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Subskills and Sub-Knowledge in Chinese as a Second Language Reading Comprehension: A Structural Equation Modeling Study

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Title: Subskills and Sub-Knowledge in Chinese as a Second Language Reading Comprehension: A Structural Equation Modeling Study
Language: English
Authors: Jia Lin (ORCID 0000-0002-6002-8887), Li Yang (ORCID 0000-0002-4608-2705)
Source: Reading and Writing: An Interdisciplinary Journal. 2025 38(7):2059-2085.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 27
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Descriptors: Second Language Learning, English (Second Language), Reading Comprehension, Reading Skills, Structural Equation Models, Vocabulary Development, Grammar, Teacher Attitudes, Learning Analytics, Attitude Measures, Prior Learning, Rhetoric, Predictor Variables, Second Language Instruction
DOI: 10.1007/s11145-024-10588-7
ISSN: 0922-4777
1573-0905
Abstract: To achieve efficient reading comprehension, Chinese as a second language (L2) learners adopt various component skills and knowledge, including the aspects of vocabulary, grammar, and coherence. However, there is no consensus regarding the relative predictive powers of these three areas in L2 reading comprehension. Instead of employing direct measurement of student reading performance, this study aims to explore this issue by analyzing teacher perception data. Using a Likert-scale questionnaire, 95 experienced teachers rated L2 Chinese learners' reading comprehension, subskills, and sub-knowledge of reading. The results of structural equation modeling reveal that the three areas of subskills and sub-knowledge (i.e., "Vocabulary," "Grammar," and "Coherence") all positively and significantly predicted reading comprehension. "Grammar" exhibits the strongest predictive power, followed by "Coherence," and "Vocabulary." This study enhances our understanding of the relative contributions of subskills and sub-knowledge to L2 Chinese reading. Implications for L2 Chinese instruction are provided.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1482339
Database: ERIC
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  Value: <anid>AN0187667274;2ap01sep.25;2025Sep03.06:43;v2.2.500</anid> <title id="AN0187667274-1">Subskills and sub-knowledge in Chinese as a second language reading comprehension: a structural equation modeling study </title> <p>To achieve efficient reading comprehension, Chinese as a second language (L2) learners adopt various component skills and knowledge, including the aspects of vocabulary, grammar, and coherence. However, there is no consensus regarding the relative predictive powers of these three areas in L2 reading comprehension. Instead of employing direct measurement of student reading performance, this study aims to explore this issue by analyzing teacher perception data. Using a Likert-scale questionnaire, 95 experienced teachers rated L2 Chinese learners' reading comprehension, subskills, and sub-knowledge of reading. The results of structural equation modeling reveal that the three areas of subskills and sub-knowledge (i.e., Vocabulary, Grammar, and Coherence) all positively and significantly predicted reading comprehension. Grammar exhibits the strongest predictive power, followed by Coherence, and Vocabulary. This study enhances our understanding of the relative contributions of subskills and sub-knowledge to L2 Chinese reading. Implications for L2 Chinese instruction are provided.</p> <p>Keywords: Chinese as a second language; Coherence; Grammar; Reading comprehension; Structural equation modeling; Vocabulary; Education Specialist Studies In Education</p> <p>Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</p> <hd id="AN0187667274-2">Introduction</hd> <p>Reading comprehension in a second language (L2) is not only a complex process but also a challenging task for learners (Sparks, [<reflink idref="bib42" id="ref1">42</reflink>]). Van Dijk and Kintsch ([<reflink idref="bib46" id="ref2">46</reflink>]) posit that the process of reading comprehension involves two elements, namely the mental representation of a textbase (i.e., the textbase model) and the cognitive representation of situational factors related to the text (i.e., the situation model). The situation model differs from the text model of comprehension mainly in that the former involves readers' individual interpretation (van Dijk & Kintsch, [<reflink idref="bib46" id="ref3">46</reflink>]). In L2 reading, due to readers' relatively limited proficiency, the occurrence of reader-text interaction is less frequent than in L1 reading. Lower-level decoding dominates L2 reading and plays a crucial role in successful L2 reading (Koda, [<reflink idref="bib25" id="ref4">25</reflink>]). Therefore, research on the textbase model in L2 reading holds great significance. The present study opts to focus on subskills and sub-knowledge associated with the textbase model.</p> <p>According to the textbase model, readers comprehend the meaning of words, draw on their understanding of syntactic units at different complexity levels, and establish both local and global coherence (Choi & Zhang, [<reflink idref="bib10" id="ref5">10</reflink>]). Similarly, Perfetti et al. ([<reflink idref="bib36" id="ref6">36</reflink>]) discuss that text comprehension occurs at three levels, namely word level (lexical processing), sentence level (syntactic processing), and higher text level (textual inferencing). Successful reading comprehension involves both knowledge and skills to utilize the knowledge for meaning construction (Koda, [<reflink idref="bib25" id="ref7">25</reflink>]). Accordingly, to achieve efficient text comprehension, three levels of component skills and knowledge need to be developed and cultivated: vocabulary knowledge and word processing, grammar knowledge and syntactic parsing, and knowledge of cohesive devices and coherence building. For ease of reference, these three factors are also called <emph>Vocabulary, Grammar,</emph> and <emph>Coherence</emph> in this study.</p> <p>Among the three areas of knowledge, vocabulary knowledge and grammar knowledge have been observed to strongly correlate with L2 reading proficiency (Jeon & Yamashita, [<reflink idref="bib20" id="ref8">20</reflink>]). However, the empirical evidence with regard to the relative predictive powers of the two types of knowledge in L2 reading comprehension is still limited and inconsistent (Choi & Zhang, [<reflink idref="bib10" id="ref9">10</reflink>]). This likely prevents teachers from adopting efficient pedagogical practices to facilitate learners' reading development in the L2 classroom. Moreover, a strong emphasis on English other than other languages, especially Mandarin Chinese (hereafter Chinese), is also apparent. Chinese differs from English at both morphological and syntactic levels (Sun, [<reflink idref="bib43" id="ref10">43</reflink>]), and its unique linguistic and psycholinguistic features (e.g., word decision, refer to Sect. "Vocabulary, grammar, and coherence in L2 Chinese reading" for more examples) require the cognitive mechanisms that do not exist in reading English and other alphabetic languages. Because of these differences, empirical studies on the relative roles of vocabulary and grammar knowledge in L2 Chinese reading comprehension are warranted. Additionally, the building of coherence is of significance to reading comprehension as readers need to link the meaning of words and sentences to the prior context for constructing accurate understanding (Ferstl & von Cramon, [<reflink idref="bib12" id="ref11">12</reflink>]). However, the contribution of knowledge of cohesive devices to L2 reading comprehension has not been sufficiently investigated. Moreover, successful reading comprehension requires both knowledge and skills to apply the knowledge in constructing meaning (Koda, [<reflink idref="bib25" id="ref12">25</reflink>]). Most previous studies only investigated sub-knowledge of reading (e.g., Hu et al., [<reflink idref="bib17" id="ref13">17</reflink>]; Shiotsu & Weir, [<reflink idref="bib41" id="ref14">41</reflink>]). They seldom examined subskills associated with vocabulary, grammar, and coherence, that is, word processing, syntactic parsing, and coherence building.</p> <p>To further the understanding and also fill the gap in L2 Chinese reading, the current study investigated the relative contributions of the knowledge and processing skills associated with vocabulary, grammar, and coherence to L2 Chinese reading comprehension among a group of college students in a Chinese as a foreign language context. Unlike prior research that mainly utilized the data based on student test measurements, this study adopted teacher-perceived assessments to evaluate the three areas. Previous studies (e.g., Graus & Coppen, [<reflink idref="bib15" id="ref15">15</reflink>]; Scheffler, [<reflink idref="bib39" id="ref16">39</reflink>]) revealed the credibility and reliability of teacher perceptions in gauging L2 proficiency. This study utilizes teacher perception data in hopes of examining this research topic from a different perspective. Particularly, previous research findings regarding vocabulary and grammar lack consensus, so this study aims to provide new evidence from a new data source. Findings of this study are expected to not only provide more scholarly evidence regarding the roles of different sub-knowledge and subskills of reading but also offer practical, instructional suggestions on the effective facilitation of L2 Chinese reading development.