Although cross-linguistic influence involving the lexicon has been widely investigated, there is inconclusive evidence regarding potential CLI of syntax on L2 reading comprehension. Several behavioral studies involving children educated in L2 English-dominant environments found no relationship between L1 syntactic skills and L2 reading comprehension. In a study of adolescent Spanish-English bilinguals who were newcomers to the United States with prior schooling in Spanish, Garrison-Fletcher et al. (2019) found that general and academic reading comprehension, but not Spanish syntactic skills, were positive predictors of English text comprehension. Similarly, Swanson et al. (2008) assessed 68 third grade Spanish-English bilinguals with both Spanish and English reading component measures. Although L1 Spanish morphosyntactic knowledge positively predicted English reading comprehension, it did not do so uniquely—this relationship was explained by other English measures. With 123 children in grades 3–5, Leider et al. (2008) found a negative relationship between Spanish syntax and English sentence judgment performance but no relationship with English comprehension measured by cloze or multiple-choice tasks. Kieffer (2012) found a similar negative relationship between 295 kindergarten children’s Spanish oral language skills more broadly measured and later English reading comprehension in nationally representative longitudinal data. These three studies were conducted in the United States, where the L2 (English) is the dominant language used almost exclusively in public schools. Only one study with participants in this setting produced a contrasting result. In a longitudinal investigation of syntactic skills among 156 Spanish-English bilingual upper elementary students, Proctor et al. (2017) found that L1 syntax, measured with a sentence formulation task in the second grade, predicted English oral language and reading comprehension in the fifth grade. There is thus mixed evidence of cross-linguistic syntactic transfer in L2 English-dominant settings at different ages, with study findings variously suggesting interference, positive transfer, or no influence of L1 syntactic skills on L2 text comprehension.

In contrast, behavioral studies conducted in immersive bilingual education settings where bilingual literacy is explicitly instructed have found a consistent positive relationship between L1 syntax and L2 reading comprehension during the preschool to upper elementary years. Gabriele et al. (2009) examined a small sample of Spanish-English bilinguals in a bilingual education preschool program. Preschoolers’ performance on native Spanish structures (i.e., more complex structures) predicted better performance on an English reading readiness measure. In unpublished studies, Sohail (2015) tested a cross-sectional sample of emergent Canadian English-French bilingual first graders and their third-grade peers who had completed 2 years of French immersion using a word order correction task. In the first grade, but not in the third grade, L1 English word order correction was positively associated with L2 French reading comprehension. Among bilingual Cantonese-English first through third graders studying a dual-language curriculum in Hong Kong, both cross-sectional (Siu and Ho, 2015) and longitudinal (Siu and Ho, 2020) studies found that L1 Chinese word order and morphosyntactic skills positively predicted L2 English text comprehension measured in the third grade. L2 English word order and morphosyntactic skills mediated both cross-sectional and longitudinal relationships when accounting for oral language and cognitive skills, suggesting that syntactic skills represent a common underlying linguistic proficiency contributing to reading comprehension. Similarly, for Spanish-English bilingual upper elementary students in dual immersion programs, Phillips Galloway et al. (2020) found that L2 (English) reading comprehension was positively associated with a composite measure of academic language in the L1 Spanish that included syntactic skills in addition to vocabulary and genre-related knowledge. Although each of these studies investigated different age groups (preschool to upper elementary) and different measures of syntactic skill (word order, morphosyntax, and sentence complexity), they share common findings of cross-linguistic syntactic transfer to L2 reading among children in bilingual immersion education settings. Consistent with Cummins' (1979) hypothesis that readers could draw upon a common underlying linguistic proficiency to support L2 comprehension only when they possessed adequate L1 proficiency, these findings in bilingual education settings suggest that school instruction in both L1 and L2 may support the positive influence of L1 skills on L2 reading, or at least may mitigate variability in L1 proficiency that impedes this cross-linguistic influence.

