lahmi-Kakon, L., Ben-Zvi, G., & Bar-On, A. (2020). Derived word completion task for assessment of morpho-lexical knowledge in 3rd–7th grade. DASH BARESHET: The Israeli Journal of Language Speech and Hearing Disorders , 39 . Levesque, K. C., Kieffer, M. J., & Deacon, S. H. (2017). Morphological awareness and reading comprehension: Examining mediating factors. Journal of Experimental Child Psychology , 160 , 1–20. https://doi.org/10.1016/j.jecp.2017.02.015 Liebfreund, M. D. (2021). Cognitive and Motivational Predictors of Narrative and Informational Text Comprehension. Reading Psychology , 42 (2), 177–196. https://doi.org/10.1080/02702711.2021.1888346 Liu, Y., Groen, M. A., & Cain, K. (2024). The association between morphological awareness and reading comprehension in children: A systematic review and meta-analysis. Educational Research Review , 42 , 100571. https://doi.org/10.1016/j.edurev.2023.100571 Manshari, M., & Bar-On, A. (2020). Collocation completion task: Lexical knowledge assessment tool. DASH BARESHET: The Israeli Journal of Language Speech and Hearing Disorders , 39 . Mar, R. A., Li, J., Nguyen, A. T. P., & Ta, C. P. (2021). Memory and comprehension of narrative versus expository texts: A meta-analysis. Psychonomic Bulletin & Review , 28 (3), 732–749. https://doi.org/10.3758/s13423-020-01853-1 McNamara, D. S., Ozuru, Y., & Floyd, R. G. (2011). Comprehension challenges in the fourth grade: The roles of text cohesion, text genre, and readers’ prior knowledge. International Electronic Journal of Elementary Education , 4 (1), 229–257. Meyer, B. J. F., & Ray, M. N. (2017). Structure strategy interventions: Increasing reading comprehension of expository text. International Electronic Journal of Elementary Education , 4 (1), 127–152. Miller, A., Swett, K., Burns, S., Davis, N., Hoeft, F., Petrill, S. A., & Cutting, L. E. (2013). Comprehending expository texts: The dynamic neurobiological correlates of building a coherent text representation. Frontiers in Human Neuroscience , 7 , 853. https://doi.org/10.3389/fnhum.2013.00853 Nagy, W., Berninger, V. W., & Abbott, R. D. (2006). Contributions of morphology beyond phonology to literacy outcomes of upper elementary and middle-school students. Journal of Educational Psychology , 98 (1), 134–147. https://doi.org/10.1037/0022-0663.98.1.134 Nation, I. S. P. (2001). Learning Vocabulary in Another Language . Cambridge University Press. National Authority for Measurement and Evaluation in Education. (2014). Meitzav: Hebrew reading comprehension assessments for Grade 5 (narrative and informational text units) . Ministry of Education. https://rama.edu.gov.il National Reading Panel (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction (Nos. 00–4769). National Institute of Child Health and Human Development. https://www.nichd.nih.gov/publications/pubs/nrp/Documents/report.pdf Nelson, T. O. (1990). Metamemory: A theoretical framework and new findings. In G. H. Bower (Ed.), Psychology of Learning and Motivation (Vol. 26, pp. 125–173). Academic. Neuman, S. B., Kaefer, T., & Pinkham, A. (2025). Is narrative in printed text primary for knowledge-building? An analysis of genre and medium. Reading and Writing , 39 (1), 91–119. https://doi.org/10.1007/s11145-025-10634-y Nippold, M. A. (2007). Later language development: School-age children, adolescents, and young adults . Pro-Ed. Novick, J. M., Trueswell, J. C., & Thompson-Schill, S. L. (2005). Cognitive control and parsing: Reexamining the role of Broca’s area in sentence comprehension. Cognitive Affective & Behavioral Neuroscience , 5 (3), 263–281. https://doi.org/10.3758/CABN.5.3.263 Ouellette, G. P. (2006). What’s meaning got to do with it: The role of vocabulary in word reading and reading comprehension. Journal of Educational Psychology , 98 (3), 554–566. https://doi.org/10.1037/0022-0663.98.3.554 Padeliadu, S., & Antoniou, F. (2014). The relationship between reading comprehension, decoding, and fluency in Greek: A cross-sectional study. Reading and Writing Quarterly , 30 (1), 1–31. https://doi.org/10.1080/10573569.2013.758932 Peng, P., Liu, Y., Cartwright, K., Goodrich, M., Koziol, N., Ma, C., & Whitmarsh, C. (2024). The role of domain-general, behavioral, and reading-specific executive function in reading comprehension: Does context-specific executive function matter? Scientific Studies of Reading , 28 (6), 713–736. https://doi.org/10.1080/10888438.2024.2409635 Perfetti, C. A. (2007). Reading ability: Lexical quality to comprehension. Scientific Studies of Reading , 11 (4), 357–383. https://doi.org/10.1080/10888430701530730 Perfetti, C. A., & Hart, L. (2002). The lexical quality hypothesis. In L. T. Verhoeven, C. Elbro, & P. Reitsma (Eds.), Precursors of functional literacy (Vol. 11, pp. 67–86). John Benjamins Publishing. Perfetti, C. A., & Stafura, J. (2014). Word knowledge in a theory of reading comprehension. Scientific Studies of Reading , 18 (1), 22–37. https://doi.org/10.1080/10888438.2013.827687 Primor, L., Pierce, M. E., & Katzir, T. (2011). Predicting reading comprehension of narrative and expository texts among Hebrew-speaking readers with and without a reading disability. Annals of Dyslexia , 61 (2), 242–268. https://doi.org/10.1007/s11881-011-0059-8 Protopapas, A., Mouzaki, A., Sideridis, G. D., Kotsolakou, A., & Simos, P. G. (2013). The role of vocabulary in the context of the simple view of reading. Reading and Writing Quarterly , 29 (2), 168–202. https://doi.org/10.1080/10573569.2013.758569 Protopapas, A., Sideridis, G. D., Mouzaki, A., & Simos, P. G. (2007). Development of lexical mediation in the relation between reading comprehension and word reading skills in Greek. Scientific Studies of Reading , 11 (3), 165–197. https://doi.org/10.1080/10888430701344322 Quinn, J. M., Wagner, R. K., Petscher, Y., & Lopez, D. (2015). Developmental relations between vocabulary knowledge and reading comprehension: A latent change score modeling study. Child Development , 86 (1), 159–175. https://doi.org/10.1111/cdev.12292 Rassel, A., Facon, B., & Casalis, S. (2021). Morphological awareness and learning to read: Impact of socio-economic status in French third graders. Journal of Research in Reading , 44 (1), 228–246. https://doi.org/10.1111/1467-9817.12321 Raven, J., Prieler, J., & Fischer, G. (1996). Standard progressive matrices . Oxford Psychologists. Ravid, D., & Berman, R. A. (2010). Developing Noun Phrase Complexity at School Age: A Text-Embedded Cross-Linguistic Analysis. First Language , 30 (1), 3–26. https://doi.org/10.1177/0142723709350531 Ravid, D., & Mashraki, Y. E. (2007). Prosodic reading, reading comprehension and morphological skills in Hebrew-speaking fourth graders. Journal of Research in Reading , 30 (2), 140–156. https://doi.org/10.1111/j.1467-9817.2007.00340.x Santos, S., Cadime, I., Viana, F. L., Chaves-Sousa, S., Gayo, E., Maia, J., & Ribeiro, I. (2017). Assessing reading comprehension with narrative and expository texts: Dimensionality and relationship with fluency, vocabulary and memory. Scandinavian Journal of Psychology , 58 (1), 1–8. https://doi.org/10.1111/sjop.12335 Scarborough, H. S. (2001). Connecting early language and literacy to later reading (dis) abilities: Evidence, theory, and practice. In F. Fletcher-Campbell, J. Soler, & G. Reid (Eds.), Approaching difficulties in literacy development: Assessment, pedagogy and programmes (pp. 97–110). SAGE Publications Ltd. Shany, M., Lahman, D., Shalem, T., Bahat, A., & Zayger, T. (2006). Alef ad taf: A system for diagnosing disabilities in the processes of reading and writing according to national norms . Yesod Publishing. Share, D. L. (2008). On the Anglocentricities of current reading research and practice: The perils of overreliance on an outlier orthography. Psychological Bulletin , 134 (4), 584–615. https://doi.org/10.1037/0033-2909.134.4.584 Share, D. L. (2025). Blueprint for a universal theory of learning to read: The combinatorial model. Reading Research Quarterly , 60 (2), 1–51. https://doi.org/10.1002/rrq.603 Share, D. L., & Bar-On, A. (2018). Learning to read a Semitic abjad: The triplex model of Hebrew reading development. Journal of Learning Disabilities , 51 (5), 444–453. https://doi.org/10.1177/0022219417718198 Shimron, J., & Sivan, T. (1994). Reading proficiency and orthography evidence from Hebrew and English. Language Learning , 44 (1), 5–27. https://doi.org/10.1111/j.1467-1770.1994.tb01447.x Simpson, I. C., Moreno-Pérez, F. J., & Rodríguez-Ortiz, I. (2019). los R., Valdés-Coronel, M., & Saldaña, D. The effects of morphological and syntactic knowledge on reading comprehension in spanish speaking children. Reading and Writing , 33 (2), 329–348. https://doi.org/10.1007/s11145-019-09964-5 Snow, C. E. (2018). Simple and not-so-simple views of reading. Remedial and Special Education , 39 (5), 313–316. https://doi.org/10.1177/0741932518770288 Tong, X., Deacon, S. H., Kirby, J. R., Cain, K., & Parrila, R. (2011). Morphological awareness: A key to understanding poor reading comprehension in English. Journal of Educational Psychology , 103 (3), 523–534. https://doi.org/10.1037/a0023495 Tong, X., Tong, X., & McBride, C. (2017). Unpacking the relation between morphological awareness and Chinese word reading: Levels of morphological awareness and vocabulary. Contemporary Educational Psychology , 48 , 167–178. https://doi.org/10.1016/j.cedpsych.2016.07.003 Uysal, P. K., & Bilge, H. (2018). An investigation on the relationship between reading fluency and level of reading comprehension according to the type of texts. International Electronic Journal of Elementary Education , 11 (2), 161–172. Vaknin-Nusbaum, V., Sarid, M., & Shimron, J. (2015). Morphological awareness and reading in second and fifth grade: Evidence from Hebrew. Reading and Writing , 29 (2), 229–244. https://doi.org/10.1007/s11145-015-9587-7 van Silfhout, G., Evers-Vermeul, J., & Sanders, T. (2015). Connectives as processing signals: How students benefit in processing narrative and expository texts. Discourse Processes , 52 (1), 47–76. https://doi.org/10.1080/0163853X.2014.905237 Wechsler, D. (2012). Wechsler intelligence scale for children–fourth edition (WISC-IV), Hebrew version . Wray, A. (2002). Formulaic Language and the Lexicon . Cambridge University Press. Wu, Y., Barquero, L. A., Pickren, S. E., Taboada Barber, A., & Cutting, L. E. (2020). The relationship between cognitive skills and reading comprehension of narrative and expository texts: A longitudinal study from Grade 1 to Grade 4. Learning and Individual Differences , 80 , 101848. https://doi.org/10.1016/j.lindif.2020.101848 Yildirim, K., Yildiz, M., & Ateş, S. (2011). Is vocabulary a strong variable predicting reading comprehension and does the prediction degree of vocabulary vary according to text types? Educational Sciences: Theory & Practice , 11 (3), 1541–1547. Yoo, Y. (2024). On the dynamics of inferential behavior while reading expository and narrative texts. Brain Sciences , 14 (5), 428. https://doi.org/10.3390/brainsci14050428 Zabrucky, K. M., & Moore, D. (1999). Influence of text genre on adults’ monitoring of understanding and recall. Educational Gerontology , 25 (8), 691–710. https://doi.org/10.1080/036012799267440 Zhang, D., Ke, S., Echo, & Mo, Y. (2023). Morphology in reading comprehension among school-aged readers of English: A synthesis and meta-analytic structural equation modeling study. Journal of Educational Psychology , 115 (5), 683–699. https://doi.org/10.1037/edu0000797 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9574360","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633648547,"identity":"afcb89cc-2c2e-470c-bd82-8eb297d61396","order_by":0,"name":"Smadar Zohar Patael","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYJACCRDBjy4oQ1CLZBsSB0TzENRicAxVCwNOLfLTDj+88XPPHXnj+83PJD62MdTxz0hg/PCDwQKnFoPbacaWPc+eGW47xmYmOeMMg4TEjQRmyR48DjOQTjCT4DlwmHHbMQYzaZ4KoMNuJDBI4/OL/Oz0b5J/Dhy239zG/k36jwGDhDzQlt94vX87B2j4gcOJG9h4zKQZgLYY3Ehgw2uLwe2cYmuZA8+SZxzLKbbsOSMhufHMwzbLHgO8Dtt4882BO7b9zcc33vjZZsMvdzz58I0fFXVyOB0GAQdgDFC0MDYAbSegAUnLKBgFo2AUjAJMAADH6FBEQDAMSQAAAABJRU5ErkJggg==","orcid":"","institution":"Tel Aviv University","correspondingAuthor":true,"prefix":"","firstName":"Smadar","middleName":"Zohar","lastName":"Patael","suffix":""},{"id":633648548,"identity":"8a02f77d-5fbe-44e2-a856-29588251b1cf","order_by":1,"name":"Ori Levin","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Ori","middleName":"","lastName":"Levin","suffix":""},{"id":633648551,"identity":"0ac6871a-5766-41a4-a02b-9452ad72e8c0","order_by":2,"name":"Mor Levy","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Mor","middleName":"","lastName":"Levy","suffix":""},{"id":633648554,"identity":"da6b5950-c1ef-4cc1-bd2d-18658bcb9b14","order_by":3,"name":"Amalia Bar-On","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Amalia","middleName":"","lastName":"Bar-On","suffix":""}],"badges":[],"createdAt":"2026-04-30 08:40:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9574360/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9574360/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108386171,"identity":"dbf055fb-7f3b-48c9-8356-e8820fbc52e7","added_by":"auto","created_at":"2026-05-04 06:15:45","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":299239,"visible":true,"origin":"","legend":"\u003cp\u003ePath analysis model for reading comprehension based on the Lexical Quality Hypothesis and the Combinatorial Model\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9574360/v1/07fc0aa66180db8f3296f1c8.jpeg"},{"id":108492487,"identity":"96702f17-fb2d-4b24-a64b-bac9498854fc","added_by":"auto","created_at":"2026-05-05 09:57:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":868679,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9574360/v1/1c81a113-d82e-458d-b922-199a11385695.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pathways to comprehension: The role of supra-lexical monitoring in narrative and informational text understanding","fulltext":[{"header":"Introduction","content":"\u003cp\u003eReading comprehension is a complex, multidimensional ability that relies on an interplay of decoding, linguistic, cognitive, and metacognitive processes. Several theoretical models describe how these processes support the construction of meaning. The Simple View of Reading conceptualizes comprehension as the product of decoding and linguistic understanding (Hoover, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hoover \u0026amp; Gough, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), a framework that has received broad empirical support across languages and developmental stages (e.g., Bellocchi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Catts et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Joshi et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although the Simple View frames these components as distinct, subsequent research has shown that the relationships among them are dynamic and reciprocal (e.g., Duke \u0026amp; Cartwright, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scarborough, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Snow, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Perfetti and Stafura\u0026rsquo;s (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) framework extends this view by positioning reading comprehension as the coordinated outcome of efficient word-level processes and higher-order text integration. Central to this account is the Lexical Quality Hypothesis (Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Perfetti \u0026amp; Hart, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), which holds that readers with precise and well specified lexical representations access word meanings rapidly and consistently, thereby supporting fluent integration and inference making. Share\u0026rsquo;s recent Combinatorial Model of reading acquisition (Share, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) offers an additional conceptual layer that is relevant to comprehension. The model characterizes reading development as the integration of linguistic information across sub-morphemic, morpho-lexical, and supra-lexical levels. The supra-lexical phase highlights the reader\u0026rsquo;s ability to use context to monitor, evaluate, and refine meaning during reading, reflecting a shift toward flexible and strategically guided comprehension. Although these models conceptualize reading comprehension as a general process, extensive research shows that the operation of decoding, lexical, and higher-order processes varies across text types, particularly narrative and informational texts, which differ in their linguistic and cognitive demands (Graesser et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite extensive research on reading comprehension across text types, existing accounts have typically focused on relations among decoding and lexical knowledge, while the role of supra-lexical processes has received comparatively less attention within integrated models. As a result, it remains unclear how word-level processes and higher-order, context-driven regulation operate jointly within a unified framework, particularly across genres. In addition, monitoring processes have often been assessed using domain-general executive function measures, leaving open the question of whether reading-specific, context-based monitoring uniquely contributes to comprehension. This issue is especially relevant in orthographies such as Hebrew, where pervasive lexical ambiguity increases reliance on contextual information during reading.