</p> <hd id="AN0187667274-3">Literature review</hd> <p>This section synthesizes theoretical and empirical research on L2 reading along with studies in Chinese linguistics to explore the L2 Chinese reading subskills and sub-knowledge pertaining to vocabulary, grammar, and coherence, highlighting L1-L2 linguistic differences. Considering that English is typically the L1 for L2 Chinese learners in the United States, the discussion emphasizes the linguistic disparities between English and Chinese, showcasing unique linguistic features and processing skills specific to Chinese.</p> <hd id="AN0187667274-4">Vocabulary, grammar, and coherence in L2 Chinese reading</hd> <p></p> <hd id="AN0187667274-5">Vocabulary knowledge and word processing</hd> <p>Vocabulary knowledge and efficient access to word meaning are crucial for reading comprehension (Adlof & Perfetti, [<reflink idref="bib1" id="ref17">1</reflink>]; Andrews, [<reflink idref="bib2" id="ref18">2</reflink>]). Chinese words are generally composed of one, two, or more characters, without inherent markers of lexical category or inflections. Approximately 80% compound words are bi-morphemic in Modern Chinese (Lin, [<reflink idref="bib26" id="ref19">26</reflink>]). Based on the ways of word formation, Chinese bi-morphemic words can be grouped into five types: attributive compounds, coordinative words, verb-complements, subject-predicates, and verb-objects (Huang & Liao, [<reflink idref="bib18" id="ref20">18</reflink>]). Morphological awareness directly enhances vocabulary development and reading comprehension competence (Grabe & Yamashita, [<reflink idref="bib14" id="ref21">14</reflink>]). When a Chinese word consists of multiple characters, recognizing characters during word decoding is similar to the process of identifying individual morphemes in a multi-morphemic English word (Shen, [<reflink idref="bib40" id="ref22">40</reflink>]).</p> <p>The processing of Chinese words involves at least three component skills: character recognition, word decision, and lexical access (Shen, [<reflink idref="bib40" id="ref23">40</reflink>]). Character recognition involves identifying the visual structure of a character, activating its pronunciation either audibly or mentally, and accessing its meaning (Shen, [<reflink idref="bib40" id="ref24">40</reflink>]). Word decision, on the other hand, refers to the ongoing process of grouping adjacent characters into words while reading. The significant disparity in word processing between Chinese and English lies in the necessity of making a word decision for lexical access in Chinese, unlike in English where visible space boundaries aid in word segmentation. While proficient native speakers can effortlessly segment words, L2 Chinese learners often find word decision to be a complex process (Shen, [<reflink idref="bib40" id="ref25">40</reflink>]). Regarding lexical access, it involves the encoding of a word's meaning, syntactic properties, and pronunciation from long-term memory, which fit the context (Wu & Liu, [<reflink idref="bib48" id="ref26">48</reflink>]). The process encompasses all the variant orthographic forms, related meanings, metaphoric and pragmatic uses, as well as associated words (Grabe & Yamashita, [<reflink idref="bib14" id="ref27">14</reflink>]). Chinese words, particularly single-character ones, often carry multiple meanings and may have multiple pronunciations. Consequently, readers must rely on contextual cues to determine the intended meanings and pronunciations of these words. Therefore, contextualized word processing is critical for successful L2 Chinese reading comprehension (Shen, [<reflink idref="bib40" id="ref28">40</reflink>]).</p> <hd id="AN0187667274-6">Syntactic knowledge and syntactic parsing</hd> <p>Syntactic parsing is the process of extracting information from a phrase, clause, or sentence structure formed by a sequence of activated words (Grabe & Yamashita, [<reflink idref="bib14" id="ref29">14</reflink>]). Syntactic knowledge provides various functional insights that enhance the precision of the message being delivered and is traditionally linked with syntactic parsing as a distinct language mechanism (Grabe & Yamashita, [<reflink idref="bib14" id="ref30">14</reflink>]). Chinese exhibits several differences from English in terms of syntactic features, particularly in sentence structures. This section commences with a brief exploration of the positions and functions of verbs, objects, subjects, and adverbials in Chinese sentences, followed by the highlighting of unique syntactic patterns in Chinese.</p> <p>While the dominant sentence structures in Chinese align with English (SVO), the relationship between subject and predicate in Chinese demonstrates significant semantic looseness (Norman, [<reflink idref="bib35" id="ref31">35</reflink>]). In Chinese, the subject of a sentence can assume diverse logical relationships relative to the predicate, serving as the agent of a transitive verb, an object about which some quality is predicated, the patient or recipient of the action, or an instrument (Norman, [<reflink idref="bib35" id="ref32">35</reflink>]). Chao ([<reflink idref="bib8" id="ref33">8</reflink>]) characterizes the grammatical functions of subject and predicate in Chinese as "topic" and "comment," respectively, indicating that the predicate conveys information about the subject. Chinese sentences can generally be classified into two categories: major sentences with both subject and predicate, and minor sentences which omit the subject. The frequent exclusion of pronominal subjects suggests that the minor sentences are a more prevalent feature in Chinese than in English (Norman, [<reflink idref="bib35" id="ref34">35</reflink>]).</p> <p>In English, adverbials of manner, time, and place typically follow the main verb, whereas in Chinese, they are positioned before the main verb or subject. Moreover, Chinese, being an analytic language, lacks final inflections to denote grammatical features like aspect, passiveness, and plurality, etc., which are represented by particles and by word order instead. There are also notable distinctions between Chinese and English nominal sentences. For instance, Chinese nominal sentences may lack a verb entirely but are exemplified by constructions such as 今天星期六 (jīn tiān xīng qī liù; TODAY SATURDAY- Today is Saturday). Additionally, certain Chinese syntactic patterns, such as the <emph>shì...de</emph> structure and the <emph>Ba</emph>-constructions (S–<emph>bǎ</emph>–<emph>O</emph>–<emph>V</emph>– <emph>other elements</emph>), also potentially pose challenges for L2 Chinese learners due to the absence of direct English equivalents.</p> <hd id="AN0187667274-7">Knowledge of cohesive devices and coherence building</hd> <p>Understanding how coherence relations are indicated among text elements is crucial for constructing cohesive text representations. Coherence building relies heavily on linguistic knowledge and the effective use of cohesive devices. The ability to integrate relational information signaled by cohesive devices is closely related to comprehension and retention (Koda, [<reflink idref="bib25" id="ref35">25</reflink>]). While the fundamental requirements for coherence building are similar in L1 and L2 discourse processing, the factors facilitating coherence building differ. In L2 reading, cohesive devices serve as compensatory tools for limited lexical knowledge. They include conjunctions, linking adverbs, and connecting ultra-word units, which connect various linguistic units (e.g., clauses, sentences, and utterances) to form cohesive text. However, very few Chinese cohesive devices have direct equivalences in English, which are both semantically and syntactically interchangeable. Furthermore, a sentence-oriented language like English has distinct sentence boundaries and all the important elements (subjects, predicates, and objects). Syntactic analysis is typically conducted within the sentence level. Conversely, understanding a discourse-oriented language like Chinese necessitates the consideration of all the discourse information (Tsao, [<reflink idref="bib45" id="ref36">45</reflink>]). Consequently, the mastery of cohesive devices, especially inter-sentence connectors, holds considerable importance to L2 Chinese reading (Lin & Gao, [<reflink idref="bib28" id="ref37">28</reflink>]).</p> <p>Based on the conveyed semantic relationships, cohesive devices can be categorized into 12 types, with those indicating causal, adversative, and hypothetical, and progressive relationship being the most frequently used. Based on the grammatical units that they can connect with, Chinese cohesive devices fall into three categories. Firstly, intra-sentence connectives like <emph>hé</emph> (和 and), <emph>yǔ</emph> (与 and), solely link words or phrases. The second category of connectives can link clauses or sentences but not connect words or phrases. Finally, the last category can connect words, phrases, clauses, and sentences, exemplified by <emph>huòzhě</emph> (或者 or), <emph>yīnwèi</emph> (因为 because). Unlike English connectives, Chinese connectives can be paired. According to Zhang and Qiu's ([<reflink idref="bib52" id="ref38">52</reflink>]) corpus-based study, L1 Chinese speakers tend to use pairs of connectives such as <emph>bùjǐn ... érqiě</emph> (不仅......而且 not only ... but also), <emph>jì</emph> ... <emph>yòu</emph> (既......