Particularly in the United States' educational context where English-only schooling has predominated in recent decades, these mixed results from studies investigating CLI may arise from heterogeneity in either or both participant language characteristics and educational environments. For example, United States-centric studies of Spanish-English bilinguals often examine students designated in the public school system as English learners, who are predominantly United States born, but may in fact range from recent immigrants from Spanish-speaking countries with extensive Spanish-language educational experience to second generation heritage speakers with minimal Spanish proficiency (e.g. see Luk and Christodoulu, 2016 for a discussion). The present study, conducted in the United States context, seeks to understand how students for whom Spanish is the first spoken language (L1) may draw upon this L1 to support text processing and comprehension in English, their second spoken language (L2). We considered Spanish as the participant’s L1 if it was the earliest language spoken by the participant on a daily basis at home, even for participants who may have been exposed to English at an early age by listening to media, community interactions, or family conversation in the context of the United States where English is the societally dominant language.

Variability found in CLI effects both within L2 English-dominant school environments and also across L2-dominant compared to immersive bilingual education settings additionally suggest that CLI is more likely to be observed in contexts where both L1 and L2 literacy are systematically taught and that skills with L1 oral vs. written syntax may have different influences on L2 written comprehension. L1 syntactic skills may thus support L2 reading comprehension; however, it is still unclear for whom and under what behavioral measures and environmental conditions this cross-linguistic support may take place.

Unlike traditional behavioral tasks, eye-tracking allows for a direct, naturalistic, and temporally sensitive measure of the cognitive processes underlying reading behaviors as they unfold (Rayner, 2009). A large body of eye-tracking literature on bilingual sentence processing has found that L1 syntactic knowledge impacts online L2 sentence reading most often by slowing text processing, for example in complex syntactic structures, such as causal connectives (van den Bosch et al., 2018), anaphora (see Godfroid, 2019 for a review), and referential clauses (see Dussias et al., 2010; Rossi et al., 2019 for a review). Eye-tracking studies of connected text reading (though not focused on CLI) have also found differences in L1 and L2 reading behavior, including longer fixations and more saccades in the L2, contributing to longer reading times. These differences can vary according to levels of self-reported L1 and L2 exposure (Whitford and Titone, 2012; Whitford and Titone, 2017) and objective L1 and L2 proficiency (Cop et al., 2015; Whitford and Joanisse, 2018).

In addition to reader characteristics, effects of syntactic complexity of the text have been found in bilingual adults’ adaptation to word category combinations (e.g., article-adjective-noun). Snell and Theeuwes (2020) presented a naturalistic narrative text in both Dutch and English and found that higher frequency structures facilitated Dutch-English bilinguals’ eye movement reading behavior in both languages. Differences for bilingual adults reading narrative passages in L1 vs. L2 have been found for syntactic structures such as gerunds, participial phrases, and relative clauses (De Groot, 2018). Among monolingual children, word position during expository text reading has been found to impact offline comprehension (de Leeuw et al., 2016). Furthermore, syntactic processing difficulties have been reported among monolingual children for anaphoric structures in short narrative passages (Joseph et al., 2015).

Eye-tracking studies of connected text reading have primarily focused on adults, leaving reading behavior in children relatively less understood. However, prior studies involving both monolinguals (Joseph et al., 2015; Reichle et al., 2013; Whitford and Joanisse, 2018) and bilinguals (Whitford and Joanisse, 2018) have reported age differences in reading performance, with children exhibiting more fixations and regressions, longer fixations, and shorter saccade amplitudes than adults (Whitford and Joanisse, 2018). Although the maturation of oculomotor control appears to be largely complete by puberty, or around 12 years of age, children’s eye movement reading behavior only approximates that of adults as their language proficiency and word-reading automaticity develops (Blythe and Joseph, 2011; Reichle et al., 2013). Adolescent middle schoolers in K-12 education contexts thus are likely to have adult-like oculomotor capacities as well as word-level decoding skills but are still developing in the language and higher-level complex reading skills needed for efficient text processing.