\u003c/p\u003e \u003cp\u003eTo address these gaps, the present study integrates the Lexical Quality Hypothesis and the Combinatorial Model within a unified empirical framework. Specifically, we examine how lexical knowledge (vocabulary and morpho-lexical knowledge), decoding (accuracy and rate), and supra-lexical monitoring jointly contribute to the comprehension of narrative and informational texts in Hebrew-speaking fourth graders. This developmental stage marks the transition from \u0026ldquo;learning to read\u0026rdquo; to \u0026ldquo;reading to learn\u0026rdquo; (Chall, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Hoover \u0026amp; Gough, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; National Reading Panel, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), during which decoding becomes increasingly automatized and higher-order linguistic and regulatory processes play a more central role in comprehension (Cain \u0026amp; Oakhill, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Catts et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Examining these components within a unified framework across text genres enables a direct comparison of shared and genre-specific pathways to comprehension, providing a more comprehensive account of how readers coordinate word-level and supra-lexical processes during this critical stage of reading development.\u003c/p\u003e \u003cp\u003eNarrative and informational text comprehension\u003c/p\u003e \u003cp\u003eNarrative and informational texts differ systematically in their communicative purposes. Narratives aim to entertain and convey human experience, whereas informational texts aim to present factual knowledge and explain concepts (Duke \u0026amp; Cartwright, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Graesser et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These differing purposes are reflected in their structural organization. Narratives typically follow event-based structures that unfold sequentially over time, supported by temporal and causal connections (Berman \u0026amp; Slobin, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Informational texts, in contrast, employ expository structures that organize ideas according to logical relations such as cause and effect or comparison (Berman, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Meyer \u0026amp; Ray, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At the linguistic level, narratives tend to rely on familiar, high-frequency vocabulary that supports the representation of characters and events, whereas informational texts show higher lexical density and greater reliance on abstract and domain-specific terminology. They also typically involve greater syntactic complexity, requiring readers to process more compact and conceptually dense expressions (Berman, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Berman \u0026amp; Nir-Sagiv, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Fang \u0026amp; Schleppegrell, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ravid \u0026amp; Berman, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Together, these differences contribute to distinct cognitive demands across text types.\u003c/p\u003e \u003cp\u003eAcross development, narrative texts are generally easier to understand than informational texts. Meta-analytic evidence indicates a small to moderate narrative advantage in both general and inferential comprehension (Clinton et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mar et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Informational texts also appear to place greater demands on executive control and inference generation, with readers producing fewer bridging and elaborative inferences and more knowledge-based errors (Kraal et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Miller et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Genre differences appear across reading modalities (Dickens \u0026amp; Meisinger, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and persist even when cohesion is increased (McNamara et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; van Silfhout et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Among young readers, these differences remain even after controlling for vocabulary, inferencing, and working memory (Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among older students, the gap is reduced but not eliminated, suggesting that the magnitude of genre effects depends on readers\u0026rsquo; linguistic, cognitive, and motivational profiles (Cruz Neri et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Eason et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, genre effects are not absolute. When content is matched across genres, informational texts sometimes support comparable or even superior learning outcomes, both in recall of identical content and in conceptual understanding (Cervetti et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Neuman et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These findings suggest that genre effects depend on factors such as readers\u0026rsquo; age and the nature of the comprehension task.\u003c/p\u003e \u003cp\u003eContribution of lexical and morpho-lexical knowledge to comprehension across the two text types\u003c/p\u003e \u003cp\u003eLexical knowledge is consistently identified as a central component of reading comprehension, contributing to both efficient semantic access and higher-order integration processes (Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Perfetti \u0026amp; Stafura, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). A large body of empirical research across languages and developmental stages shows that vocabulary predicts comprehension even after accounting for decoding (e.g., Ouellette, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Protopapas et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Quinn et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). With respect to text genre, evidence across age groups and research designs suggests that vocabulary contributes to comprehension in both narrative and informational texts to a comparable degree. For example, vocabulary has been found to predict comprehension to a similar degree in both genres among elementary school students (Santos et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), to longitudinally predict later comprehension outcomes across genres (Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and to show similar associations in older students as well (Cruz Neri et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Some studies nevertheless report somewhat stronger vocabulary effects for informational text comprehension, particularly from the middle elementary grades onward (Liebfreund, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yildirim et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Because informational comprehension is closely tied to background knowledge, vocabulary may appear especially predictive when lexical knowledge overlaps with the conceptual knowledge required for understanding the text (Best et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Consistent with this interpretation, vocabulary measures containing items related to informational content tend to show stronger associations with informational comprehension (Hannon, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond vocabulary, morphological knowledge has also emerged as an important contributor to reading comprehension. A recent meta-analysis of 44 studies with children aged 6 to 16 reported a strong overall association between morphological awareness and comprehension (r \u0026asymp; .565), an effect that strengthens across development as texts contain more morphologically complex vocabulary (Liu et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Morphological awareness contributes both directly, by enabling readers to extract semantic and relational information from complex words, and indirectly through its effects on word reading and vocabulary growth (Deacon et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Foorman et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Importantly, this contribution is not reducible to vocabulary knowledge, as it explains unique variance in comprehension even after controlling for vocabulary, phonological awareness, and word reading (Levesque et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tong et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The contribution of morphology to comprehension has been documented across alphabetic languages such as English (Deacon et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nagy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), French (Rassel et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Spanish (Simpson et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as well as in non-alphabetic orthographies such as Chinese (Tong et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In Hebrew, a morphologically rich Semitic language, awareness of root and pattern structures has also been shown to support text comprehension (Primor et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Ravid \u0026amp; Mashraki, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Vaknin-Nusbaum et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite extensive research on morphology and reading comprehension, little is known about whether its contribution varies across text genres. To date, only one study has examined morphology in relation to genre specific comprehension (Primor et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In this study of Hebrew speaking fourth graders, morphological awareness explained modest but significant variance in comprehension, predicting narrative comprehension among children with reading disabilities and informational text comprehension among typically developing readers. No research has examined genre differences while simultaneously modeling morphological awareness, vocabulary, and decoding abilities, leaving an important gap in understanding how these skills support comprehension across text types.\u003c/p\u003e \u003cp\u003eContribution of decoding abilities to comprehension across the two text types\u003c/p\u003e \u003cp\u003eA growing body of research indicates that the contribution of decoding to reading comprehension is moderated by several interrelated factors, most prominently readers\u0026rsquo; age, with a marked decline in the decoding\u0026ndash;reading comprehension relation around ages 9 to 10 (Garc\u0026iacute;a \u0026amp; Cain, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In their meta-analytic study, Garc\u0026iacute;a and Cain (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) also identified the type of decoding measure as a key moderator of this relationship. Among young readers, reading accuracy showed the strongest correlations with comprehension, whereas speed-based measures showed weaker associations. As decoding accuracy approaches ceiling levels with development, a progression that often occurs earlier in alphabetic systems with relatively transparent grapheme\u0026ndash;phoneme correspondences (Joshi, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), its predictive power diminishes, and measures indexing processing efficiency, such as timed word reading or text-level fluency, become more informative (Padeliadu \u0026amp; Antoniou, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Protopapas et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen genre is considered, the pattern becomes more complex. Studies using untimed, word-level accuracy measures have shown that narrative comprehension is predicted by decoding, whereas informational text comprehension is more strongly associated with world knowledge (Best et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hannon, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, when decoding is assessed using timed word-level measures that integrate accuracy and speed, early decoding efficiency predicts growth in informational, but not narrative, comprehension, suggesting a role for automatized lexical access in processing informational texts (Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Studies employing text-level measures of reading fluency, which assess accuracy and speed within connected text, have not consistently found genre-specific effects. Across languages and age groups, decoding-related skills measured in this way tend to predict comprehension similarly across narrative and informational texts (e.g., Padeliadu \u0026amp; Antoniou, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Primor et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Uysal \u0026amp; Bilge, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These findings suggest that, beyond developmental factors, inconsistencies in literature reflect differences in the level of measurement (word vs. text) and in the nature of the construct assessed (accuracy vs. integrated fluency).\u003c/p\u003e \u003cp\u003eHigher-Order Supra-Lexical Processes: The Case of Hebrew\u003c/p\u003e \u003cp\u003eReading is not solely a matter of accurate word identification or lexical access but also involves the integration of contextual information. The addition of the supra-lexical layer in the Combinatorial Model (Share, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reframes reading as a process of meaning construction guided by contextual information. At this level, readers integrate linguistic information across words, sentences, and discourse, while continuously revising and regulating interpretations in response to contextual cues. Such cues become particularly important when readers encounter lexical ambiguity, in which a single orthographic form corresponds to multiple meanings. This occurs with homophonic homographs that share pronunciation but differ in meaning, (e.g., \u003cem\u003ebat\u003c/em\u003e), and with heterophonic homographs (e.g., \u003cem\u003epresent\u003c/em\u003e), which differ in both meaning and pronunciation. Although heterophonic homographs are relatively rare in many non-Semitic languages (Perfetti \u0026amp; Hart, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), they are common in Hebrew and Arabic due to their Abjadic writing systems, which provide limited marking of vowels (Share, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHebrew-speaking children initially learn to read a transparent version of the script, the pointed system, in which phonology is represented almost fully through consonantal letters, vowel letters, and vowel diacritics. After approximately three to four years of schooling, they transition to the unpointed script, where diacritics are removed and phonological information, especially vowels, is only partially encoded (e.g., Share \u0026amp; Bar-On, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Reading this opaque script requires reliance on two complementary strategies. One is morpho-orthographic identification, in which readers use the consonantal root and pattern system of Hebrew to constrain lexical candidates and recover missing phonological information (Bar-On \u0026amp; Ravid, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The second is reliance on contextual information. Because unpointed Hebrew contains many heterophonic homographs, readers must integrate syntactic, semantic, and discourse cues to determine the appropriate interpretation (Bar-On et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consistent with this perspective, and in line with the Combinatorial Model (Share, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), Share and Bar-On (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) identified context reliance as a distinct third level in their Triplex Model of learning to read Hebrew. The pervasive lexical ambiguity created by the Abjadic script increases the likelihood of misidentification and therefore heightens the importance of efficient supra-lexical monitoring processes during reading.