又not only ... but also), etc. However, the co-occurrence of some connectives is optional; for instance, connectives <emph>jìrán</emph> (既然 since), <emph>wúlùn</emph> (无论 no matter), <emph>yīnwèi</emph> (因为 because) can stand alone or be accompanied by another connective in the second clause (Lu, [<reflink idref="bib32" id="ref39">32</reflink>]). Similarly, some connectors, which typically appear in the second clause, can also appear alone or co-occur with another connective in the first clause. Additionally, the positions of Chinese connectives are more flexible compared to their English counterparts (Lu, [<reflink idref="bib32" id="ref40">32</reflink>]). Typically, regardless of whether the subjects of clauses are identical, connective conjunctions should precede the subjects (i.e., in the sentence- or clause-initial positions). However, if subjects of two clauses are the same, the subject in the second clause may be omitted, with connective conjunctions usually positioned after the subject of the first clause. In summary, Chinese connectives are complex and flexible, thus presenting challenges for L2 learners (Lu, [<reflink idref="bib32" id="ref41">32</reflink>]).</p> <hd id="AN0187667274-8">The predictive powers of subskills and sub-knowledge in L2 reading comprehension</hd> <p>Among the different subskills and sub-knowledge of reading, the importance of vocabulary and grammar have been recognized in L2 reading literature. According to the recent meta-analysis reports (Jeon & Yamashita, [<reflink idref="bib20" id="ref42">20</reflink>]; Zhang & Zhang, [<reflink idref="bib51" id="ref43">51</reflink>]), knowledge of L2 vocabulary and grammar both have strong correlations with L2 reading comprehension. The fruitful and consistent results notwithstanding, the empirical evidence that investigated the relative contributions of vocabulary and grammar to L2 reading comprehension is still limited, and the findings yielded are different and inconclusive (see Choi & Zhang, [<reflink idref="bib10" id="ref44">10</reflink>] for a review).</p> <p>A line of the studies reported vocabulary knowledge as a stronger predicator of L2 reading comprehension over the knowledge of grammar. Among them, van Gelderen et al. ([<reflink idref="bib47" id="ref45">47</reflink>]) investigated the relative significance of vocabulary and grammar knowledge, processing speed in word recognition and sentence verification, and metacognitive knowledge to L1 and L2 reading comprehension among 281 Dutch EFL learners. Based on the structural equation modeling (SEM) analysis, vocabulary knowledge was observed to play a significant role in L2 reading comprehension, but grammar knowledge did not. A similar finding was reported by Zhang ([<reflink idref="bib49" id="ref46">49</reflink>]), who recruited 190 Chinese EFL graduate students to examine how vocabulary and grammar contributed to L2 reading comprehension. Vocabulary knowledge was evaluated according to its size and depth while grammar knowledge was measured at both implicit and explicit dimensions. The implicit grammar knowledge was assessed through timed grammaticality judgment tasks, and the explicit grammatical knowledge was tested using grammatical error correction tasks. Regarding the reading comprehension, it contained three indicators, namely co-reference, inference, and gist. The SEM results showed that vocabulary knowledge was a better predictor of L2 reading comprehension than grammar knowledge. Using the Artificial Neural Network, Aryadoust and Baghaei (2016) investigated the same issue among 825 L2 English participants. Their knowledge of vocabulary and grammar, as well as the reading comprehension ability, were estimated by the Rasch model. Although both vocabulary and grammar knowledge were observed to be important factors in distinguishing more versus less competent readers, the findings confirmed the stronger role that vocabulary played in L2 reading comprehension. More recently, 1,149 sixth grade EFL participants in Hu et al. ([<reflink idref="bib17" id="ref47">17</reflink>]) completed the tests for vocabulary knowledge (focused on vocabulary size), grammar knowledge (including forms and meanings), and reading comprehension (featuring extraction, integration, and inferencing). The SEM regression models indicated that both vocabulary and grammar knowledge contributed to English reading comprehension. However, vocabulary affected the learners' reading comprehension more significantly than grammar did.</p> <p>Contrastively, another group of studies observed grammar knowledge as a more contributing factor to L2 reading proficiency. Shiotsu and Weir's ([<reflink idref="bib41" id="ref48">41</reflink>]) SEM article reported the findings of three studies regarding the relative role that vocabulary and grammar knowledge played in L2 reading comprehension. Study 1 had 107 students from a British EAP program to participate, while the other two studies both recruited Japanese EFL university students. In Studies 2 and 3, vocabulary knowledge was indexed by its size, and reading comprehension was measured by multiple-choice questions that required the synthesis of information across sentences. Overall, all three studies concluded that grammar knowledge was a stronger predicator over vocabulary knowledge in L2 reading comprehension. Along the same line, Nergis ([<reflink idref="bib34" id="ref49">34</reflink>]) examined the relative importance of vocabulary knowledge, syntactic awareness, and metacognitive strategies to L2 academic reading comprehension in the case of 45 undergraduate students in an English-medium university in Turkey. Vocabulary knowledge was examined according to its depth, and syntactic awareness was measured using the sentence combinations part of a test that was frequently utilized to test the relations between syntactic knowledge and academic reading. The findings of multiple regression analysis suggested that syntactic awareness, rather than vocabulary knowledge, played a more significant role in L2 reading comprehension. Recruiting 96 high school EFL male students in South Korea, Kim and Cho ([<reflink idref="bib23" id="ref50">23</reflink>]) explored the relative superiority of vocabulary and grammar to L2 reading comprehension. Corresponding tests that evaluated the participants' respective vocabulary knowledge (on vocabulary size), grammar knowledge, and reading comprehension (including gist, co-reference, inference, conjunction, and literal meaning) were completed. The results suggested that grammar knowledge had a stronger predictive power over vocabulary to L2 reading comprehension.</p> <p>Unlike the two groups of research reviewed above, some studies reported that the relative importance of vocabulary and grammar to L2 reading comprehension seems to vary according to the learners' proficiency level. Taking the SEM approach, Raeisi‐Vanani and Baleghizadeh ([<reflink idref="bib37" id="ref51">37</reflink>]) recruited 368 Iranian EFL students and assigned them to two proficiency levels: higher-proficiency (advanced) versus lower-proficiency (including beginner and intermediate). As in Zhang ([<reflink idref="bib49" id="ref52">49</reflink>]), grammar knowledge was measured both explicitly and implicitly, and vocabulary knowledge was examined at both levels of depth and breadth. For reading comprehension, it was evaluated using five indicators, namely vocabulary, detail and negative factual information, main idea and purpose, co‐reference, and inference. The results revealed an impact of learner proficiency on the contribution of vocabulary and grammar to L2 reading comprehension. To be more specific, vocabulary knowledge was a better predictor of reading proficiency for the higher-proficiency students, while grammar knowledge was observed to be slightly more contributive to reading comprehension for the lower-proficiency learners.</p> <p>Of direct relevance to the L2 targeted by the current study (namely L2 Chinese), only a few studies have been conducted on Chinese heritage language (CHL) learners. For instance, Zhang and Koda ([<reflink idref="bib50" id="ref53">50</reflink>]) examined the predictive power of vocabulary knowledge and morphological awareness in the reading comprehension of 195 CHL students from study abroad programs in China. They were all intermediate level learners and had early exposure to spoken Chinese at home before receiving the formal Chinese instruction. The CHL students' vocabulary knowledge was evaluated using two tests: one contained vocabulary items related to early exposure to spoken Chinese while the other comprised the words learned in formal Chinese classrooms. The CHL learners' reading comprehension was indexed by lexical inference and passage comprehension. According to the SEM analysis results, although vocabulary knowledge and morphological awareness both significantly contributed to reading comprehension, morphological awareness was observed to mediate the contributions that vocabulary knowledge made to CHL reading comprehension. Findings of Zhang and Koda ([<reflink idref="bib50" id="ref54">50</reflink>]) expanded the line of research by focusing on L2 Chinese, a language that has received far less attention in the literature. However, the observations were restricted to vocabulary knowledge and morphological awareness but not concerning the knowledge and skills beyond the word level.