To our knowledge, studies have yet to investigate the interaction of reader characteristics, syntactic characteristics of text, and reading comprehension using both offline comprehension tasks and eye movement measures of reading in L2 adolescent readers. Kuperman et al. (2018) examined a broad range of reader and text characteristics in native English monolingual university students, and found at the passage level that syntactic complexity of passages predicted several measures of online eye movement behavior, as well as offline reading comprehension. Results for reader characteristics varied depending upon the specific eye movement measure examined, with word reading fluency and nonverbal reasoning emerging as the common predictors of online text processing. Overall in this study, there was little modulation of reader characteristics by syntactic complexity of the text when comparing less complex to more complex passages. Although prior eye-tracking studies have found that syntactic complexity of texts influences eye movement reading behavior in monolingual children (e.g., measured as sentence length in German-speaking children: Tiffin-Richards and Schroeder, 2018) and adults (e.g., English-speaking adults: Kuperman et al., 2018), none have focused on word-to-sentence integration in bilingual adolescents who are experiencing the transitional demand of learning complex academic knowledge through a developing second language.

Prior CLI research, which has primarily focused on bilingual adults (and thus, lack generalizability to other populations) and employed highly controlled sentences as stimuli (and thus, may lack ecological validity), has found that both complex syntactic features of the text and L1 proficiency influence L2 text processing and comprehension. Syntactic features prevalent in school texts, such as elaborated noun phrases, lengthy relative clauses, conceptual anaphora, and the use of distinctive connectives, have been found to pose particular challenges for written text comprehension (Scott and Balthazar, 2010; Uccelli et al., 2015a) in students generally and in L2 learners more specifically (Phillips Galloway and Uccelli, 2019). Cross-linguistically, L2 English academic skills and reading comprehension have been found to be positively associated with L1 Spanish academic vocabulary (Lubliner and Hiebert, 2011) and with academic language skills broadly measured as combined lexical, syntactic, and discourse skills (Aguilar et al., 2020; Phillips Galloway and Uccelli, 2019). However, how L2 learners process distinctive syntactic features of written school texts is not well understood, and little prior research has examined L2 syntactic processing beyond morphosyntax in written academic discourse comprehension. Concurrently, prior education research involving bilingual adolescents has found that complex syntactic text features impede L2 reading comprehension, as a function of L2 proficiency. However, there is still little work connecting these two bodies of literature and examining how syntactic characteristics of L2 texts modulate the cross-linguistic relationship of individual reader characteristics and the comprehension of naturalistic school-based texts. To address this critical gap, the current study asks: How do complex syntactic text features and individual differences in cross-linguistic sentence integration skills, as well as their interactions, affect 1) online processing and 2) offline comprehension of naturalistic school-based texts in bilingual adolescent readers?

We examined individual differences in sentence integration skills in both the L1 (Spanish) and L2 (English), as well as in word decoding and vocabulary knowledge in both languages in order to control for lexical effects. Based on prior research, we expected that better L1 and L2 sentence integration skills would be associated with higher levels of L2 text comprehension (Lesaux et al., 2006) and with more efficient online L2 reading (Cop et al., 2015; Gollan et al., 2008; Whitford and Titone, 2012; Whitford and Titone, 2015; Whitford and Titone, 2017). We included two adolescent participant groups: functionally monolingual native English speakers, and Spanish (L1) - English (L2) speakers, acquiring English in school.

Three categories of text features were included in the study: phrase complexity, clause complexity, and the degree of anaphoric reference. Based on the RSF model (Perfetti and Stafura, 2014), we expected that these features, which present challenges to sentence integration processes, such as those involved in parsing, sequencing, and combinatorial analysis/synthesis, would be a potential locus of cross-linguistic influence in which individual differences in L1 sentence integration skills might contribute to L2 text comprehension. Because syntactic complexity presents challenges to sentence integration, readers may draw upon integrative resources such as syntactic representations or processing biases developed in the L1 to cope with these challenges. As previous research has found that complex syntactic text features are associated with reading comprehension difficulties in L2 child and adolescent readers (Uccelli et al., 2015a; Uccelli et al., 2015b; Phillips Galloway and Uccelli, 2019), we expected that phrase complexity, clause complexity, and anaphoric references would all negatively modulate the expected positive effect of cross-linguistic sentence integration skills on offline text comprehension. Based on similar findings in a self-paced L2 reading study in Spanish-English bilingual adolescents which found that words in more syntactically complex passages were read more slowly than words in simpler ones (Kim et al., 2018; Mulder et al., 2020), we expected a negative impact of these complex text features on online text processing. The study’s hypotheses were that:

1) greater L1 proficiency in sentence integration would be associated with higher levels of L2 text reading efficiency and comprehension, and

Sixty-five typically developing adolescents, aged 11–15 years, participated in the current study. Participants resided in the Boston Metropolitan Area and attended English-instruction schools. In accordance with Institutional Review Board guidelines (Harvard University IRB16-0866), both child assent and parental consent were obtained. Participants were compensated $50 for their time. The final sample included 59 participants; three were excluded due to eye-tracking issues and another three were excluded due to low nonverbal reasoning scores (standard scores <86.6 or > two standard deviations below the sample mean on the Kaufman Brief Intelligence Test-2; KBIT-2 Matrices; Kaufman and Kaufman, 2004), which can influence reading comprehension outcomes (Quinn and Wagner, 2018).

A parental version of the Language and Social Background Questionnaire (LSBQ; adapted from Luk and Bialystok, 2013; Anderson et al., 2018) assessed participants’ demographic background, language history, and familial language use. All participants demonstrated heterogeneous language backgrounds reflective of minority language speakers found in United States classrooms. Twenty-nine participants were native L1 (English) speakers, with no L2 immersion experience and minimal proficiency in an additional language. Most were enrolled in an introductory foreign language class as part of the standard middle school curriculum, and several of these L1 English speakers had been enrolled in some form of beginning language class sporadically since an early age. Thus, they were all functionally monolingual.

We considered Spanish as the participant’s L1 if Spanish was the earliest language spoken on a daily basis at home, even for participants who may have been exposed to English at an early age by listening to media, community interactions, or family conversation. As illustrated in Table 1, thirty participants were identified as L1 Spanish speakers, who spoke Spanish from birth at home and used it 47% of the time, on average. Twenty-two of these participants were from Spanish-speaking countries (Mexico = 8, Central America = 5, South America = 7, Spain = 2) and eight had only lived in the United States The age at which participants were first exposed to English on a regular basis was correspondingly heterogeneous, ranging from birth to 14 years of age (m = 7.8, sd = 3.7); however, all participants spoke Spanish at home and did not start to use English regularly until at least school age, or approximately 5–6 years of age.

As illustrated in Figure 2 showing on the x-axis the difference scores between Spanish and English vocabulary measures as a proxy for language proficiency dominance, the sample displayed a continuous range of variation on multiple and intersecting, but not fully overlapping, dimensions of language experience. For example, one participant who had lived in the United States for 10 years had markedly strong English dominance with a difference between English and Spanish vocabulary scores of over 40 points. This student could thus be considered a heritage speaker with attrition in home language but was nonetheless reported by parents to speak and read Spanish at home approximately 30% of the day and was similar in this regard to other students with English learner designations and with fewer years of residence in the United States. The multiple and at times disparate dimensions of language experience displayed in Figure 2—relative language proficiency, relative language usage, and relative community immersion—are reflective of the ecological variation in minority language speaker backgrounds found in United States classrooms. Also typical of United States classrooms, most of our minority language speaking sample had been initially identified as English learners upon school entry and had exited from this designation at various points in time prior to their study participation. Because initial English learner classification in United States schools is often based upon speaking a home language other than English, this designation encompasses a heterogeneous range of language proficiencies and language dominance as represented in our sample. Figure 2 illustrates this wide distribution of students eligible for English learner services along all the other dimensions of language use, including language dominance, daily Spanish spoken, and years in the United States.