\u003c/p\u003e \u003cp\u003eSupra-lexical monitoring processes\u003c/p\u003e \u003cp\u003eWithin contemporary models of reading comprehension, a key component of skilled reading is the ability to detect and repair breakdowns in understanding. In metacognitive and conflict-monitoring frameworks, this regulatory capacity comprises two coordinated processes: monitoring, the detection of mismatches between an emerging interpretation and incoming textual information (Nelson, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), and control, processes that resolve such mismatches through inhibition, reanalysis, and updating (Botvinick et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Koriat \u0026amp; Goldsmith, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). A well-established paradigm for investigating this coordination in real time is the Garden Path (GP) sentence. Garden Path structures temporarily guide readers toward an interpretation that later proves incompatible with subsequent input, creating a point of processing conflict. Successful comprehension, therefore, requires readers to detect the conflict, inhibit the initial interpretation, and construct an alternative analysis. Because these processes occur during real-time sentence interpretation, the Garden Path paradigm provides a behavioral index of supra-lexical monitoring processes that trigger reanalysis and control within reading (Frazier \u0026amp; Rayner, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Novick et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHebrew provides a particularly informative context for examining such processes. The high frequency of heterophonic homographs in unpointed Hebrew requires readers to rely on syntactic and semantic context to determine the intended interpretation (Shimron \u0026amp; Sivan, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Garden Path paradigms have therefore been adapted in Hebrew to examine real-time supra-lexical monitoring during lexical ambiguity resolution (Bar-On et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In a large developmental study, Bar-On et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) asked participants ranging from second graders to adults to read aloud sentences containing heterophonic homographs that induced temporary misinterpretations. Whereas second and third graders showed little evidence of monitoring, fourth graders corrected approximately half of the induced misinterpretations, with continued improvement into adolescence. Although the Garden Path task captures readers\u0026rsquo; ability to detect and revise misinterpretations in real time, it remains unclear whether such supra-lexical monitoring processes explain unique variance in reading comprehension beyond lexical knowledge and decoding skills. Much of the literature linking executive processes to comprehension has relied on domain-general executive function (EF) measures, such as inhibition, working memory, and cognitive flexibility, administered outside the context of reading. A comprehensive meta-analytic review of 29 studies reported a moderate overall association between EF and reading comprehension across development (Follmer, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, this reliance limits conclusions about the processes engaged during reading itself. Consistent with this limitation, recent studies show that reading-specific EF tasks, which embed control demands within print processing, explain unique variance in comprehension beyond traditional EF measures (Cartwright et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Peng et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, we therefore employ the Garden Path paradigm to capture supra-lexical monitoring processes in reading. If such processes contribute uniquely to comprehension, an open question is whether their contribution varies across text genres. Some studies suggest that executive processes may be particularly important for informational texts, which often impose greater integration and regulatory demands (Eason et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, structural models also report similar patterns across genres, with working memory showing direct effects on both narrative and informational comprehension, and inhibition and cognitive flexibility operating indirectly through vocabulary in both (Escobar \u0026amp; Espinoza, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Evidence from text-based studies likewise points to genre differences in monitoring demands. These processes are typically assessed through readers\u0026rsquo; responses to inconsistencies or inference gaps in extended texts, indexed by slowed reading, rereading, or explicit detection of comprehension problems. Informational texts generally elicit slower reading, more rereading, and lower recall than narrative texts, and effective regulation strategies such as selective rereading are more strongly associated with informational text comprehension (Kraal et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yoo, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zabrucky \u0026amp; Moore, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Neurophysiological evidence similarly indicates greater semantic integration demands during inference generation in informational texts (Baretta et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Accordingly, if supra-lexical monitoring processes make a unique contribution to reading comprehension, this contribution is expected to be stronger for informational than for narrative texts.\u003c/p\u003e \u003cp\u003eThe present study\u003c/p\u003e \u003cp\u003eThe study aims to examine how foundational lexical knowledge, decoding skills, and supra-lexical monitoring processes jointly contribute to reading comprehension at a stage when basic word identification has largely stabilized. In addition to assessing their direct contributions, the study evaluates whether supra-lexical monitoring functions as a regulatory mechanism linking word-level decoding to text-level comprehension. Specifically, the study investigates whether the relative contributions and structural relations among these components differ between narrative and informational texts. By integrating vocabulary and morpho-lexical knowledge as complementary indices of lexical quality, separating decoding into accuracy and rate components, and incorporating a reading-embedded measure of supra-lexical monitoring derived from the Garden Path paradigm, the study evaluates reading processes across multiple representational levels within a single path-analytic framework. In doing so, it addresses a key gap in the literature concerning the joint contribution of word-level and supra-lexical processes to comprehension across text genres.\u003c/p\u003e \u003cp\u003eThe ordering of variables in the proposed path model was guided by the Lexical Quality Hypothesis (Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Perfetti \u0026amp; Stafura, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and the Combinatorial Model (Share, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Although lexical knowledge and reading experience influence one another, lexical representations are theorized to constrain the efficiency and flexibility of word identification (Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Accordingly, lexical knowledge was positioned as the foundational layer of the model. Decoding skills, operationalized as accuracy and rate, were entered at the second level to capture the quality of word identification in print. At the third level, supra-lexical monitoring was included to reflect higher-level regulation during sentence-level processing. We expected lexical knowledge to contribute robustly to comprehension across genres. Decoding was expected to show a reduced but potentially genre-sensitive contribution at this developmental stage, and supra-lexical monitoring was expected to explain additional unique variance beyond lexical and decoding components. Given evidence that informational texts impose greater lexical, conceptual, and regulatory demands, we hypothesized that the relative contributions of lexical knowledge, decoding components, and supra-lexical monitoring would differ between informational and narrative comprehension.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eSample\u003c/p\u003e \u003cp\u003eThe sample comprised 94 fourth-grade students (53 girls) aged 9 to 11 years (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.01, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.33) from four public schools in Israel. The schools were evenly distributed between the state secular education system (49% of participants) and the state religious education system, with all schools ranked in the 1st-2nd deciles of the Israeli Ministry of Education's nurture index, indicating a medium to high socioeconomic status. Participant selection followed specific inclusion criteria. All participants demonstrated normal nonverbal intelligence, as measured by Raven's Progressive Matrices (Raven et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), and verbal intelligence, as measured by the vocabulary subscale of the Wechsler Intelligence test (Wechsler, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Additionally, all participants had at least five years of Hebrew language exposure and the absence of hearing or neurodevelopmental disorders. The final sample comprised both typically developing readers and children with documented learning disabilities, capturing the full range of reading and language abilities. The research protocol was approved by the authors\u0026rsquo; institutional ethics committee and the national education authority (Approval No. 8790). Written informed consent was obtained from both participants and their parents before study enrolment. For the current study, the following measures were selected from a larger battery of tests.\u003c/p\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003cp\u003e \u003cb\u003eReading comprehension tests\u003c/b\u003e. Two reading comprehension tests were administered during separate assessment sessions: one using an informational text and the other using a narrative text. In the absence of standardized reading comprehension tests in Hebrew, texts were selected from the national large-scale assessment (National Authority for Measurement and Evaluation in Education, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Both texts were presented in unpointed Hebrew, reflecting the developmental stage of fourth-grade students who no longer rely on diacritical marks (Bar-On \u0026amp; Ravid, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Students were instructed to read both texts silently and answer written questions. The informational text, titled \"The Invention of the Hot Air Balloon,\" focused on the scientific and historical content of hot air balloons. The narrative text, titled \"A Real Hero,\" centered on a moral dilemma and character development involving a child's decision to rescue puppies on the way to school, despite risking punishment for being late. Both texts included two accompanying illustrations to support comprehension.\u003c/p\u003e \u003cp\u003eThe comprehension assessment included both original questions from the Meitzav and questions developed specifically for this study. Both tests contained a comparable number of questions with comparable questioning formats, combining open-ended and multiple-choice items designed to evaluate multiple levels of comprehension according to Kintsch's model of text representation (Kintsch, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Kintsch \u0026amp; Kintsch, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Internal consistency was acceptable for both measures (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.77 for the informational text; α\u0026thinsp;=\u0026thinsp;.73 for the narrative text). Each test featured a scoring guide (rubric) developed in two stages: initial scoring based on a sample of approximately 20 student responses and 15 responses from native-speaking adults, followed by refinement based on the full range of responses. The questions demonstrated good inter-rater reliability (0.81\u0026ndash;0.99).\u003c/p\u003e \u003cp\u003e \u003cb\u003eVocabulary test\u003c/b\u003e. vocabulary knowledge was assessed using the Collocation Completion (Manshari \u0026amp; Bar-On, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Collocations are word combinations that frequently occur together in a language (such as \"heavy rain,\" \"good luck\", \u0026ldquo;hand-writing\u0026rdquo;), which provide an ecologically valid measure of lexical knowledge because they demonstrate a deeper understanding of how words are typically used together in natural language. This test was designed to assess vocabulary in school-age children and contained 30 items. Students were required to complete collocations by providing the missing word at the end of a sentence. For example, in English this would be similar to completing \"The cars stopped at the traffic ____\" (light). Scoring awarded 0 points for an incorrect response, 1 point for a response that was semantically appropriate but not the conventional collocation (e.g., \"signal\") or contained morphological/phonological errors (e.g., \"lite\"), and 2 points for the correct conventional response (\"light\"). The test was divided into two parts (each containing 15 sentences) and administered in two separate sessions.\u003c/p\u003e \u003cp\u003e\u003cb\u003eMorpho-lexical test\u003c/b\u003e. Morpho-lexical knowledge was assessed by the Derived Word Completion Test (Lahmi-Kakon et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The test examines the derivation of verbs, adjectives, and verbal nouns through completing words in short sentences containing a prime word from which the target word must be derived. It contained 16 items where students completed sentences with words derived from the same root as a highlighted word. For example, \"The teachers \u003cb\u003edecided\u003c/b\u003e on a uniform, but the students opposed the teachers' _____\" [decision]). Scoring awarded 0 points for an incorrect response (unrelated root), 1 point for morphological errors (correct root but incorrect pattern), and 2 points for the correct response (appropriate derivation). Scores were expressed as a percentage of the maximum possible score.\u003c/p\u003e \u003cp\u003e \u003cb\u003eReading tests.