</p> <hd id="AN0187667274-9">Current study</hd> <p>As previously discussed, the existing studies that explored the relative predictive power of vocabulary and grammar knowledge in reading comprehension reported different and inconsistent observations (Choi & Zhang, [<reflink idref="bib10" id="ref55">10</reflink>]). This calls for more research efforts to be made so as to obtain more robust conclusions. Also worth noting is that the L2s that have been studied in prior research focused on English, while L2 Chinese has been given insufficient attention. As revealed in Sect. "Vocabulary, grammar, and coherence in L2 Chinese reading", Chinese language exhibits uniqueness in terms of vocabulary, grammar, and coherence, distinguishing it from English. Although there are some studies (e.g., Zhang & Koda, [<reflink idref="bib50" id="ref56">50</reflink>]) conducted on CHL learners, what was investigated is limited to the word level knowledge (e.g., vocabulary knowledge, morphological awareness). It remains not yet addressed regarding the relative contributions of vocabulary, grammar, and coherence in the case of learners of Chinese as a foreign language (CFL), especially considering the fact that the three types of sub-knowledge and subskills are of significance to L2 Chinese reading comprehension. Moreover, as the brief overview illustrates, prior research has put much emphasis on the knowledge of vocabulary and grammar. However, the relationship of coherence knowledge and coherence building to L2 reading comprehension was much less researched, which resulted in little evidence and understanding regarding the exact contributions they likely make to L2 reading comprehension, especially the reading comprehension of a discourse-oriented language such as Chinese. Furthermore, greater research efforts have been dedicated to exploring the predictive powers of sub-knowledge rather than subskills of reading. Last but not least, previous studies gauged reading comprehension, subskills, and sub-knowledge using tests on student reading performance. The present study adopted teacher-perceived assessment of these variables, which could shed light on their precative roles in L2 reading comprehension from an additional perspective. The research question that guides this study is:What are the predictive powers of the three aspects of component skills and knowledge (i.e., <emph>Vocabulary</emph>, <emph>Grammar</emph>, and <emph>Coherence</emph>) on L2 Chinese reading comprehension?</p> <hd id="AN0187667274-10">Methods</hd> <p></p> <hd id="AN0187667274-11">Participants</hd> <p>Experienced college Chinese language teachers (<emph>N</emph> = 95) evaluated students' L2 Chinese reading comprehension, subskills and sub-knowledge using an online questionnaire (see the Appendix), distributed by Qualtrics.com. Teacher participants were selected through convenience sampling from 43 universities or colleges across the United States. The inclusion criteria comprised: (a) having at least three years of independent Chinese teaching experience and (b) holding an M.A. or Ph.D. degree in relevant fields, such as teaching Chinese as a second/foreign language, foreign language/world language education, applied linguistics, or second language acquisition.</p> <p>Table 1 presents the age, gender, educational background, and teaching experience of the teachers who participate in this study. Although the teacher participants exhibited diversity in their backgrounds as shown in Table 1, the Chinese language courses they taught shared similarities in instructional materials and curriculum design. Typically, the first- and second-year courses generally convened four to five times on a weekly basis, each lasting for 50 min, while the third- and fourth-year courses met two to three times every week, which totaled 150 min. Additionally, the vast majority of the teacher participants utilized <emph>Integrated Chinese</emph> (Third or Fourth Edition; Liu et al., [<reflink idref="bib30" id="ref57">30</reflink>], [<reflink idref="bib31" id="ref58">31</reflink>]) as their primary textbooks for lower-level courses (i.e., 1st and 2nd year).</p> <p>Table 1 Demographic backgrounds of participants (N = 95)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="2"><p>Age</p></th><th align="left" colspan="2"><p>Year of teaching experience</p></th><th align="left" colspan="2"><p>Gender</p></th><th align="left" colspan="2"><p>Highest degree</p></th></tr><tr><th align="left"><p>Mean (SD)</p></th><th align="left"><p>Range</p></th><th align="left"><p>Mean (SD)</p></th><th align="left"><p>Range</p></th><th align="left"><p>Female</p></th><th align="left"><p>Male</p></th><th align="left"><p>M.A</p></th><th align="left"><p>Doctoral Degree</p></th></tr></thead><tbody><tr><td align="left"><p>40.4 (8.5)</p></td><td align="left"><p>30–69</p></td><td align="left"><p>13.2 (6.3)</p></td><td align="left"><p>3–35</p></td><td char="." align="char"><p>n = 83</p></td><td char="." align="char"><p>n = 12</p></td><td char="." align="char"><p>n = 38</p></td><td char="." align="char"><p>n = 57</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0187667274-12">Data collection</hd> <p>Using the questionnaire, teacher participants assessed the reading comprehension, reading subskills and sub-knowledge of a hypothetical average learner in their classes, defined as an average achieving, non-heritage, and English-speaking student. Institutions that grant a bachelor's degree in Chinese in the United States typically offer four years of Chinese language courses (namely 1st, 2nd, 3rd, and 4th-year). If a teacher participant was teaching multiple instructional levels, she/he was requested to assess all the levels that she/he was teaching. The evaluations for different instructional levels by the same teacher were treated as separate responses in this study. On average, each teacher participant evaluated two instructional levels, yielding a total of 179 responses after removing incomplete ones. Specifically, 41 teachers evaluated only one instructional level, while 32, 12, and nine teachers evaluated two, three, or four levels respectively. Previous studies (e.g., Raeisi‐Vanani & Baleghizadeh, [<reflink idref="bib37" id="ref59">37</reflink>]) suggest that L2 learners' language proficiency may impact the relative importance of vocabulary and grammatical knowledge in the prediction of reading comprehension. Therefore, in order to counteract the potential influence of reading proficiency, approximately equal numbers of responses (<emph>n</emph> = 45, 48, 43, 43) were collected from the four instructional levels to ensure adequate representation of each level.</p> <p>The objectivity and accuracy of teacher-perceived assessments could be affected by factors such as teachers' experiences with students, and their individual interpretation of the questionnaire items and of student abilities. Experienced teachers are more likely to have an accurate perception of student abilities. To increase the objectivity and accuracy of the measurement, as discussed previously, we only recruited teachers with rich teaching experience and sufficient training. In addition, the data collection happened at the end of the academic year, when teachers had gained a thorough insight into their students. This further increased the accuracy of teachers' evaluation. Moreover, as presented in Lin ([<reflink idref="bib29" id="ref60">29</reflink>]), which reported the development and validation procedures and psychometric properties of the questionnaire used in the present study, all items in this questionnaire had gone through expert review to improve their clarity, brevity, accuracy, independence, and applicability. For items that teacher participants may have difficulty understanding, examples and further elaborations were provided (e.g., Item 13 and 39) to facilitate appropriate interpretation. Lastly, we recruited a relatively large number of teacher participants (<emph>N</emph> = 95) to balance the potential biases from individual teachers.</p> <hd id="AN0187667274-13">Key measures</hd> <p>By using the questionnaire, teacher participants rated on the scale of five points (ranging from <emph>0 "Can not be expected to perform like this"</emph> to <emph>4 "This describes a performance that is clearly below the learner's skill level. Could perform better than this"</emph>) on statements of L2 Chinese readers' reading comprehension, and subskills and sub-knowledge of reading. The questionnaire consists of 46 items selected from a longer instrument <emph>Chinese as a Second Language Reading Proficiency Scale</emph> (Lin, [<reflink idref="bib29" id="ref61">29</reflink>]), keeping the original item numbers. The 46 items were grouped into four categories, measuring sub-skills/sub-knowledge associated with vocabulary, grammar, and coherence, and measuring reading comprehension. With reference to the <emph>Common European Framework of Reference for Languages (CEFR)</emph> (Council of Europe, [<reflink idref="bib11" id="ref62">11</reflink>]), these items were written in the format of "can-do" statements, measuring the degree to which L2 Chinese learners "can do" what these descriptors denoted. As indicated in the direction of the questionnaire, teacher participants made the evaluation on the basis of their observations of student performance in class activities, tests, and assignments. Lin ([<reflink idref="bib29" id="ref63">29</reflink>]) reported the development and validation procedures, as well as psychometric properties of this questionnaire. This instrument is also theoretically solid because its items were created based on the results of reviewing theoretical works (e.g., Grabe, [<reflink idref="bib13" id="ref64">13</reflink>]; Grabe & Yamashita, [<reflink idref="bib14" id="ref65">14</reflink>]; Koda, [<reflink idref="bib25" id="ref66">25</reflink>]), the Communicative Language Ability Model (Bachman & Palmer, [<reflink idref="bib3" id="ref67">3</reflink>], [<reflink idref="bib4" id="ref68">4</reflink>]), and studies on Chinese linguistics (Hung, [<reflink idref="bib19" id="ref69">19</reflink>]; Norman, [<reflink idref="bib35" id="ref70">35</reflink>]; Shen, [<reflink idref="bib40" id="ref71">40</reflink>]; Sun, [<reflink idref="bib43" id="ref72">43</reflink>]).</p> <p> <emph>Vocabulary.</emph> The first category consists of six items measuring subskills and sub-knowledge related to vocabulary (i.e., vocabulary knowledge and word processing). The overall mean was <emph>M</emph> = 2.07 and the internal consistency of the six items was α = 0.90.</p> <p> <emph>Grammar.