The two language groups were matched on gender (Fisher’s exact p = 0.42), age (Kruskal-Wallis χ² p = 0.06), nonverbal IQ (KBIT Matrices, Kaufman and Kaufman, 2004, Kruskal-Wallis χ² p = 0.07), verbal working memory (Digits Backward, Reynolds and Voress, 2007, Kruskal-Wallis χ² p = 0.05), and rapid naming (Letter, Number, 2-set, and 3-set subtests; Wolf and Denckla, 2005; Kruskal-Wallis χ² p = 0.16). These tasks were administered in the participant’s preferred language. The two language groups were also matched on timed English word reading (Sight Word Efficiency, Torgesen et al., 2011, Kruskal-Wallis χ² p = 0.96) and untimed English word reading (Word Identification, Woodcock-Muñoz Language Survey with Normative Update, WMLS-R-NU, Woodcock et al., 2005; Kruskal-Wallis χ² p = 0.46). Median maternal education was higher in the L1 English group (graduate degree) than the L1 Spanish group (bachelor’s degree, Fisher’s exact p = 0.01). L1 English speakers also performed higher on average than L1 Spanish speakers on measures of English vocabulary knowledge (WMLS-R-NU Picture Vocabulary, Woodcock et al., 2005; Kruskal-Wallis χ² p = 0.46). Measures of Spanish proficiency (Vocabulario sobre dibujos, Identificación de letras y palabras, and Comprensión de textos, Woodcock et al., 2005) were only administered to L1 Spanish speakers due to L1 English speakers’ reported lack of Spanish proficiency and language experience. L1 Spanish speakers’ English and Spanish skills were balanced on average, with no significant difference between English and Spanish vocabulary (Wilcoxon signed-rank p = 0.76) or cloze (p = 0.77) scores. Word identification skills for this group were higher on average in Spanish than English (p < 0.001) although English scores on this subtest remained significantly above the population mean of 100 (p < 0.001). See Table 2 for participants’ cognitive and language proficiency characteristics and Supplementary Table SA, for psychometric information on the standardized assessments.

Each paragraph was evaluated using three classes of syntax measures: 1) classic measures that employ length, or number of words, as an indicator of syntactic complexity; 2) word-level syntax measures; and 3) syntax measures beyond the word level (e.g., examining phrases, clauses, sentences, etc.). Most sentences were composed of a single utterance called a T-unit, itself containing only a single clause. Classic syntactic complexity measures were first generated using the L2 Syntactic Complexity Analyzer (L2SCA; Lu, 2010). L2SCA output was reviewed manually. The greatest numeric variability across paragraphs is captured by sentence length (in number of words), verb phrases, coordinate phrases, and complex nominals. See Supplementary Table SB, for more on L2SCA measures. Next, word-level syntax measures were generated using the Tool for the Automatic Analysis of Cohesion 2.0 (TAACO; Crossley et al., 2019), which employs the Stanford Natural Language Parser (NLP). The word-level parses were inspected for errors manually and corrected where needed. TAACO analysis produces part-of-speech (POS) information as well as type-token measures for key function words at the lemma level. Semantic similarity is represented by Word2Vec (Mikolov et al., 2013), a neural network-derived representation of semantic distance among words and phrases. Supplementary Table SC, provides further information on the TAACO lexico-syntactic complexity measures. Finally, syntactic complexity measures beyond the word level were generated using the Tool for the Automatic Analysis of Syntactic Complexity (TAASC; Kyle and Crossley, 2018), which computes complexity indicators using Stanford NLP parses. Unlike the TAACO measures, TAASC provides syntactic complexity indicators that reflect relationships among words in a sentence and across sentences in a paragraph. TAASC indicators of syntactic sophistication (average lemma log frequency and average verb-argument construction log frequency) measure the overlap with lemmas and constructions found in the academic sub-corpus of the Corpus of Contemporary American English (COCA; Davies, 2009, 2010 as cited in Kyle and Crossley, 2018). See Supplementary Table SD, for more on TAASC phrase-level syntactic complexity measures.

Phrase elaboration, clause complexity, and anaphoric reference were quantified by conducting a nonlinear principal components analysis (PCA) for each characteristic. The nonlinear PCA for phrase complexity incorporated phrase measures from the parsing tools described above: adjective modifiers, nominal dependents, direct and prepositional object dependents, and prepositional phrases as nominal modifiers. The nonlinear PCA for clause complexity included clause measures: relative clause modifiers, dependent clauses, clausal direct objects, and clausal conjunctions. For anaphoric reference, the variables entered into PCA analysis were pronoun density, pronoun-noun ratio, and demonstratives. The first principal component from each of these PCA analyses was used as a corresponding text characteristic predictor in subsequent linear regression models. For phrase complexity, the first principal component accounted for 91% of total variance, for clause complexity 93%, and for anaphoric relations, 67%. See Supplementary Table SE, for details.