\u003c/b\u003e Reading accuracy and speed measures were based on oral reading of four texts from the standardized \"Alef to Tav\" battery for evaluating reading and writing abilities in Hebrew (Shany et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Participants were asked to read four texts: two pointed texts (an informational text containing 199 words and a narrative text containing 105 words) and two unpointed texts (an informational text containing 208 words and a narrative text containing 310 words). Participants were instructed to read aloud as quickly and accurately as possible. The accuracy measure was calculated as the percentage of words read correctly, while reading speed was determined by the number of words read per minute. The reliability coefficients were high, with Cronbach's alpha of 0.90 for reading accuracy and 0.97 for reading speed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSupra-lexical monitoring (Context-related processes).\u003c/b\u003e Supra-lexical monitoring (hereafter, monitoring) was assessed using a Garden Path (GP) test adapted from Bar-On et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This paradigm captures readers\u0026rsquo; ability to use contextual information to detect and revise interpretations that become inconsistent with ongoing sentence input, thereby indexing online regulation of meaning during reading. The test consisted of 16 Hebrew heterophonic-homographic words (e.g., מדבר, which can be read as /midbar/ [desert] or /medaber/ [speaking]) embedded in 32 sentences representing two conditions: Non-Garden Path (NGP) sentences, where both preceding and following contexts supported the target pronunciation (e.g., \"המטיילים עברו הר גבוה ומדבר רחב\" [The hikers crossed a high mountain and a wide desert]), and Garden Path (GP) sentences, where preceding context directed readers toward one pronunciation that proved incorrect as the sentence continued (e.g., \"האיש הולך ומדבר רחב לפניו\" [The man walks and a wide desert is before him]). Each target homographic word appeared once in an NGP sentence and once in a GP sentence. The sentences were divided into two balanced blocks, with each word appearing only once per block and each block containing both GP and NGP sentences as well as four additional filler sentences without target words. These blocks were administered to participants in separate individual sessions to prevent practice effects. Participants were instructed to read the sentences aloud and were told they could correct their reading if necessary.\u003c/p\u003e \u003cp\u003eMonitoring assessed participants' ability to detect and correct reading errors across both sentence types. While Garden Path (GP) sentences were specifically designed to induce reading errors due to misleading contexts, errors also occurred in Non-Garden Path (NGP) sentences, particularly for less skilled readers. Therefore, monitoring abilities were assessed across all sentences to provide a comprehensive evaluation of error detection and correction capabilities. Four monitoring levels were defined: 0 point for no error detection, 1 point for detection without correction, where participants noticed the error (e.g., pausing or saying \"this sounds strange\") but did not correct it, 2 points for delayed correction after completing the sentence, and 3 points for immediate correction during reading. For each participant, the maximum possible monitoring score was calculated by multiplying the total number of reading errors (across both GP and NGP sentences) by 3, representing the highest level of monitoring efficiency. The monitoring score was then calculated as the sum of all monitoring points divided by this maximum possible score, yielding a weighted proportion that reflects the participant's error correction efficiency while accounting for individual differences in error rates. Together, detection and correction performance provide an index of monitoring efficiency during real-time reading.\u003c/p\u003e \u003cp\u003eProcedure\u003c/p\u003e \u003cp\u003eData collection was conducted as part of a larger research project examining the relationships between decoding abilities, linguistic knowledge, executive functions, and reading comprehension. In total, 32 tests were administered across five sessions, each lasting approximately 45 minutes. Two of these sessions were conducted individually (including reading assessments and the Garden Path task), while the remaining sessions were administered in group settings (including reading comprehension tests, lexical tests, and Raven's Progressive Matrices). Data collection was carried out by seven researchers, all of whom were certified speech-language pathologists. All sessions took place during regular school hours within the school premises.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003ePath analysis was conducted to examine the relationships among lexical knowledge (vocabulary and morpho-lexical knowledge), reading skills (accuracy and speed), monitoring, and comprehension of narrative and informational texts. The model specified a theoretically driven sequence in which lexical knowledge predicted reading (accuracy and rate) skills and monitoring, and reading skills predicted monitoring, and all three domains were modeled as direct predictors of the two comprehension outcomes. The analysis was conducted in IBM AMOS (Version 30; IBM Corp.) using maximum likelihood with robust standard errors. Model fit was evaluated using standard indices (χ\u0026sup2;, CFI, TLI), and direct and indirect effects were examined.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptive statistics and correlations among all study variables are presented in Table 1. Performance levels were comparable across the two lexical measures and across the two comprehension tasks, suggesting balanced task difficulty across measures. Variability within each domain was similar, with no evidence of ceiling or floor effects. Reading accuracy was uniformly high, whereas reading speed and monitoring showed greater dispersion, reflecting individual differences in fluency and contextual regulation typical of fourth-grade readers. Mean scores on both lexical and reading measures were aligned with previous studies and established Hebrew norms (Bar-On et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lahmi-Kakon et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Manshari \u0026amp; Bar-On, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shany et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Together, these patterns confirm the reliability and ecological validity of the measures used in the present model. The correlation analysis revealed strong associations among the linguistic measures, with lexical and morpho-lexical knowledge closely related to each other and both moderately associated with reading comprehension. Reading accuracy and speed were also interrelated and showed moderate links with comprehension performance. The monitoring measure correlated with both comprehension tasks, suggesting shared variance across genres. Finally, comprehension of narrative and informational texts was positively and substantially related.\u003c/p\u003e\n\u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u0026nbsp;Table 1: Descriptive Statistics and Correlations Among Study Variables\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eVariable\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eM\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eSD\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e1\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e6\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eLexical knowledge\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e1. Vocabulary [% correct]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e70.92\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e17.95\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e2. Morpho-lexical Knowledge [% correct]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e70.82\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e17.6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.72***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eReading Variables\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e3. Reading Accuracy [% correct words]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e96.49\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e2.99\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.53***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.52***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e4. Reading Speed [Words per minute (wpm)]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e106.49\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e24.47\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.48***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.39***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.62***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eContext Variables\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e5. Supra-lexical monitoring [% efficient corrections]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e55.92\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e19.23\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.54***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.47***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.54***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.38***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003eReading Comprehension\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e6. Informational Text [% correct answers]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e66.25\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e21.23\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.63***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.62***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.56***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.52***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.51***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e\u0026mdash;\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e7. Narrative Text [% correct answers]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e66.94\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e18.12\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.61***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.55***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.48***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.43***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.49***\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv\u003e.58***\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNote.\u003c/strong\u003e All measures are based on Hebrew tasks (see Method). *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ePath analysis examined the direct and indirect pathways through which linguistic and reading variables contribute to narrative and informational text comprehension in unpointed Hebrew. The path analysis model demonstrated an excellent fit to the data \u0026chi;2(7)\u0026thinsp;=\u0026thinsp;7.705, \u003cem\u003ep\u003c/em\u003e = .359, CFI\u0026thinsp;=\u0026thinsp;0.977, RMSEA\u0026thinsp;=\u0026thinsp;0.033. The standardized path coefficients are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The path analysis revealed distinct pathways for narrative and informational text comprehension.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDirect, Indirect, and Total Effects of Linguistic, Reading, and Supra-lexical monitoring Variables on Narrative and Informational Text Comprehension\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\n \u003cp\u003eNarrative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e\n \u003cp\u003eInformational text\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eDirect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIndirect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003eDirect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eIndirect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eLexical knowledge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1. Vocabulary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.495**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.105*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e.600**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003e.258*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e.186*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003e.443**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e2. Morpho-lexical Knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.02*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e.02*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003e.260*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e.015*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003e.28*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eReading Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e3. Reading Accuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.08*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e.08*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e4. Reading Speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003e.211*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003e.211*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eContext Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e5. Supra-lexical monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.220*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e.220*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\" style=\"width: 1.6698%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\" style=\"width: 10.204%;\"\u003e\n \u003cp\u003e.175*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003e.175*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\"\u003e* p \u0026lt; .05, ** p \u0026lt; .01, *** p \u0026lt; .001\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFor narrative text comprehension, vocabulary was a strong predictor, showing both direct effects (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.495, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and indirect effects through monitoring (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.105, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), yielding a total effect (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.600, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Monitoring directly influenced narrative comprehension (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.220, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, morpho-lexical knowledge did not show significant direct or indirect effects on narrative text comprehension. The model explained 41% of the variance in narrative comprehension. For informational text comprehension, a broader set of predictors was involved. Vocabulary showed direct (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.258, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and indirect effects (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.186, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), though with a smaller total effect (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.443, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) than for narrative texts. However, unlike narrative comprehension, morpho-lexical knowledge predicted informational text comprehension through both direct (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.260, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and indirect effects (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, reading speed directly contributed (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.211, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Monitoring contributed significantly (\u003cem\u003e\u0026beta;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.175, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), confirming its importance across genres. The model explained 51% of the variance in informational comprehension. With respect to relations among the predictor variables, reading accuracy significantly predicted monitoring (\u0026beta;\u0026thinsp;=\u0026thinsp;0.344, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Lexical knowledge showed both direct (\u0026beta;\u0026thinsp;=\u0026thinsp;0.357, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and indirect effects (\u0026beta;\u0026thinsp;=\u0026thinsp;0.123, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on monitoring. Overall, the model revealed both shared and distinct pathways to comprehension across genres, with monitoring contributing directly to comprehension in both text types.