</emph> Subskills and sub-knowledge associated with grammar (i.e., grammar knowledge and syntactic parsing) were measured by 20 items. The overall mean was <emph>M</emph> = 2.28, and the internal consistency of these items was α = 0.98.</p> <p> <emph>Coherence.</emph> Three items measured the subskills and sub-knowledge pertaining to coherence (i.e., knowledge of cohesive devices and coherence building). The overall mean was <emph>M</emph> = 2.25 and the internal consistency of items associated with this construct was α = 0.90.</p> <p> <emph>Reading comprehension.</emph> L2 Chinese learners' reading comprehension was gauged by 17 items. Exploratory Factor Analysis (EFA), using principal components analysis method and Varimax rotation method, was conducted to explore the underlying dimensions of these 17 items. As shown in Table 2, the KMO measure is 0.96, higher than the threshold value of 0.6, indicating a very high degree of sampling adequacy (Kaiser, [<reflink idref="bib21" id="ref73">21</reflink>], [<reflink idref="bib22" id="ref74">22</reflink>]). The significance level of Bartlett's Test of Sphericity (0.000) is lower than 0.05, indicating that the correlation matrix in this study is not an identity matrix (Bartlett, [<reflink idref="bib5" id="ref75">5</reflink>]). The KMO value and Bartlett's Test of Sphericity result suggest the suitability of the data for factor analysis. As seen in Table 3, two factors, whose Eigenvalues are larger than 1, were extracted from the 17 items. In total, they account for 79.218% of the variance. Accordingly, the 17 items were classified into two groups (see Table 4 for detail). Group 1, having seven items (<emph>M</emph> = 2.27, α = 0.94), measured basic reading comprehension, such as understanding straightforward information, explicit details, and the main idea of the text specially prepared for L2 readers or simple authentic materials. Group 2 (<emph>M</emph> = 1.07, α = 0.97), including 10 items, assessed advanced reading comprehension, such as comprehending long authentic material over a wide range of topics, and appreciating nuances or stylistics.</p> <p>Table 2 KMO and Bartlett's Test</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="2"><p>Kaiser–Meyer–Olkin measure of sampling adequacy</p></th><th align="left"><p>0.960</p></th></tr><tr><th align="left"><p>Bartlett's test of Sphericity</p></th><th align="left"><p>Approx. Chi-Square</p></th><th align="left"><p>3726.592</p></th></tr></thead><tbody><tr><td align="left" /><td align="left"><p>df</p></td><td align="left"><p>136</p></td></tr><tr><td align="left" /><td align="left"><p>Sig</p></td><td align="left"><p>0.000</p></td></tr></tbody></table> </ephtml> </p> <p>Table 3 Total variance explained</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Component</p></th><th align="left" colspan="3"><p>Initial eigenvalues</p></th><th align="left" colspan="3"><p>Extraction sums of squared loadings</p></th><th align="left" colspan="3"><p>Rotation sums of squared loadings</p></th></tr><tr><th align="left"><p>Total</p></th><th align="left"><p>% of Variance</p></th><th align="left"><p>Cumulative %</p></th><th align="left"><p>Total</p></th><th align="left"><p>% of Variance</p></th><th align="left"><p>Cumulative %</p></th><th align="left"><p>Total</p></th><th align="left"><p>% of Variance</p></th><th align="left"><p>Cumulative %</p></th></tr></thead><tbody><tr><td align="left"><p>1</p></td><td char="." align="char"><p>12.134</p></td><td char="." align="char"><p>71.377</p></td><td char="." align="char"><p>71.377</p></td><td char="." align="char"><p>12.134</p></td><td char="." align="char"><p>71.377</p></td><td char="." align="char"><p>71.377</p></td><td char="." align="char"><p>7.820</p></td><td char="." align="char"><p>46.001</p></td><td char="." align="char"><p>46.001</p></td></tr><tr><td align="left"><p>2</p></td><td char="." align="char"><p>1.333</p></td><td char="." align="char"><p>7.841</p></td><td char="." align="char"><p>79.218</p></td><td char="." align="char"><p>1.333</p></td><td char="." align="char"><p>7.841</p></td><td char="." align="char"><p>79.218</p></td><td char="." align="char"><p>5.647</p></td><td char="." align="char"><p>33.217</p></td><td char="." align="char"><p>79.218</p></td></tr><tr><td align="left"><p>3</p></td><td char="." align="char"><p>0.587</p></td><td char="." align="char"><p>3.453</p></td><td char="." align="char"><p>82.671</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>4</p></td><td char="." align="char"><p>0.503</p></td><td char="." align="char"><p>2.956</p></td><td char="." align="char"><p>85.627</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>5</p></td><td char="." align="char"><p>0.381</p></td><td char="." align="char"><p>2.243</p></td><td char="." align="char"><p>87.870</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>6</p></td><td char="." align="char"><p>0.340</p></td><td char="." align="char"><p>2.002</p></td><td char="." align="char"><p>89.871</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>7</p></td><td char="." align="char"><p>0.275</p></td><td char="." align="char"><p>1.617</p></td><td char="." align="char"><p>91.488</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>8</p></td><td char="." align="char"><p>0.243</p></td><td char="." align="char"><p>1.430</p></td><td char="." align="char"><p>92.918</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>9</p></td><td char="." align="char"><p>0.219</p></td><td char="." align="char"><p>1.288</p></td><td char="." align="char"><p>94.207</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>10</p></td><td char="." align="char"><p>0.171</p></td><td char="." align="char"><p>1.005</p></td><td char="." align="char"><p>95.211</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>11</p></td><td char="." align="char"><p>0.156</p></td><td char="." align="char"><p>0.919</p></td><td char="." align="char"><p>96.130</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>12</p></td><td char="." align="char"><p>0.147</p></td><td char="." align="char"><p>0.864</p></td><td char="." align="char"><p>96.994</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>13</p></td><td char="." align="char"><p>0.127</p></td><td char="." align="char"><p>0.747</p></td><td char="." align="char"><p>97.741</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>14</p></td><td char="." align="char"><p>0.118</p></td><td char="." align="char"><p>0.695</p></td><td char="." align="char"><p>98.436</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>15</p></td><td char="." align="char"><p>0.096</p></td><td char="." align="char"><p>0.563</p></td><td char="." align="char"><p>98.999</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>16</p></td><td char="." align="char"><p>0.093</p></td><td char="." align="char"><p>0.549</p></td><td char="." align="char"><p>99.548</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>17</p></td><td char="." align="char"><p>0.077</p></td><td char="." align="char"><p>0.452</p></td><td char="." align="char"><p>100.00</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr></tbody></table> </ephtml> </p> <p>Table 4 Rotated component matrix</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p> Item</p></th><th align="left"><p>Factor 1 (Basic reading comprehension)</p></th><th align="left"><p>Factor 2 (Advanced reading comprehension)</p></th></tr></thead><tbody><tr><td align="left"><p>Item 51</p></td><td char="." align="char"><p>0.869</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 49</p></td><td char="." align="char"><p>0.867</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 52</p></td><td char="." align="char"><p>0.848</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 53</p></td><td char="." align="char"><p>0.844</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 50</p></td><td char="." align="char"><p>0.833</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 45</p></td><td char="." align="char"><p>0.821</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 48</p></td><td char="." align="char"><p>0.779</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 46</p></td><td char="." align="char"><p>0.777</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 56</p></td><td char="." align="char"><p>0.755</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 44</p></td><td char="." align="char"><p>0.658</p></td><td char="." align="char" /></tr><tr><td align="left"><p>Item 39</p></td><td char="." align="char" /><td char="." align="char"><p>0.846</p></td></tr><tr><td align="left"><p>Item 38</p></td><td char="." align="char" /><td char="." align="char"><p>0.841</p></td></tr><tr><td align="left"><p>Item 40</p></td><td char="." align="char" /><td char="." align="char"><p>0.810</p></td></tr><tr><td align="left"><p>Item 41</p></td><td char="." align="char" /><td char="." align="char"><p>0.786</p></td></tr><tr><td align="left"><p>Item 42</p></td><td char="." align="char" /><td char="." align="char"><p>0.700</p></td></tr><tr><td align="left"><p>Item 43</p></td><td char="." align="char" /><td char="." align="char"><p>0.671</p></td></tr><tr><td align="left"><p>Item 54</p></td><td char="." align="char" /><td char="." align="char"><p>0.600</p></td></tr></tbody></table> </ephtml> </p> <p>Item parceling refers to the process of combining multiple items assumed to be conceptually similar or to assess the same construct (Kishton & Widaman, [<reflink idref="bib24" id="ref76">24</reflink>]). Item parceling is commonly used to reduce the number of parameters estimated rather than eliminating some items and losing important information (Thompson & Melancon, [<reflink idref="bib44" id="ref77">44</reflink>]). In the present study, item parceling was employed because having each of the 46 variables as an individual observed variable was considered excessive for the small sample size (<emph>N</emph> = 179). An excessive number of variables relative to the sample size can lead to misleading findings and invalid conclusions regarding the factor structure (Bernstein & Teng, [<reflink idref="bib6" id="ref78">6</reflink>]; Kishton & Widaman, [<reflink idref="bib24" id="ref79">24</reflink>]). Items measuring the subskill and sub-knowledge associated with vocabulary, grammar, and coherence were parceled and averaged separately to create three observed variables, namely <emph>Vocabulary</emph>, <emph>Grammar</emph>, and <emph>Coherence</emph>. In addition, basic and advanced reading comprehension items were parceled and averaged separately, resulting in the formation of two distinct observed variables: <emph>Basic reading comprehension</emph>, and <emph>Advanced reading comprehension</emph>. As shown in Table 5, in total, five observed variables were created through item parceling.