After consenting, participants completed the eye-tracking task, where they silently read one practice paragraph and four experimental paragraphs at their own pace. After reading each paragraph, they answered six comprehension questions without being able to refer back to the passage. The order of the experimental paragraphs was counterbalanced across the two language groups in a Latin Square design. Lastly, participants completed the behavioral tasks, which were presented in a fixed order: KBIT-2, RAN/RAS, TOWRE-2, English WMLS-R, and then TOMAL-2 for L1 English speakers and KBIT-2, RAN/RAS, Spanish WMLS-R, TOMAL-2, English WMLS-R, and TOWRE-2 for L1 Spanish speakers. Total participation duration was about 3 hours.

Our first hypotheses concerned cross-linguistic influence of component reading processes on offline comprehension of naturalistic English school texts of varying syntactic complexity. We first identified patterns in children’s paragraph comprehension and the association of these patterns with specific syntactic characteristics of the paragraphs using multidimensional scaling (Borg et al., 2012). Next, behavioral measures that characterized paragraph comprehension outcomes were jointly plotted with these syntactic characteristics. Finally, regression taxonomies using behavioral predictors modeled paragraph comprehension outcomes.

Using syntactic elements identified based on the text analysis, we next asked what kind of relationship between eye movement measures, syntax, and L1 and L2 reading skills is observed in adolescents when reading naturalistic school texts in English. This second set of analyses identified patterns in adolescents’ eye-tracking measures and the association of these patterns with specific syntactic characteristics of the stimulus paragraphs using multidimensional scaling (Borg et al., 2012). Next, behavioral measures that characterized paragraph comprehension outcomes were jointly plotted with these syntactic characteristics. Finally, regression taxonomies using syntactic and behavioral predictors were used to model eye-tracking outcomes.

We hypothesized that greater L1 and L2 proficiency in sentence integration would be associated with higher levels of L2 text comprehension and that phrase complexity, clause complexity, and anaphoric references would all negatively modulate the expected positive effect of cross-linguistic sentence integration skills on offline text comprehension. English sentence integration and vocabulary scores were positive predictors of English text comprehension, and this relationship was similar for both L1 English and L1 Spanish speakers. This result is consistent with prior studies of English learners’ reading development (e.g., Lesaux et al., 2007; Lesaux and Harris, 2017) and with most reading comprehension models, including the RSF (Perfetti and Stafura, 2014), which generally highlight the important role of skills in the language of the text in both reading fluency and comprehension.

We expected that L1 sentence integration abilities would support L2 text comprehension, and this was indeed the case when controlling for the effect of Spanish L1 vocabulary. Prior literature has found weak or nonexistent associations of L1 sentence integration with L2 reading among students in L2 dominant school environments but more consistent positive associations among students in bilingual education settings where students receive academic instruction in both languages. Although the L1 Spanish speakers in our sample, except for two in bilingual English-Spanish schools, attended almost entirely English-speaking schools, they still retained relatively balanced or Spanish-dominant language skills when we tested them in middle school. Our biliterate sample was also reported by parents to consistently engage in reading in Spanish at home, with an average of 34% of daily reading reported to take place in Spanish. Thus, in spite of educational settings similar to those found in prior studies with no CLI effects in text reading, our sample possessed proficiency in L1 Spanish reading that may have led to outcomes more similar to students in bilingual education than ones in English-only instruction. If the transfer of a common underlying proficiency, as in Cummins' (1979) proposal, requires some minimal level of L1 abilities, the home language and literacy experiences in our sample appear to have sustained at least a level of Spanish proficiency that supported the transfer of sentence integration skills to English reading.