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined how lexical knowledge, decoding skills, and supra-lexical monitoring processes contribute to reading comprehension of narrative and informational texts among Hebrew-speaking fourth graders. The resulting model demonstrated excellent fit and explained substantial variance in comprehension across both text genres, highlighting the importance of integrating these processes within a single explanatory framework. Importantly, the pattern of findings aligns closely with the multi-level architecture proposed in the Combinatorial Model, with lexical knowledge supporting word identification processes, and supra-lexical monitoring coordinating the integration of meaning during reading. In this sense, a central contribution of the study lies in identifying supra-lexical monitoring as a regulatory mechanism linking lower-level reading processes with higher-level comprehension.\u003c/p\u003e \u003cp\u003eImportantly, performance levels on the narrative and informational comprehension tasks were highly comparable, with nearly identical mean accuracy scores (narrative: M\u0026thinsp;=\u0026thinsp;66.94%, SD\u0026thinsp;=\u0026thinsp;18.12; informational: M\u0026thinsp;=\u0026thinsp;66.25%, SD\u0026thinsp;=\u0026thinsp;21.23). This pattern is not fully consistent with much of the literature, which often reports lower performance for informational texts due to their greater lexical and conceptual demands, although findings are not entirely uniform. In the present context, however, this equivalence constitutes a methodological advantage, as it rules out differences in task difficulty as an explanation for the observed divergence in predictive pathways. Instead, the findings point to systematic differences in how readers allocate linguistic and cognitive resources when processing texts that vary in discourse structure, lexical density, and conceptual demands.\u003c/p\u003e \u003cp\u003eOverall, the model accounted for more variance in informational text comprehension than in narrative comprehension (51% vs. 41%, respectively), suggesting that informational texts recruit a broader and more differentiated constellation of linguistic and reading-related skills, consistent with their higher lexical density, morphological complexity, and conceptual demands. At the same time, narrative and informational comprehension were strongly correlated at the bivariate level (r = .58, p \u0026lt; .001), indicating a substantial shared foundation. However, once lexical, decoding, and monitoring variables were entered into the model, this association was markedly reduced (to approximately r \u0026asymp; .20), suggesting that much of the apparent overlap between genres reflects common underlying mechanisms rather than a unitary comprehension ability. These findings support a view of reading comprehension as grounded in shared lexical and supra-lexical processes, while also revealing genre-specific configurations that reflect the distinct linguistic demands of narrative and informational texts. In the sections that follow, we examine these shared and unique contributors in turn, beginning with the role of lexical knowledge as the core engine of comprehension.\u003c/p\u003e \u003cp\u003eLexical knowledge as a central resource for reading comprehension\u003c/p\u003e \u003cp\u003eThe present findings confirm the central role of lexical knowledge in reading comprehension across text genres, in line with extensive previous research and with both the Lexical Quality Hypothesis (Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Perfetti \u0026amp; Stafura, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Kim\u0026rsquo;s Direct and Indirect Effects Model (DIER, Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consistent with previous studies showing that vocabulary predicts comprehension beyond decoding in both narrative and informational texts (Cruz Neri et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Protopapas et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), lexical knowledge in the present model emerged as a strong predictor of comprehension across genres. Vocabulary showed substantial total effects on comprehension, with a stronger contribution to the narrative text (β\u0026thinsp;=\u0026thinsp;.60, p \u0026lt; .01) and a moderate but robust contribution to the informational text (β\u0026thinsp;=\u0026thinsp;.44, p \u0026lt; .01). Morpho-lexical knowledge made a significant and selective contribution to informational text comprehension (total effect β\u0026thinsp;=\u0026thinsp;.28, p \u0026lt; .05), while showing no meaningful contribution to narrative comprehension. These effects included both direct and indirect paths mediated through supra-lexical monitoring, indicating that vocabulary knowledge supports comprehension through efficient semantic access and higher-order integration.\u003c/p\u003e \u003cp\u003eThe pattern of results, however, diverges from much of the existing literature regarding genre differences in lexical contributions. Several studies have reported comparable vocabulary effects across narrative and informational texts (Santos et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), whereas others have found stronger vocabulary effects for informational texts, particularly from the middle elementary grades onward (Hannon, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liebfreund, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yildirim et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This divergence is plausibly related to the nature of the vocabulary measures used. Studies reporting an informational advantage have often relied on vocabulary tasks emphasizing academic or content-specific lexical knowledge, thereby increasing overlap between the vocabulary assessment and the demands of informational texts (Best et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hannon, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, vocabulary was assessed using a collocation completion task designed to capture the breadth and conventionality of lexical knowledge in context, indexing readers\u0026rsquo; sensitivity to how words typically co-occur in natural language. This type of knowledge is characteristic of the literate lexicon that develops during the school years, reflecting increasing exposure to written language and sensitivity to conventionalized word combinations (Ellis, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Nippold, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The items in the task span a wide range of lexical registers and discourse contexts, including everyday expressions (e.g., \u0026ldquo;helplessness\u0026rdquo;, \u0026ldquo;handwriting\u0026rdquo;), lexical items common in children\u0026rsquo;s literature (e.g., \u0026ldquo;royal throne\u0026rdquo; \u0026ldquo;(they live) happily ever after\u0026rdquo;), and collocations with a more informational or academic flavor (e.g., \"side effects\u0026rdquo; \u0026ldquo;earthquake\u0026rdquo;). As such, this measure does not target a specific genre or content domain but rather reflects general lexical quality. This broad sampling of lexical knowledge likely explains why vocabulary showed strong effects across both genres and particularly robust effects for narrative comprehension, where rapid access to familiar and conventionalized lexical combinations facilitates fluent meaning construction and supports the building of coherent event-based representations (Graesser et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Nation, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Wray, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe inclusion of a morpho-lexical measure extends the assessment of lexical quality beyond surface familiarity and usage-based knowledge. The task assesses readers\u0026rsquo; ability to derive words from a shared base, reflecting their capacity to analyze morphological structure and to exploit systematic form\u0026ndash;meaning relations in support of comprehension (Deacon et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nagy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The task items include derivations that are frequently used to condense information and express abstract relations, such as passive verb forms (e.g., \u003cem\u003eWe have tried to catch the mouse. At the end of the day, he\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ewas caught\u003c/span\u003e), derivational adjectives (e.g., \u003cem\u003ea country with many mountains is\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003emountainous\u003c/span\u003e), and complex noun constructions based on action nouns (e.g., \u003cem\u003eThe jackals howled all night. We could not sleep because of the\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ejackals\u0026rsquo; howling\u003c/span\u003e). Because informational discourse relies heavily on morphologically complex forms of this kind (Berman, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Berman \u0026amp; Nir-Sagiv, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Fang \u0026amp; Schleppegrell, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), it is therefore not surprising that morpho-lexical knowledge showed a selective contribution to informational text comprehension. These findings point to a division of labor between vocabulary and morpho-lexical knowledge: whereas vocabulary supports comprehension across genres, morpho-lexical knowledge appears to be especially relevant for informational texts. This pattern highlights the importance of considering the internal structure of the lexicon when modeling genre-specific comprehension.\u003c/p\u003e \u003cp\u003eBeyond their contribution to comprehension, both lexical measures were also related to reading processes themselves. In the model, morpho-lexical knowledge contributed to reading accuracy, supporting the view that morphological analysis facilitates word identification in unpointed Hebrew by constraining possible lexical candidates and supporting morpho-orthographic identification (Bar-On \u0026amp; Ravid, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Share \u0026amp; Bar-On, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Vocabulary knowledge, in turn, was associated with supra-lexical monitoring efficiency, indicating that readers with stronger vocabulary skills exhibit more efficient conflict detection and meaning revision (e.g., Cartwright et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; McNamara et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In line with DIER model (Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), these findings reinforce the idea that lexical knowledge supports reading comprehension both directly, by enabling efficient meaning construction, and indirectly, by shaping the quality of word identification and the effectiveness of supra-lexical regulation.\u003c/p\u003e \u003cp\u003eContribution of decoding skills to reading comprehension\u003c/p\u003e \u003cp\u003e Decoding skills were assessed through oral reading of connected texts rather than isolated words. This choice reflects the characteristics of Hebrew orthography, in which word identification in the unpointed script relies heavily on contextual information, making connected text a more ecologically valid medium for assessing reading processes. At the same time, the use of text-level measures raises the possibility that decoding indices may incorporate higher-level processes. To address this concern, reading accuracy and reading speed were analyzed separately, allowing us to distinguish between components of word identification within connected text and to avoid conflating them into a single fluency measure. Overall, decoding-related reading skills played a relatively limited role in explaining individual differences in reading comprehension in the present sample. This pattern is consistent with models proposing that decoding accuracy becomes less predictive of comprehension in the middle elementary grades, as variability in comprehension increasingly reflects higher-level linguistic and regulatory processes (Cain \u0026amp; Oakhill, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Catts et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Garc\u0026iacute;a \u0026amp; Cain, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Within this overall pattern, the only direct decoding effect emerged for reading speed, and only for informational text comprehension. This selective effect suggests that processing efficiency continues to matter under conditions of increased linguistic density and conceptual load (Best et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Eason et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). From the perspective of Kintsch\u0026rsquo;s construction\u0026ndash;integration framework (Kintsch, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), informational comprehension places heavier demands on building and integrating a dense \u003cem\u003etextbase\u003c/em\u003e representation, where efficient processing of successive propositions is critical. When processing demands are high, slower reading may constrain the reader\u0026rsquo;s ability to maintain and integrate multiple informational units. Narrative comprehension, by contrast, relies more strongly on the construction of a \u003cem\u003esituation model\u003c/em\u003e grounded in causal and temporal relations among events, which can be supported by lexical knowledge and background schemas even when reading proceeds relatively slowly.\u003c/p\u003e \u003cp\u003eIn contrast to reading speed, reading accuracy did not exert a direct effect on comprehension in either genre. At this stage of development, most children have already achieved reliable word identification, as evidenced by uniformly high accuracy scores (M\u0026thinsp;=\u0026thinsp;96.49%, SD\u0026thinsp;=\u0026thinsp;2.99), leaving little variability in decoding accuracy to account for individual differences in reading comprehension. Reading accuracy, however, showed a significant indirect contribution to comprehension through monitoring ability. This pattern indicates that accurate word identification serves as a foundational skill that supports readers\u0026rsquo; ability to detect and resolve inconsistencies during reading. It may also reflect differences in readers\u0026rsquo; orientation to accuracy, such that those who attend more closely to producing accurate word forms are also more likely to notice mismatches and initiate correction when errors occur. Importantly, the differential contributions of accuracy and speed do not reflect a trade-off between these components. Although accuracy and speed were moderately to strongly correlated (r = .62, p \u0026lt; .001), indicating substantial shared variance, each showed distinct pathways within the model.\u003c/p\u003e \u003cp\u003eContribution of supra-lexical monitoring processes\u003c/p\u003e \u003cp\u003eSupra-lexical monitoring, as indexed by the Garden Path task, showed a significant and comparable direct contribution to both narrative and informational comprehension. Although the magnitude of this effect was modest, it remained significant after accounting for lexical knowledge and decoding, indicating that monitoring explains unique variance in comprehension beyond foundational reading skills. This finding aligns with meta-analytic evidence demonstrating a stable association between executive processes and reading comprehension across development (Follmer, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as well as with studies showing that reading-specific executive tasks contribute uniquely to comprehension (Cartwright et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Peng et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe absence of a genre interaction did not support the hypothesis that monitoring would show a stronger contribution to informational than to narrative comprehension. In line with Escobar and Espinoza (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), the present findings indicate that monitoring is not selectively tied to informational reading. While informational texts may increase demands at the level of text-base integration, narrative texts may impose regulatory demands at the level of situation-model updating, including revising causal interpretations and character intentions (Graesser et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Kintsch, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Kintsch \u0026amp; Kintsch, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Thus, the absence of a genre interaction does not imply equivalent processing demands but rather suggests that supra-lexical monitoring operates across representational levels, with genre differences emerging in locus rather than magnitude. This pattern may be particularly pronounced in Hebrew, where pervasive lexical ambiguity in the unpointed script requires continuous reliance on contextual monitoring across reading situations, potentially reducing genre-based differences in the magnitude of monitoring demands.