</p> <p>Table 5 Descriptive statistics and reliability</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Factor</p></th><th align="left"><p>Item</p></th><th align="left"><p>Mean</p></th><th align="left"><p>SD</p></th></tr></thead><tbody><tr><td align="left"><p>Vocabulary</p></td><td align="left"><p>Item4</p></td><td char="." align="char"><p>2.42</p></td><td align="left"><p>0.94</p></td></tr><tr><td align="left" /><td align="left"><p>Item5</p></td><td char="." align="char"><p>2.17</p></td><td align="left"><p>0.91</p></td></tr><tr><td align="left" /><td align="left"><p>Item6</p></td><td char="." align="char"><p>2.3</p></td><td align="left"><p>0.75</p></td></tr><tr><td align="left" /><td align="left"><p>Item7</p></td><td char="." align="char"><p>2.16</p></td><td align="left"><p>0.99</p></td></tr><tr><td align="left" /><td align="left"><p>Item8</p></td><td char="." align="char"><p>1.63</p></td><td align="left"><p>0.89</p></td></tr><tr><td align="left" /><td align="left"><p>Item9</p></td><td char="." align="char"><p>1.74</p></td><td align="left"><p>0.86</p></td></tr><tr><td align="left" /><td align="left"><p>Total</p></td><td char="." align="char"><p>2.07</p></td><td align="left"><p>0.73</p></td></tr><tr><td align="left" /><td align="left"><p>Alpha</p></td><td char="." align="char"><p>0.90</p></td><td align="left" /></tr><tr><td align="left"><p>Grammar</p></td><td align="left" /><td char="." align="char" /><td align="left" /></tr><tr><td align="left" /><td align="left"><p>Item10</p></td><td char="." align="char"><p>2.68</p></td><td align="left"><p>0.92</p></td></tr><tr><td align="left" /><td align="left"><p>Item11</p></td><td char="." align="char"><p>2.85</p></td><td align="left"><p>0.94</p></td></tr><tr><td align="left" /><td align="left"><p>Item12</p></td><td char="." align="char"><p>2.64</p></td><td align="left"><p>1.04</p></td></tr><tr><td align="left" /><td align="left"><p>Item13</p></td><td char="." align="char"><p>2.81</p></td><td align="left"><p>1.04</p></td></tr><tr><td align="left" /><td align="left"><p>Item14</p></td><td char="." align="char"><p>2.46</p></td><td align="left"><p>0.93</p></td></tr><tr><td align="left" /><td align="left"><p>Item15</p></td><td char="." align="char"><p>2.11</p></td><td align="left"><p>0.96</p></td></tr><tr><td align="left" /><td align="left"><p>Item16</p></td><td char="." align="char"><p>2.15</p></td><td align="left"><p>1.04</p></td></tr><tr><td align="left" /><td align="left"><p>Item17</p></td><td char="." align="char"><p>2.28</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Item18</p></td><td char="." align="char"><p>2.19</p></td><td align="left"><p>1.2</p></td></tr><tr><td align="left" /><td align="left"><p>Item19</p></td><td char="." align="char"><p>1.97</p></td><td align="left"><p>1.21</p></td></tr><tr><td align="left" /><td align="left"><p>Item20</p></td><td char="." align="char"><p>2.71</p></td><td align="left"><p>1.07</p></td></tr><tr><td align="left" /><td align="left"><p>Item21</p></td><td char="." align="char"><p>2.2</p></td><td align="left"><p>1.01</p></td></tr><tr><td align="left" /><td align="left"><p>Item22</p></td><td char="." align="char"><p>2.21</p></td><td align="left"><p>1</p></td></tr><tr><td align="left" /><td align="left"><p>Item23</p></td><td char="." align="char"><p>2.26</p></td><td align="left"><p>1.02</p></td></tr><tr><td align="left" /><td align="left"><p>Item24</p></td><td char="." align="char"><p>2.08</p></td><td align="left"><p>0.9</p></td></tr><tr><td align="left" /><td align="left"><p>Item25</p></td><td char="." align="char"><p>2.18</p></td><td align="left"><p>1.03</p></td></tr><tr><td align="left" /><td align="left"><p>Item26</p></td><td char="." align="char"><p>2.41</p></td><td align="left"><p>1.07</p></td></tr><tr><td align="left" /><td align="left"><p>Item27</p></td><td char="." align="char"><p>2.41</p></td><td align="left"><p>1.07</p></td></tr><tr><td align="left" /><td align="left"><p>Item28</p></td><td char="." align="char"><p>1.54</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Item29</p></td><td char="." align="char"><p>1.5</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Total</p></td><td char="." align="char"><p>2.28</p></td><td align="left"><p>0.85</p></td></tr><tr><td align="left" /><td align="left"><p>Alpha</p></td><td char="." align="char"><p>0.98</p></td><td align="left" /></tr><tr><td align="left"><p>Coherence</p></td><td align="left"><p>Item31</p></td><td char="." align="char"><p>2.61</p></td><td align="left"><p>1</p></td></tr><tr><td align="left" /><td align="left"><p>Item32</p></td><td char="." align="char"><p>2.13</p></td><td align="left"><p>1.04</p></td></tr><tr><td align="left" /><td align="left"><p>Item33</p></td><td char="." align="char"><p>2.02</p></td><td align="left"><p>1.03</p></td></tr><tr><td align="left" /><td align="left"><p>Total</p></td><td char="." align="char"><p>2.25</p></td><td align="left"><p>0.93</p></td></tr><tr><td align="left" /><td align="left"><p>Alpha</p></td><td char="." align="char"><p>0.90</p></td><td align="left" /></tr><tr><td align="left"><p>Basic reading comprehension</p></td><td align="left"><p>Item38</p></td><td char="." align="char"><p>3.06</p></td><td align="left"><p>0.96</p></td></tr><tr><td align="left" /><td align="left"><p>Item39</p></td><td char="." align="char"><p>2.5</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Item40</p></td><td char="." align="char"><p>2.12</p></td><td align="left"><p>1.07</p></td></tr><tr><td align="left" /><td align="left"><p>Item41</p></td><td char="." align="char"><p>2.08</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Item42</p></td><td char="." align="char"><p>1.69</p></td><td align="left"><p>1.09</p></td></tr><tr><td align="left" /><td align="left"><p>Item43</p></td><td char="." align="char"><p>2.16</p></td><td align="left"><p>1.1</p></td></tr><tr><td align="left" /><td align="left"><p>Item54</p></td><td char="." align="char"><p>2.3</p></td><td align="left"><p>1.02</p></td></tr><tr><td align="left" /><td align="left"><p>Total</p></td><td char="." align="char"><p>2.27</p></td><td align="left"><p>0.91</p></td></tr><tr><td align="left" /><td align="left"><p>Alpha</p></td><td char="." align="char"><p>0.94</p></td><td align="left" /></tr><tr><td align="left"><p>Advanced reading comprehension</p></td><td align="left"><p>Item44</p></td><td char="." align="char"><p>1.58</p></td><td align="left"><p>0.97</p></td></tr><tr><td align="left" /><td align="left"><p>Item45</p></td><td char="." align="char"><p>1.12</p></td><td align="left"><p>1.07</p></td></tr><tr><td align="left" /><td align="left"><p>Item46</p></td><td char="." align="char"><p>1.33</p></td><td align="left"><p>1.06</p></td></tr><tr><td align="left" /><td align="left"><p>Item48</p></td><td char="." align="char"><p>1.22</p></td><td align="left"><p>1.06</p></td></tr><tr><td align="left" /><td align="left"><p>Item49</p></td><td char="." align="char"><p>0.88</p></td><td align="left"><p>0.97</p></td></tr><tr><td align="left" /><td align="left"><p>Item50</p></td><td char="." align="char"><p>1.04</p></td><td align="left"><p>1.02</p></td></tr><tr><td align="left" /><td align="left"><p>Item51</p></td><td char="." align="char"><p>0.82</p></td><td align="left"><p>0.92</p></td></tr><tr><td align="left" /><td align="left"><p>Item52</p></td><td char="." align="char"><p>0.88</p></td><td align="left"><p>0.93</p></td></tr><tr><td align="left" /><td align="left"><p>Item53</p></td><td char="." align="char"><p>0.83</p></td><td align="left"><p>0.94</p></td></tr><tr><td align="left" /><td align="left"><p>Item56</p></td><td char="." align="char"><p>0.98</p></td><td align="left"><p>1.03</p></td></tr><tr><td align="left" /><td align="left"><p>Total</p></td><td char="." align="char"><p>1.07</p></td><td align="left"><p>0.89</p></td></tr><tr><td align="left" /><td align="left"><p>Alpha</p></td><td char="." align="char"><p>0.97</p></td><td align="left" /></tr></tbody></table> </ephtml> </p> <hd id="AN0187667274-14">Data analysia</hd> <p>Primary data analysis involved two steps. First, the measurement model that depicted the correspondence between the latent variable (i.e., reading comprehension) and its two indicators (namely <emph>Basic reading comprehension</emph> and <emph>Advanced reading comprehension</emph>) was evaluated using confirmatory factor analysis (CFA). Since there are only two indicators, to make the model identified, the loading of each indicator was constrained to be 1 and the error variances of the two indicators were set to be equal. Second, structural equation modeling (SEM) was used to explore the predictive effects of three areas of subskills and sub-knowledge (i.e., <emph>Vocabulary</emph>, <emph>Grammar</emph>, and <emph>Coherence</emph>) on reading comprehension.