The positive association of L1 sentence integration skills with reading was not limited to offline, post-reading comprehension but also seen in reading efficiency, where higher levels of Spanish sentence integration were associated with faster and more efficient online text processing. The parallel findings in both online behavior (seen in eye-tracking) and offline behavior (seen in the post-reading comprehension task) suggests that CLI of L1 Spanish sentence integration is not, or is not solely, a post-reading process of reasoning or strategizing about the comprehension questions asked, or re-creating a representation of the text meaning in relation to the comprehension questions asked of students after reading. Instead, these triangulated results suggest that CLI occurs during the reading process as readers are integrating words into larger sentence and text representations. For monolingual models of text processing and comprehension such as the RSF, these findings indicate that linguistic resources beyond the language of the text can support this integration process even when lexical knowledge in that language, such as reflected in our L1 Spanish speakers’ English vocabulary scores, may not provide the high-quality lexical representations of meaning that are called for in the RSF to support sentence- and text-level meaning integration. While sentence integration in the RSF model is generally assumed to be a within-language skill supporting word-to-text integration, results from both the behavioral and eye-movement analyses thus indicate that a cross-language sentence integration competency beyond vocabulary knowledge may also support text processing and comprehension in an L2.

Because syntactically complex texts present greater difficulty in both L1 and L2 reading, we had hypothesized that syntactic complexity of the text would modulate the association between L1 sentence integration skills and both text processing and comprehension. Our results demonstrate a significant negative main effect of syntactic complexity on paragraph comprehension. In other words, more complex texts, in terms of clause complexity, were more difficult to comprehend both for the full sample and for L1 Spanish speakers when examined separately. Further, clause complexity positively moderated the relationship of Spanish sentence integration skills with offline comprehension such that the positive association of Spanish sentence integration with L2 comprehension was more pronounced in texts with greater clause complexity. In the least complex passages, there was no evident relationship between L1 sentence integration and paragraph comprehension while in the most complex passages, higher L1 sentence integration skills were associated with better paragraph comprehension. L2 comprehension thus appears to draw more heavily on sentence integration skills developed in the L1 when sentences are more structurally complex and difficult to understand.

In online text processing, we again found that syntactic characteristics of the text were associated with reading efficiency. However, unlike for comprehension, better reading efficiency was predicted by the greater presence of anaphoric references and not by clause complexity. In other words, passages with more anaphoric references were read faster and more efficiently than those with fewer such references. In the study passages, these text features may have provided links among concepts in the text that led to more fluent and efficient online text processing. We also found a trend, but non-significant association for the interaction of anaphoric references and L1 sentence integration skills, raising the question of whether in a larger sample or a longer paradigm, these text characteristics would modulate the facilitative main effect of L1 sentence integration on text processing efficiency.

While the present exploratory study cannot identify mechanisms for CLI in complex text, the RSF was formulated as a bottom-up, memory-based integration model, suggesting that beyond lexical representation, individual differences in short-term and working memory capacities could explain comprehension outcomes. Results of the present study do not support a memory-based explanation of individual differences as our measures of sentence integration in both Spanish and English were written and untimed, and in group comparisons, L1 Spanish and L1 English speakers were matched on verbal working memory and nonverbal reasoning. However, the study findings do suggest that in comprehending text with complex clauses that may be likely to tax memory resources, bilinguals may be drawing upon expectation-based meaning construction skills measured by our sentence integration task. These skills may be specific to features shared by Spanish and English or shared in the academic register. For example, while Spanish and English share a canonical subject-verb-object word order in simple sentences, we might speculate that the relative flexibility of Spanish regarding word order could facilitate comprehension of variation in word order in academic language marked by complex clauses. For Spanish speakers, a bias toward disregarding canonical word order in complex clauses, or toward attending to lexical cues in anaphoric references, could conceivably thus facilitate text processing and comprehension in texts containing anaphors and complex clausal structures. The crosslinguistic influence as well as the modulatory effect of text complexity on CLI demonstrated here may thus be specific to a feature such as word order, or combinatorial similarities in a particular language, Spanish, or pair of languages, Spanish and English. Alternatively, crosslinguistic influence might arise from language-general factors such as general skills with statistical learning, predictive processing, parsing, or inferencing. Future studies that employ more than one task, or more specific tasks, may disentangle these or other possibilities.