\u003c/p\u003e \u003cp\u003eFinally, the mediating role of monitoring provides a theoretical insight. Monitoring partially mediated the relation between lower-level reading skills and comprehension, suggesting that reading and comprehension are best conceptualized as components of a continuous regulatory system rather than discrete stages. Within both the Combinatorial Model and the Lexical Quality framework, monitoring can be understood as a supra-lexical mechanism that coordinates bottom-up word identification with top-down contextual integration, enabling flexible revision when lexical interpretations conflict with context. Taken together, these findings support the view that supra-lexical monitoring functions as a bridging mechanism through which lexical quality and decoding efficiency are translated into coherent text comprehension.\u003c/p\u003e \u003cp\u003eConclusions, limitations and implications\u003c/p\u003e \u003cp\u003eThe present study advances an integrative account of reading comprehension by demonstrating how lexical knowledge, decoding processes, and supra-lexical monitoring jointly contribute to comprehension across text genres. The results reveal both shared and genre-specific pathways to comprehension, indicating that narrative and informational texts do not differ simply in overall difficulty, but rather impose distinct patterns of demands across representational levels, with each genre engaging different configurations of lexical, decoding, and supra-lexical processes. Crucially, supra-lexical monitoring emerged as a domain-general regulatory mechanism that operates across genres, linking lower-level reading processes with higher-level interpretation. These findings extend both the Lexical Quality Hypothesis and the Combinatorial Model by highlighting the role of context-sensitive regulation in coordinating multiple levels of reading.\u003c/p\u003e \u003cp\u003eSeveral limitations of the present study should be considered alongside directions for future research. First, the sample was restricted to fourth-grade readers, and the findings therefore reflect a specific stage in the development of reading proficiency, at which basic word identification has largely stabilized but higher-level processes continue to develop. Also, the study was conducted in Hebrew, an orthography characterized by pervasive lexical ambiguity due to the unpointed script. This combination of developmental stage and orthographic characteristics may shape the role and relative importance of supra-lexical monitoring processes. Future research should therefore examine whether the observed patterns generalize across developmental stages and orthographies, including both earlier and later phases of reading acquisition and languages with different degrees of transparency and ambiguity. Second, the study relied on a single text for each genre. Although the texts were carefully selected and matched, genre-related effects may be influenced by text-specific characteristics, and the use of multiple texts per genre would allow for a more robust assessment of genre-related processing demands. Finally, supra-lexical monitoring was assessed via a single task. While the Garden Path paradigm provides a well-established measure of real-time conflict detection and revision, future studies could benefit from incorporating additional measures to capture a broader range of monitoring processes.\u003c/p\u003e \u003cp\u003eThe findings have implications for reading instructions. First, they highlight the importance of fostering supra-lexical monitoring processes in reading development. Instruction should support students\u0026rsquo; regulation of understanding by detecting inconsistencies, revising interpretations, and using contextual information to resolve ambiguity, thereby supporting the integration of word-level and text-level processes. Second, instructional approaches should be sensitive to genre-specific demands. Rather than viewing informational texts as uniformly more difficult, educators should recognize that different text types engage different configurations of cognitive and linguistic processes. Third, the differentiated contribution of decoding components indicates that fluency instruction should move beyond general practice toward targeted support that considers the interaction between processing efficiency and text characteristics. Finally, the findings underscore the importance of integrating lexical and morphological instruction within reading curricula, particularly for supporting comprehension of informational texts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSP and AB contributed to the conception and design of the study, developed the theoretical framework, conducted the statistical analyses, interpreted the findings, and drafted and revised the manuscript. ML and OL contributed to data collection, coding, and data curation as graduate research students whose research projects provided the empirical basis for the present study. SP and AB jointly supervised the research process. All authors reviewed the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank Liron Lerdan, Dafna Biton, Shlomit Ostri, and Noa Morag for their careful work in data collection and coding. We are also grateful to Haya Fogel-Grinvald for statistical consultation and support with the analyses. Finally, we gratefully acknowledge the late Dr. Ronit Levy, who contributed to the early conceptualization of the broader research project from which this study emerged. Her thoughtful perspective and intellectual contribution helped shape the initial thinking behind this work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not publicly available due to privacy and ethical restrictions involving child participants and school-based assessment data. Data may be made available from the corresponding author upon reasonable request and subject to applicable ethical approvals and data-sharing agreements.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBaretta, L., Tomitch, L. M. B., MacNair, N., Lim, V. K., \u0026amp; Waldie, K. E. (2009). Inference making while reading narrative and expository texts: An ERP study. \u003cem\u003ePsychology \u0026amp; Neuroscience\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(2), 137\u0026ndash;145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3922/j.psns.2009.2.005\u003c/span\u003e\u003cspan address=\"10.3922/j.psns.2009.2.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBar-On, A., Dattner, E., \u0026amp; Braun-Peretz, O. (2019). Resolving homography: The role of post-homograph context in reading aloud ambiguous sentences in Hebrew. \u003cem\u003eApplied Psycholinguistics\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e, 1405\u0026ndash;1420. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0142716419000316\u003c/span\u003e\u003cspan address=\"10.1017/S0142716419000316\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBar-On, A., Dattner, E., \u0026amp; Ravid, D. (2017). Context effects on heterophonic-homography resolution in learning to read Hebrew. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(3), 463\u0026ndash;487. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-016-9685-1\u003c/span\u003e\u003cspan address=\"10.1007/s11145-016-9685-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBar-On, A., Oron, T., \u0026amp; Peleg, O. (2021). Semantic and syntactic constraints in resolving homography: A developmental study in Hebrew. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(8), 2103\u0026ndash;2126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-021-10129-6\u003c/span\u003e\u003cspan address=\"10.1007/s11145-021-10129-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBar-On, A., \u0026amp; Ravid, D. (2011). Morphological analysis in learning to read pseudowords in Hebrew. \u003cem\u003eApplied Psycholinguistics\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(3), 553\u0026ndash;581. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S014271641100021X\u003c/span\u003e\u003cspan address=\"10.1017/S014271641100021X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBellocchi, S., Priolo, D., \u0026amp; Bonifacci, P. (2025). The simple view of reading in monolingual and language-minority bilingual children learning to read in French or Italian: Evidence from a direct cross-linguistic comparison study. \u003cem\u003eJournal of Research in Reading\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(3), 259\u0026ndash;277. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1467-9817.70007\u003c/span\u003e\u003cspan address=\"10.1111/1467-9817.70007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerman, R. A. (2008). The psycholinguistics of developing text construction. \u003cem\u003eJournal of Child Language\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(4), 735\u0026ndash;771. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0305000908008787\u003c/span\u003e\u003cspan address=\"10.1017/S0305000908008787\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerman, R. A. (2016). Linguistic literacy and later language development. In J. Perera, M. Aparici, E. Rosado, \u0026amp; N. Salas (Eds.), \u003cem\u003eWritten and Spoken Language Development across the Lifespan: Essays in Honour of Liliana Tolchinsky\u003c/em\u003e (Vol. 11, pp. 181\u0026ndash;200). Springer International Publishing. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-319-21136-7_12\u003c/span\u003e\u003cspan address=\"10.1007/978-3-319-21136-7_12\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerman, R. A., \u0026amp; Nir-Sagiv, B. (2009). Clause packaging in narratives: A crosslinguistic developmental study. In J. Guo, E. Lieven, N. Budwig, S. Ervin-Tripp, K. Nakamura, \u0026amp; S. Ozcaliskan (Eds.), \u003cem\u003eCrosslinguistic approaches to the psychology of language: Research in the tradition of Dan Isaac Slobin\u003c/em\u003e (pp. 149\u0026ndash;162). Psychology.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerman, R. A., \u0026amp; Slobin, D. I. (1994). \u003cem\u003eRelating events in narrative: A crosslinguistic developmental study\u003c/em\u003e. Psychology.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBest, R. M., Floyd, R. G., \u0026amp; McNamara, D. S. (2008). Differential competencies contributing to children\u0026rsquo;s comprehension of narrative and expository texts. \u003cem\u003eReading Psychology\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(2), 137\u0026ndash;164. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02702710801963951\u003c/span\u003e\u003cspan address=\"10.1080/02702710801963951\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBotvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., \u0026amp; Cohen, J. D. (2001). Conflict monitoring and cognitive control. \u003cem\u003ePsychological Review\u003c/em\u003e, \u003cem\u003e108\u003c/em\u003e(3), 624\u0026ndash;652. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-295X.108.3.624\u003c/span\u003e\u003cspan address=\"10.1037/0033-295X.108.3.624\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCain, K., \u0026amp; Oakhill, J. (2008). \u003cem\u003eChildren\u0026rsquo;s comprehension problems in oral and written language: A cognitive perspective\u003c/em\u003e. Guilford Press.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCartwright, K. B., Marshall, T. R., \u0026amp; Hatfield, N. A. (2020). Concurrent and longitudinal contributions of a brief assessment of reading-specific executive function to reading comprehension in first and second grade students. \u003cem\u003eMind Brain and Education\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 114\u0026ndash;123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mbe.12236\u003c/span\u003e\u003cspan address=\"10.1111/mbe.12236\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCatts, H. W., Hogan, T. P., \u0026amp; Adlof, S. M. (2005). Developmental changes in reading and reading disabilities. In H. W. Catts, \u0026amp; A. G. Kamhi (Eds.), \u003cem\u003eThe connections between language and reading disabilities\u003c/em\u003e (pp. 25\u0026ndash;40). Lawrence Erlbaum Associates.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCervetti, G. N., Bravo, M. A., Hiebert, E. H., Pearson, P. D., \u0026amp; Jaynes, C. A. (2009). Text genre and science content: Ease of reading, comprehension, and reader preference. \u003cem\u003eReading Psychology\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(6), 487\u0026ndash;511. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02702710902733550\u003c/span\u003e\u003cspan address=\"10.1080/02702710902733550\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChall, J. S. (1983). \u003cem\u003eStages of Reading Development\u003c/em\u003e. McGraw-Hill.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClinton, V., Taylor, T., Bajpayee, S., Davison, M. L., Carlson, S. E., \u0026amp; Seipel, B. (2020). Inferential comprehension differences between narrative and expository texts: A systematic review and meta-analysis. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(9), 2223\u0026ndash;2248. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-020-10044-2\u003c/span\u003e\u003cspan address=\"10.1007/s11145-020-10044-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz Neri, N., Bernholt, S., H\u0026auml;rtig, H., Schmitz, A., \u0026amp; Retelsdorf, J. (2023). Cognitive and motivational characteristics as predictors of students\u0026rsquo; expository versus narrative text comprehension. \u003cem\u003eEuropean Journal of Psychology of Education\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(2), 885\u0026ndash;905. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10212-023-00717-1\u003c/span\u003e\u003cspan address=\"10.1007/s10212-023-00717-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeacon, S. H., Kieffer, M. J., \u0026amp; Laroche, A. (2014). The relation between morphological awareness and reading comprehension: Evidence from mediation and longitudinal models. \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(6), 432\u0026ndash;451. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888438.2014.926907\u003c/span\u003e\u003cspan address=\"10.1080/10888438.2014.926907\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDickens, R. H., \u0026amp; Meisinger, E. B. (2017). Examining the effects of reading modality and passage genre on reading comprehension in middle school students. \u003cem\u003eReading Psychology\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(3), 321\u0026ndash;347. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02702711.2016.1263701\u003c/span\u003e\u003cspan address=\"10.1080/02702711.2016.1263701\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuke, N. K., \u0026amp; Cartwright, K. B. (2021). The science of reading progresses: Communicating advances beyond the simple view of reading. \u003cem\u003eReading Research Quarterly\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(S1), S25\u0026ndash;S44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/rrq.411\u003c/span\u003e\u003cspan address=\"10.1002/rrq.411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEason, S. H., Goldberg, L. F., Young, K. M., Geist, M. C., \u0026amp; Cutting, L. E. (2012). Reader\u0026ndash;text interactions: How differential text and question types influence cognitive skills needed for reading comprehension. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e104\u003c/em\u003e(3), 515\u0026ndash;528. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0027182\u003c/span\u003e\u003cspan address=\"10.1037/a0027182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEllis, N. C. (2008). Usage-based and form-focused language acquisition: The associative learning of constructions, learned attention, and the limited L2 endstate. In P. Robinson, \u0026amp; N. C. Ellis (Eds.), \u003cem\u003eHandbook of Cognitive Linguistics and Second Language Acquisition\u003c/em\u003e (pp. 372\u0026ndash;405). Routledge.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEscobar, J. P., \u0026amp; Espinoza, V. (2025). Direct and indirect effects of inhibition, working memory and cognitive flexibility on reading comprehension of narrative and expository texts: Same or different effects? \u003cem\u003eReading and Writing Quarterly\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(2), 176\u0026ndash;192. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10573569.2024.2400993\u003c/span\u003e\u003cspan address=\"10.1080/10573569.2024.2400993\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang, Z., \u0026amp; Schleppegrell, M. J. (2010). Disciplinary literacies across content areas: Supporting secondary reading through functional language analysis. \u003cem\u003eJournal of Adolescent \u0026amp; Adult Literacy\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(7), 587\u0026ndash;597. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1598/JAAL.53.7.6\u003c/span\u003e\u003cspan address=\"10.1598/JAAL.53.7.6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFollmer, D. J. (2018). Executive function and reading comprehension: A meta-analytic review. \u003cem\u003eEducational Psychologist\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(1), 42\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00461520.2017.1309295\u003c/span\u003e\u003cspan address=\"10.1080/00461520.2017.1309295\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoorman, B. R., Petscher, Y., \u0026amp; Bishop, M. D. (2012). The incremental variance of morphological knowledge to reading comprehension in grades 3\u0026ndash;10 beyond prior reading comprehension, spelling, and text reading efficiency. \u003cem\u003eLearning and Individual Differences\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(6), 792\u0026ndash;798. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lindif.2012.07.009\u003c/span\u003e\u003cspan address=\"10.1016/j.lindif.2012.07.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrazier, L., \u0026amp; Rayner, K. (1982). Making and correcting errors during sentence comprehension: Eye movements in the analysis of structurally ambiguous sentences. \u003cem\u003eCognitive Psychology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 178\u0026ndash;210. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0010-0285(82)90008-1\u003c/span\u003e\u003cspan address=\"10.1016/0010-0285(82)90008-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a, J. R., \u0026amp; Cain, K. (2014). Decoding and reading comprehension: A meta-analysis to identify which reader and assessment characteristics influence the strength of the relationship in English. \u003cem\u003eReview of Educational Research\u003c/em\u003e, \u003cem\u003e84\u003c/em\u003e(1), 74\u0026ndash;111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3102/0034654313499616\u003c/span\u003e\u003cspan address=\"10.3102/0034654313499616\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraesser, A. C., McNamara, D. S., \u0026amp; Kulikowich, J. M. (2011). Coh-metrix: Providing multilevel analyses of text characteristics. \u003cem\u003eEducational Researcher\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(5), 223\u0026ndash;234. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3102/0013189X11413260\u003c/span\u003e\u003cspan address=\"10.3102/0013189X11413260\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraesser, A. C., Singer, M., \u0026amp; Trabasso, T. (1994). Constructing inferences during narrative text comprehension. \u003cem\u003ePsychological Review\u003c/em\u003e, \u003cem\u003e101\u003c/em\u003e(3), 371\u0026ndash;395. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-295X.101.3.371\u003c/span\u003e\u003cspan address=\"10.1037/0033-295X.101.3.371\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHannon, B. (2022). Children\u0026rsquo;s comprehension of narrative and expository texts: The contributions of word decoding and knowledge integration skills vary within and between text types. \u003cem\u003eJournal of Education and Training Studies\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(4), 1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.11114/jets.v10i4.5465\u003c/span\u003e\u003cspan address=\"10.11114/jets.v10i4.5465\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoover, W. A. (2023). The simple view of reading and its broad types of reading difficulties. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(9), 2277\u0026ndash;2298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-023-10471-x\u003c/span\u003e\u003cspan address=\"10.1007/s11145-023-10471-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoover, W. A., \u0026amp; Gough, P. B. (1990). The simple view of reading. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(2), 127\u0026ndash;160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00401799\u003c/span\u003e\u003cspan address=\"10.1007/BF00401799\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoshi, R. M. (2018). Simple view of reading (SVR) in different orthographies: Seeing the forest with the trees. In T. Lachmann, \u0026amp; T. Weis (Eds.), \u003cem\u003eReading and dyslexia: From basic functions to higher order cognition\u003c/em\u003e (pp. 71\u0026ndash;80). Springer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoshi, R. M., Ji, X. R., Breznitz, Z., Amiel, M., \u0026amp; Yulia, A. (2015). Validation of the Simple View of Reading in Hebrew\u0026mdash;A Semitic Language. \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), 243\u0026ndash;252. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888438.2015.1010117\u003c/span\u003e\u003cspan address=\"10.1080/10888438.2015.1010117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, Y. S. G., Quinn, J. M., \u0026amp; Petscher, Y. (2021). What is text reading fluency and is it a predictor or an outcome of reading comprehension? A longitudinal investigation. \u003cem\u003eDevelopmental Psychology\u003c/em\u003e, \u003cem\u003e57\u003c/em\u003e(5), 718\u0026ndash;732. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/dev0001167\u003c/span\u003e\u003cspan address=\"10.1037/dev0001167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. \u003cem\u003ePsychological Review\u003c/em\u003e, \u003cem\u003e95\u003c/em\u003e(2), 163\u0026ndash;182. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-295X.95.2.163\u003c/span\u003e\u003cspan address=\"10.1037/0033-295X.95.2.163\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKintsch, W., \u0026amp; Kintsch, E. (2005). Comprehension. \u003cem\u003eChildren\u0026rsquo;s reading comprehension and assessment\u003c/em\u003e. Routledge.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoriat, A., \u0026amp; Goldsmith, M. (1996). Monitoring and control processes in memory. \u003cem\u003ePsychological Review\u003c/em\u003e, \u003cem\u003e103\u003c/em\u003e, 490\u0026ndash;517.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraal, A., Koornneef, A. W., Saab, N., \u0026amp; van den Broek, P. W. (2018). Processing of expository and narrative texts by low- and high-comprehending children. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(9), 2017\u0026ndash;2040. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-017-9789-2\u003c/span\u003e\u003cspan address=\"10.1007/s11145-017-9789-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLahmi-Kakon, L., Ben-Zvi, G., \u0026amp; Bar-On, A. (2020). Derived word completion task for assessment of morpho-lexical knowledge in 3rd\u0026ndash;7th grade. \u003cem\u003eDASH BARESHET: The Israeli Journal of Language Speech and Hearing Disorders\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevesque, K. C., Kieffer, M. J., \u0026amp; Deacon, S. H. (2017). Morphological awareness and reading comprehension: Examining mediating factors. \u003cem\u003eJournal of Experimental Child Psychology\u003c/em\u003e, \u003cem\u003e160\u003c/em\u003e, 1\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jecp.2017.02.015\u003c/span\u003e\u003cspan address=\"10.1016/j.jecp.2017.02.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiebfreund, M. D. (2021). Cognitive and Motivational Predictors of Narrative and Informational Text Comprehension. \u003cem\u003eReading Psychology\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(2), 177\u0026ndash;196. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02702711.2021.1888346\u003c/span\u003e\u003cspan address=\"10.1080/02702711.2021.1888346\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, Y., Groen, M. A., \u0026amp; Cain, K. (2024). The association between morphological awareness and reading comprehension in children: A systematic review and meta-analysis. \u003cem\u003eEducational Research Review\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e, 100571. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.edurev.2023.100571\u003c/span\u003e\u003cspan address=\"10.1016/j.edurev.2023.100571\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManshari, M., \u0026amp; Bar-On, A. (2020). Collocation completion task: Lexical knowledge assessment tool. \u003cem\u003eDASH BARESHET: The Israeli Journal of Language Speech and Hearing Disorders\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMar, R. A., Li, J., Nguyen, A. T. P., \u0026amp; Ta, C. P. (2021). Memory and comprehension of narrative versus expository texts: A meta-analysis. \u003cem\u003ePsychonomic Bulletin \u0026amp; Review\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(3), 732\u0026ndash;749. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/s13423-020-01853-1\u003c/span\u003e\u003cspan address=\"10.3758/s13423-020-01853-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNamara, D. S., Ozuru, Y., \u0026amp; Floyd, R. G. (2011). Comprehension challenges in the fourth grade: The roles of text cohesion, text genre, and readers\u0026rsquo; prior knowledge. \u003cem\u003eInternational Electronic Journal of Elementary Education\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 229\u0026ndash;257.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyer, B. J. F., \u0026amp; Ray, M. N. (2017). Structure strategy interventions: Increasing reading comprehension of expository text. \u003cem\u003eInternational Electronic Journal of Elementary Education\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 127\u0026ndash;152.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller, A., Swett, K., Burns, S., Davis, N., Hoeft, F., Petrill, S. A., \u0026amp; Cutting, L. E. (2013). Comprehending expository texts: The dynamic neurobiological correlates of building a coherent text representation. \u003cem\u003eFrontiers in Human Neuroscience\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e, 853. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fnhum.2013.00853\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2013.00853\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagy, W., Berninger, V. W., \u0026amp; Abbott, R. D. (2006). Contributions of morphology beyond phonology to literacy outcomes of upper elementary and middle-school students. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e(1), 134\u0026ndash;147. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-0663.98.1.134\u003c/span\u003e\u003cspan address=\"10.1037/0022-0663.98.1.134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNation, I. S. P. (2001). \u003cem\u003eLearning Vocabulary in Another Language\u003c/em\u003e. Cambridge University Press.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Authority for Measurement and Evaluation in Education. (2014). \u003cem\u003eMeitzav: Hebrew reading comprehension assessments for Grade 5 (narrative and informational text units)\u003c/em\u003e. Ministry of Education. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rama.edu.gov.il\u003c/span\u003e\u003cspan address=\"https://rama.edu.gov.il\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Reading Panel (2000). \u003cem\u003eTeaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction\u003c/em\u003e (Nos. 00\u0026ndash;4769). National Institute of Child Health and Human Development. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nichd.nih.gov/publications/pubs/nrp/Documents/report.pdf\u003c/span\u003e\u003cspan address=\"https://www.nichd.nih.gov/publications/pubs/nrp/Documents/report.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNelson, T. O. (1990). Metamemory: A theoretical framework and new findings. In G. H. Bower (Ed.), \u003cem\u003ePsychology of Learning and Motivation\u003c/em\u003e (Vol. 26, pp. 125\u0026ndash;173). Academic.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeuman, S. B., Kaefer, T., \u0026amp; Pinkham, A. (2025). Is narrative in printed text primary for knowledge-building? An analysis of genre and medium. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(1), 91\u0026ndash;119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-025-10634-y\u003c/span\u003e\u003cspan address=\"10.1007/s11145-025-10634-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNippold, M. A. (2007). \u003cem\u003eLater language development: School-age children, adolescents, and young adults\u003c/em\u003e. Pro-Ed.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNovick, J. M., Trueswell, J. C., \u0026amp; Thompson-Schill, S. L. (2005). Cognitive control and parsing: Reexamining the role of Broca\u0026rsquo;s area in sentence comprehension. \u003cem\u003eCognitive Affective \u0026amp; Behavioral Neuroscience\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(3), 263\u0026ndash;281. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/CABN.5.3.263\u003c/span\u003e\u003cspan address=\"10.3758/CABN.5.3.263\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuellette, G. P. (2006). What\u0026rsquo;s meaning got to do with it: The role of vocabulary in word reading and reading comprehension. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e(3), 554\u0026ndash;566. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-0663.98.3.554\u003c/span\u003e\u003cspan address=\"10.1037/0022-0663.98.3.554\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePadeliadu, S., \u0026amp; Antoniou, F. (2014). The relationship between reading comprehension, decoding, and fluency in Greek: A cross-sectional study. \u003cem\u003eReading and Writing Quarterly\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(1), 1\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10573569.2013.758932\u003c/span\u003e\u003cspan address=\"10.1080/10573569.2013.758932\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeng, P., Liu, Y., Cartwright, K., Goodrich, M., Koziol, N., Ma, C., \u0026amp; Whitmarsh, C. (2024). The role of domain-general, behavioral, and reading-specific executive function in reading comprehension: Does context-specific executive function matter? \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(6), 713\u0026ndash;736. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888438.2024.2409635\u003c/span\u003e\u003cspan address=\"10.1080/10888438.2024.2409635\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerfetti, C. A. (2007). Reading ability: Lexical quality to comprehension. \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(4), 357\u0026ndash;383. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888430701530730\u003c/span\u003e\u003cspan address=\"10.1080/10888430701530730\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerfetti, C. A., \u0026amp; Hart, L. (2002). The lexical quality hypothesis. In L. T. Verhoeven, C. Elbro, \u0026amp; P. Reitsma (Eds.), \u003cem\u003ePrecursors of functional literacy\u003c/em\u003e (Vol. 11, pp. 67\u0026ndash;86). John Benjamins Publishing.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerfetti, C. A., \u0026amp; Stafura, J. (2014). Word knowledge in a theory of reading comprehension. \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), 22\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888438.2013.827687\u003c/span\u003e\u003cspan address=\"10.1080/10888438.2013.827687\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrimor, L., Pierce, M. E., \u0026amp; Katzir, T. (2011). Predicting reading comprehension of narrative and expository texts among Hebrew-speaking readers with and without a reading disability. \u003cem\u003eAnnals of Dyslexia\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(2), 242\u0026ndash;268. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11881-011-0059-8\u003c/span\u003e\u003cspan address=\"10.1007/s11881-011-0059-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProtopapas, A., Mouzaki, A., Sideridis, G. D., Kotsolakou, A., \u0026amp; Simos, P. G. (2013). The role of vocabulary in the context of the simple view of reading. \u003cem\u003eReading and Writing Quarterly\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(2), 168\u0026ndash;202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10573569.2013.758569\u003c/span\u003e\u003cspan address=\"10.1080/10573569.2013.758569\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProtopapas, A., Sideridis, G. D., Mouzaki, A., \u0026amp; Simos, P. G. (2007). Development of lexical mediation in the relation between reading comprehension and word reading skills in Greek. \u003cem\u003eScientific Studies of Reading\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(3), 165\u0026ndash;197. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10888430701344322\u003c/span\u003e\u003cspan address=\"10.1080/10888430701344322\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuinn, J. M., Wagner, R. K., Petscher, Y., \u0026amp; Lopez, D. (2015). Developmental relations between vocabulary knowledge and reading comprehension: A latent change score modeling study. \u003cem\u003eChild Development\u003c/em\u003e, \u003cem\u003e86\u003c/em\u003e(1), 159\u0026ndash;175. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/cdev.12292\u003c/span\u003e\u003cspan address=\"10.1111/cdev.12292\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRassel, A., Facon, B., \u0026amp; Casalis, S. (2021). Morphological awareness and learning to read: Impact of socio-economic status in French third graders. \u003cem\u003eJournal of Research in Reading\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(1), 228\u0026ndash;246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1467-9817.12321\u003c/span\u003e\u003cspan address=\"10.1111/1467-9817.12321\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaven, J., Prieler, J., \u0026amp; Fischer, G. (1996). \u003cem\u003eStandard progressive matrices\u003c/em\u003e. Oxford Psychologists.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRavid, D., \u0026amp; Berman, R. A. (2010). Developing Noun Phrase Complexity at School Age: A Text-Embedded Cross-Linguistic Analysis. \u003cem\u003eFirst Language\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(1), 3\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0142723709350531\u003c/span\u003e\u003cspan address=\"10.1177/0142723709350531\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRavid, D., \u0026amp; Mashraki, Y. E. (2007). Prosodic reading, reading comprehension and morphological skills in Hebrew-speaking fourth graders. \u003cem\u003eJournal of Research in Reading\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(2), 140\u0026ndash;156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1467-9817.2007.00340.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1467-9817.2007.00340.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos, S., Cadime, I., Viana, F. L., Chaves-Sousa, S., Gayo, E., Maia, J., \u0026amp; Ribeiro, I. (2017). Assessing reading comprehension with narrative and expository texts: Dimensionality and relationship with fluency, vocabulary and memory. \u003cem\u003eScandinavian Journal of Psychology\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(1), 1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sjop.12335\u003c/span\u003e\u003cspan address=\"10.1111/sjop.12335\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScarborough, H. S. (2001). Connecting early language and literacy to later reading (dis) abilities: Evidence, theory, and practice. In F. Fletcher-Campbell, J. Soler, \u0026amp; G. Reid (Eds.), \u003cem\u003eApproaching difficulties in literacy development: Assessment, pedagogy and programmes\u003c/em\u003e (pp. 97\u0026ndash;110). SAGE Publications Ltd.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShany, M., Lahman, D., Shalem, T., Bahat, A., \u0026amp; Zayger, T. (2006). \u003cem\u003eAlef ad taf: A system for diagnosing disabilities in the processes of reading and writing according to national norms\u003c/em\u003e. Yesod Publishing.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShare, D. L. (2008). On the Anglocentricities of current reading research and practice: The perils of overreliance on an outlier orthography. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e134\u003c/em\u003e(4), 584\u0026ndash;615. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-2909.134.4.584\u003c/span\u003e\u003cspan address=\"10.1037/0033-2909.134.4.584\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShare, D. L. (2025). Blueprint for a universal theory of learning to read: The combinatorial model. \u003cem\u003eReading Research Quarterly\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e(2), 1\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/rrq.603\u003c/span\u003e\u003cspan address=\"10.1002/rrq.603\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShare, D. L., \u0026amp; Bar-On, A. (2018). Learning to read a Semitic abjad: The triplex model of Hebrew reading development. \u003cem\u003eJournal of Learning Disabilities\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(5), 444\u0026ndash;453. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0022219417718198\u003c/span\u003e\u003cspan address=\"10.1177/0022219417718198\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShimron, J., \u0026amp; Sivan, T. (1994). Reading proficiency and orthography evidence from Hebrew and English. \u003cem\u003eLanguage Learning\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(1), 5\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1467-1770.1994.tb01447.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1467-1770.1994.tb01447.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimpson, I. C., Moreno-P\u0026eacute;rez, F. J., \u0026amp; Rodr\u0026iacute;guez-Ortiz, I. (2019). los R., Vald\u0026eacute;s-Coronel, M., \u0026amp; Salda\u0026ntilde;a, D. The effects of morphological and syntactic knowledge on reading comprehension in spanish speaking children. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(2), 329\u0026ndash;348. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-019-09964-5\u003c/span\u003e\u003cspan address=\"10.1007/s11145-019-09964-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnow, C. E. (2018). Simple and not-so-simple views of reading. \u003cem\u003eRemedial and Special Education\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(5), 313\u0026ndash;316. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0741932518770288\u003c/span\u003e\u003cspan address=\"10.1177/0741932518770288\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTong, X., Deacon, S. H., Kirby, J. R., Cain, K., \u0026amp; Parrila, R. (2011). Morphological awareness: A key to understanding poor reading comprehension in English. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e103\u003c/em\u003e(3), 523\u0026ndash;534. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0023495\u003c/span\u003e\u003cspan address=\"10.1037/a0023495\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTong, X., Tong, X., \u0026amp; McBride, C. (2017). Unpacking the relation between morphological awareness and Chinese word reading: Levels of morphological awareness and vocabulary. \u003cem\u003eContemporary Educational Psychology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e, 167\u0026ndash;178. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cedpsych.2016.07.003\u003c/span\u003e\u003cspan address=\"10.1016/j.cedpsych.2016.07.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUysal, P. K., \u0026amp; Bilge, H. (2018). An investigation on the relationship between reading fluency and level of reading comprehension according to the type of texts. \u003cem\u003eInternational Electronic Journal of Elementary Education\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(2), 161\u0026ndash;172.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaknin-Nusbaum, V., Sarid, M., \u0026amp; Shimron, J. (2015). Morphological awareness and reading in second and fifth grade: Evidence from Hebrew. \u003cem\u003eReading and Writing\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(2), 229\u0026ndash;244. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11145-015-9587-7\u003c/span\u003e\u003cspan address=\"10.1007/s11145-015-9587-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Silfhout, G., Evers-Vermeul, J., \u0026amp; Sanders, T. (2015). Connectives as processing signals: How students benefit in processing narrative and expository texts. \u003cem\u003eDiscourse Processes\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(1), 47\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/0163853X.2014.905237\u003c/span\u003e\u003cspan address=\"10.1080/0163853X.2014.905237\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWechsler, D. (2012). \u003cem\u003eWechsler intelligence scale for children\u0026ndash;fourth edition (WISC-IV), Hebrew version\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWray, A. (2002). \u003cem\u003eFormulaic Language and the Lexicon\u003c/em\u003e. Cambridge University Press.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu, Y., Barquero, L. A., Pickren, S. E., Taboada Barber, A., \u0026amp; Cutting, L. E. (2020). The relationship between cognitive skills and reading comprehension of narrative and expository texts: A longitudinal study from Grade 1 to Grade 4. \u003cem\u003eLearning and Individual Differences\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e, 101848. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lindif.2020.101848\u003c/span\u003e\u003cspan address=\"10.1016/j.lindif.2020.101848\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYildirim, K., Yildiz, M., \u0026amp; Ateş, S. (2011). Is vocabulary a strong variable predicting reading comprehension and does the prediction degree of vocabulary vary according to text types? \u003cem\u003eEducational Sciences: Theory \u0026amp; Practice\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(3), 1541\u0026ndash;1547.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoo, Y. (2024). On the dynamics of inferential behavior while reading expository and narrative texts. \u003cem\u003eBrain Sciences\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(5), 428. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/brainsci14050428\u003c/span\u003e\u003cspan address=\"10.3390/brainsci14050428\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabrucky, K. M., \u0026amp; Moore, D. (1999). Influence of text genre on adults\u0026rsquo; monitoring of understanding and recall. \u003cem\u003eEducational Gerontology\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(8), 691\u0026ndash;710. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/036012799267440\u003c/span\u003e\u003cspan address=\"10.1080/036012799267440\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, D., Ke, S., Echo, \u0026amp; Mo, Y. (2023). Morphology in reading comprehension among school-aged readers of English: A synthesis and meta-analytic structural equation modeling study. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e115\u003c/em\u003e(5), 683\u0026ndash;699. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/edu0000797\u003c/span\u003e\u003cspan address=\"10.1037/edu0000797\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"reading comprehension, lexical quality, morphological awareness, supra-lexical monitoring, narrative text, informational text","lastPublishedDoi":"10.21203/rs.3.rs-9574360/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9574360/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding how readers extract meaning from different text genres provides a critical test for models of reading comprehension. The present study integrates the Lexical Quality Hypothesis (Perfetti, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and the Combinatorial Model of reading acquisition (Share, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) to examine how lexical knowledge, decoding processes, and supra-lexical monitoring jointly support comprehension across narrative and informational texts in Hebrew. Ninety-four Hebrew-speaking fourth graders completed a comprehensive battery assessing vocabulary, morpho-lexical knowledge, reading accuracy and speed, supra-lexical monitoring (via a Garden Path paradigm), and comprehension of narrative and informational texts. Path analysis revealed both shared and genre-specific pathways, explaining substantial variance in comprehension (41% for narrative, 51% for informational). A common pathway emerged in which supra-lexical monitoring contributed directly to comprehension in both text types, linking word-level processes to higher-level meaning construction. Beyond this shared mechanism, distinct patterns were observed: narrative comprehension was primarily supported by vocabulary and monitoring, whereas informational comprehension relied on a broader constellation including morpho-lexical knowledge and reading speed. These findings highlight supra-lexical monitoring as a central regulatory mechanism in reading comprehension and demonstrate how readers flexibly adapt the relative contributions of lexical and decoding processes to meet genre-specific demands. The study advances an integrated account of comprehension by showing how shared and differential pathways emerge within a unified framework during the transition from learning to read to reading for learning.\u003c/p\u003e","manuscriptTitle":"Pathways to comprehension: The role of supra-lexical monitoring in narrative and informational text understanding","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 06:15:42","doi":"10.21203/rs.3.rs-9574360/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd67ce51-c2fa-4862-a735-562135d47f3d","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"4776037137750740751277868631455389380","date":"2026-05-04T06:47:31+00:00","index":21,"fulltext":""},{"type":"reviewerAgreed","content":"111562383434164388604734031852661733142","date":"2026-05-03T14:56:53+00:00","index":20,"fulltext":""},{"type":"reviewerAgreed","content":"224475997394888481995643413826966673062","date":"2026-05-03T13:15:36+00:00","index":19,"fulltext":""},{"type":"reviewerAgreed","content":"255999330218455249882952083878584904575","date":"2026-05-01T16:20:16+00:00","index":18,"fulltext":""},{"type":"reviewersInvited","content":"14","date":"2026-05-01T12:56:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-30T11:52:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-30T11:52:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reading and Writing","date":"2026-04-30T08:30:32+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T06:15:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 06:15:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9574360","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9574360","identity":"rs-9574360","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}