</p> <p>All primary analyses were conducted on <emph>Mplus</emph> 8.3 (Muthén & Muthén, 1998–[<reflink idref="bib33" id="ref80">33</reflink>]) with the estimator of Maximum Likelihood Robust (Satorra & Bentler, [<reflink idref="bib38" id="ref81">38</reflink>]). The quality of CFA and SEM models was measured by referring to the following criteria: the root mean square error of approximation (<emph>RMSEA</emph>), standardized root mean square residual (<emph>SRMR</emph>), comparative fit index (<emph>CFI</emph>), and Tucker–Lewis index (<emph>TLI</emph>). A model with <emph>RMSEA</emph> and <emph>SRMR</emph> smaller than 0.08 and 0.05 (Hu & Bentler, [<reflink idref="bib16" id="ref82">16</reflink>]) and at the same time with <emph>CFI</emph> and <emph>TLI</emph> values no smaller than 0.90 and 0.95 (Byrne, [<reflink idref="bib7" id="ref83">7</reflink>]) was determined as acceptable and good fit, respectively.</p> <hd id="AN0187667274-15">Results</hd> <p></p> <hd id="AN0187667274-16">Model fit results</hd> <p>Table 6 shows the results of CFA and SEM model fit. The measurement model showed a good fit to the data. Meanwhile, the SEM model revealing the structural relationship between subskills/sub-knowledge and reading comprehension showed an acceptable fit.</p> <p>Table 6 Results of model fit</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p><italic>X</italic><sup>2</sup>/df</p></th><th align="left"><p><italic>p</italic> value</p></th><th align="left"><p><italic>RMSEA (90% CI)</italic></p></th><th align="left"><p><italic>CFI</italic></p></th><th align="left"><p><italic>TLI</italic></p></th><th align="left"><p><italic>SRMR</italic></p></th></tr></thead><tbody><tr><td align="left"><p>Measurement model</p></td><td char="." align="char"><p>0.186/1</p></td><td char="." align="char"><p>0.666</p></td><td align="left"><p>0.000 (0.000 0.150)</p></td><td char="." align="char"><p>1.000</p></td><td char="." align="char"><p>1.004</p></td><td char="." align="char"><p>0.016</p></td></tr><tr><td align="left"><p>SEM model</p></td><td char="." align="char"><p>3.014/2</p></td><td char="." align="char"><p>0.222</p></td><td align="left"><p>0.053 (0.000 0.167)</p></td><td char="." align="char"><p>0.998</p></td><td char="." align="char"><p>0.993</p></td><td char="." align="char"><p>0.009</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0187667274-17">Results of estimates</hd> <p>Figure 1 shows the standardized estimates of the SEM Model. Three areas of subskills and sub-knowledge of reading (i.e., <emph>Vocabulary</emph>, <emph>Grammar</emph>, and <emph>Coherence</emph>) all positively and significantly predicted reading comprehension (<emph>β</emph> = 0.22, <emph>p</emph> = 0.01; <emph>β</emph> = 0.60, <emph>p</emph> < 0.001; <emph>β</emph> = 0.33, <emph>p</emph> < 0.001). Among them, <emph>Grammar</emph> is the most substantial contributor to reading comprehension, followed by <emph>Coherence</emph>, and <emph>Vocabulary</emph>. After controlling for the effect of other extraneous variables, with one standardized division unit increase in <emph>Grammar</emph>, reading comprehension will increase by 0.60 standardized division unit. The increases in reading comprehension associated with <emph>Coherence</emph>, and <emph>Vocabulary</emph> are 0.33 and 0.22 standardized division unit respectively.</p> <p>Graph: Fig. 1 Structural model representing the relationship between vocabulary, grammar, coherence, and L2 Chinese reading comprehension. Vocab, vocabulary knowledge and word processing; Grammar, grammar knowledge and syntactic parsing; Coherence, knowledge of cohesive devices and coherence building; Basic, basic reading comprehension; Advanced, advanced reading comprehension</p> <hd id="AN0187667274-18">Discussions</hd> <p>Based on the teacher perception data, this study investigated the predictive powers of sub-knowledge and subskills associated with vocabulary, grammar, and coherence on L2 Chinese reading comprehension, through a structural equation modeling approach. Key findings reveal that all three components are significant predictors of L2 Chinese reading comprehension. The most significant predictive factor is <emph>Grammar</emph>, followed by <emph>Coherence</emph>, and <emph>Vocabulary</emph>.</p> <p>Previous research has not reached a consensus on whether vocabulary knowledge or grammar knowledge plays a stronger role in L2 reading comprehension (Choi & Zhang, [<reflink idref="bib10" id="ref84">10</reflink>]). While both types of knowledge are of importance to successful reading comprehension for meaning construction (Jeon & Yamashita, [<reflink idref="bib20" id="ref85">20</reflink>]; Koda, [<reflink idref="bib25" id="ref86">25</reflink>]), in line with previous empirical studies on L2 English learners (e.g., Kim & Cho, [<reflink idref="bib23" id="ref87">23</reflink>]; Nergis, [<reflink idref="bib34" id="ref88">34</reflink>]; Shiotsu & Weir, [<reflink idref="bib41" id="ref89">41</reflink>]), the present study reinforces the argument that with reference to L2 Chinese readers, syntactic knowledge is an even more potent predictor of reading abilities than vocabulary knowledge. Furthermore, most previous studies only compared grammar knowledge and vocabulary knowledge (e.g., Hu et al., [<reflink idref="bib17" id="ref90">17</reflink>]; Shiotsu & Weir, [<reflink idref="bib41" id="ref91">41</reflink>]). The present study measured both knowledge and processing skills associated with grammar as a singular concept, as well as those related to vocabulary. Thus, the findings of this study expand our understanding of the more prominent role that grammar plays in L2 Chinese reading comprehension, as compared to vocabulary. When considering grammar knowledge and grammar processing skills as a whole, they collectively emerge as a stronger predictor than vocabulary knowledge and vocabulary processing skills measured as a singular concept. These observations may be explained by the distinct syntactic features of Chinese. As discussed previously, while the dominant sentence structures in Chinese align with those in English (SVO), the subject of a sentence in Chinese can assume diverse logical relationships relative to the predicate, which caused challenges for L2 Chinese readers. Also, the lack of final inflections to denote grammatical features in Chinese (e.g., aspect, passiveness, etc.), as well as some of its sentence patterns that have no equivalents in English, requires learners to first get acquainted with the grammar knowledge and to have the ability to conduct successful syntactic parsing before they could engage in reading comprehension in Chinese. In other words, the unique syntactic features of Chinese emphasize the significance of grammar knowledge and syntactic parsing for overall L2 Chinese reading acquisition.</p> <p>While the previous studies relied on the assessment of L2 English learner performance, this study provided additional empirical evidence for the predominant contributions of grammar from a new learner group (i.e., L2 Chinese) and a new perspective, that is, teacher perception collected through the survey questionnaire. The study is the first one that empirically compared the predictive powers of vocabulary and grammar on L2 Chinese reading comprehension. It adopted a finer-grained and more comprehensive measure of vocabulary and grammar by assessing not only knowledge but also processing skills associated with these two aspects. In constructing the questionnaire items, theoretical works on generic L2 reading, L2 Chinese reading, and Chinese linguistics were widely consulted to well represent the essential component skills and component knowledge relevant to vocabulary, grammar, and L2 Chinese reading comprehension. Particularly, through reviewing the disparities between English and Chinese, linguistic features and processing skills unique to reading Chinese language were identified and highlighted by the questionnaire items, such as word decision ability (Descriptor 6), and Chinese unique syntactic patterns (Descriptors 17, 25–27).</p> <p>Moreover, some studies (e.g., Raeisi‐Vanani & Baleghizadeh, [<reflink idref="bib37" id="ref92">37</reflink>]) revealed the influence of learner proficiency on the relationship between vocabulary, grammar, and L2 reading comprehension. To balance the influence of learner proficiency, instead of focusing on a single proficiency level, the authors managed to include approximately equal numbers of responses from first-year through fourth-year classes, representing beginning to advanced proficiency levels. The findings suggest that, with reference to L2 Chinese learners with one to four years of Chinese learning experience as a whole group, <emph>Grammar</emph> is a better predictor of L2 reading comprehension than <emph>Vocabulary</emph>.</p> <p>The relationship between knowledge of <emph>Coherence</emph> and L2 reading comprehension has seldom been investigated previously. This study found that its predictive power is significant and even larger than that of <emph>Vocabulary</emph>. This finding suggests that the mastery of cohesive devices is of great significance to the reading comprehension of L2 Chinese (Lin & Gao, [<reflink idref="bib28" id="ref93">28</reflink>]), which is related to the discourse features of the language. Unlike those sentence-oriented languages that have distinct sentence boundaries and all the important elements (subjects, predicates, and objects), the reading comprehension of Chinese, a discourse-oriented language, relies on all the information at the discourse level instead of within the sentence level (Tsao, [<reflink idref="bib45" id="ref94">45</reflink>]). Therefore, mastering cohesive devices, especially inter-sentence connectors, is crucial for L2 Chinese reading. As a result, it is conceivable that the knowledge of cohesive devices and coherence building was observed to be a significant predictor of L2 Chinese reading comprehension.</p> <p>Lastly, the results from the teacher perception data align with those from student performance assessments, underscoring the trustworthiness and validity of teacher perception as an alternative gauge for L2 reading comprehension and related skills and knowledge. These findings echo previous studies (e.g., Graus & Coppen, [<reflink idref="bib15" id="ref95">15</reflink>]; Lin, [<reflink idref="bib27" id="ref96">27</reflink>]; Scheffler, [<reflink idref="bib39" id="ref97">39</reflink>]) that have emphasized the credibility of teacher perceptions, informed by their experience and training, in assessing L2 proficiency.</p> <hd id="AN0187667274-19">Conclusion, implications, and future directions</hd> <p>All three areas of subskills and sub-knowledge of reading (i.e., <emph>Vocabulary, Grammar,</emph> and <emph>Coherence</emph>) are significant predictors of L2 Chinese reading comprehension. Based on teacher perception data, the present study yielded empirical evidence to support the argument that <emph>Grammar</emph> is of a stronger predictive power on L2 Chinese reading comprehension than <emph>Vocabulary</emph> (e.g., Kim & Cho, [<reflink idref="bib23" id="ref98">23</reflink>]; Nergis, [<reflink idref="bib34" id="ref99">34</reflink>]; Shiotsu & Weir, [<reflink idref="bib41" id="ref100">41</reflink>]). The predictive power of <emph>Coherence</emph>, which has seldom been investigated, is also significant and even stronger than that of <emph>Vocabulary</emph>. The findings obtained through the teacher perception data are in consistent with those yielded based on assessments of student performance. This highlights the credibility and reliability of teacher perceptions as an alternative measurement for L2 reading comprehension, the subskills and sub-knowledge related to reading.</p> <p>The findings of the present study have several pedagogical implications. Although regressions do not imply causal relationships, the strong predictive powers of sub-skills/sub-knowledge associated with vocabulary, grammar, and coherence still highlight their importance in the teaching and learning of L2 Chinese reading. Thus, in addition to the instruction of vocabulary, grammar, and coherence in integrated L2 Chinese courses, the training of these subskills and sub-knowledge should be explicitly and implicitly integrated into reading instruction. First of all, reading and word learning are coincidental and reciprocal (Koda, [<reflink idref="bib25" id="ref101">25</reflink>]). It is beneficial to adopt instructional approaches promoting incidental word learning while reading. For instance, guessing the meaning of unknown words based on context, identifying synonyms from the text, student making glossaries for new words are examples of activities that could facilitate incidental word learning in reading instruction. Grammar knowledge and syntactic parsing were found to be the most powerful predictor; however, the training of grammar is seldom explicitly addressed in the L2 Chinese reading class. Regarding the integration of grammar training into reading, teachers could use activities that raise student awareness of the usages of given grammar patterns in various contexts. Similarly, the previous L2 Chinese reading instruction has paid little attention to the knowledge of cohesive devices and coherence building. Activities that improve student understanding of the forms and semantic relationships of cohesive devices and activities that focus on coherence building should be important components of the L2 Chinese reading class. Lastly, the 46 items in the data collection questionnaire represent essential components of the above-mentioned three areas. Teachers can refer to these items to determine the sub-skills and component knowledge that need to be trained in each area.</p> <p>This study treated responses from four instructional levels as one single group, with each level equally represented. Given that some earlier studies reported the impact of learner proficiency on the relative contributions of grammar and vocabulary (e.g., Raeisi‐Vanani & Baleghizadeh, [<reflink idref="bib37" id="ref102">37</reflink>]), future research with a larger number of responses from each proficiency level may consider testing the generalizability of the structural equation model established in the present study across proficiency levels, through the approach of multiple-group structural equation modeling. Last but not least, L2 reading is associated with multiple component skills/knowledge beyond grammar, vocabulary, and coherence, including knowledge of discourse pattern, pragmatic knowledge, and strategic competence. The relative contributions of these components to L2 reading comprehension await further exploration.</p> <hd id="AN0187667274-20">Declarations</hd> <p></p> <hd id="AN0187667274-21">Conflict of interest</hd> <p>There are no financial interests to report.</p> <hd id="AN0187667274-22">Appendix</hd> <p>Chinese as a second language reading proficiency questionnaire</p> <p>Please indicate the instructional level you are going to evaluate: _________</p> <p></p> <ulist> <item> 1st/2nd/3rd/4th-year Chinese classes</item> </ulist> <p>Using the following rating scale and descriptors, please evaluate the reading proficiency of a hypothetical average learner at this instructional level. The learner is defined as a hypothetical average-achieving, non-heritage, and English-speaking L2 Chinese learners at this level. Your evaluation can be made by recalling students' performance in class activities, reading comprehension tests, and assignments.</p> <p></p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Rating category</p></th><th align="left"><p>Definition</p></th></tr></thead><tbody><tr><td align="left"><p>0</p></td><td align="left"><p>This describes a level, which is definitely <italic>beyond</italic> average learners' capabilities. Can <italic>not</italic> be expected to perform like this</p></td></tr><tr><td align="left"><p>1</p></td><td align="left"><p>Could <italic>minimally</italic> perform like this in favorable circumstances. This describes a performance that is <italic>slightly beyond</italic> average learners' skill level. (Favorable circumstance refers to the situation in which the learners get help or hints, have time to prepare or think over; the topics are familiar; surroundings favor the performance.)</p></td></tr><tr><td align="left"><p>2</p></td><td align="left"><p>Could be expected to perform like this without support in normal circumstances. The average learners' ability is <italic>on this level</italic></p></td></tr><tr><td align="left"><p>3</p></td><td align="left"><p>Could be expected to perform like this even in unfavorable circumstances with efforts. This describes a performance that is <italic>slightly below</italic> average learners' skill level. (Unfavorable circumstance refers to the situation in which the learners do not get help or hints, have no time to prepare or think over; the topics are unfamiliar; surroundings do not favor the performance.)</p></td></tr><tr><td align="left"><p>4</p></td><td align="left"><p>Could be expected to perform like this with ease in all circumstances. This describes a performance that is <italic>obviously below</italic> average learners' skill level</p></td></tr></tbody></table> </ephtml> </p> <p></p> <ulist> <item> <emph>Vocabulary knowledge and word processing</emph> </item> </ulist> <p>Item 4: Can derive meaning of sentences with coverbial phrases.</p> <p>Item 5: Can derive meaning of sentences with verb complements.</p> <p>Item 6: When reading text on their level, can group adjacent characters into words successfully.</p> <p>Item 7: Can analyze the intra-word structure.</p> <p>Item 8: Can use knowledge on word formation to help decode unknown words.</p> <p>Item 9: When reading text on their level, can contextually process polysemes (words with multiple meanings).</p> <p></p> <ulist> <item> <emph>Grammar knowledge and syntactic parsing</emph> </item> </ulist> <p>Item 10: Can understand limited types of sentence structures, including Subject-Predicate constructions, simple SVO constructions, all in affirmative, negative, and simple question form.</p> <p>Item 11: Can control certain structural sets, which have a limited number of items, including interrogatives (<emph>shuí, shén me</emph>), specifiers (<emph>zhè, nà</emph>), and very common noun measures (<emph>kuài, běn</emph>) etc.</p> <p>Item 12: Can understand simple Noun + Noun modification with <emph>de</emph> and Stative Verb + Noun modification with <emph>de</emph>.</p> <p>Item 13: Can comprehend preliminarily high-frequency connectors forming complex sentences (e.g., <emph>de shí hou, suī rán... kě shì</emph>).</p> <p>Item 14: Can derive meaning of sentences with the aspect markers (such as <emph>le</emph>), although still makes errors.</p> <p>Item 15: Can understand roughly the relationship of multiple modifiers to element being modified, but may have some confusion.</p> <p>Item 16: Can comprehend sentences with following basic patterns: Relative clause modification.</p> <p>Item 17: Can comprehend sentences with following basic patterns: <emph>ba</emph>-disposal.</p> <p>Item 18: Can comprehend sentences with following basic patterns: <emph>bei</emph>-passive.</p> <p>Item 19: Can comprehend sentences with following basic patterns: Indefinite usages of question words.</p> <p>Item 20: Can comprehend sentences with following basic patterns: Exclusive usages of question words.</p> <p>Item 21: Can comprehend sentences with following basic patterns: Various aspect markers.</p> <p>Item 22: Can comprehend sentences with following basic patterns: Resultative compounds.</p> <p>Item 23: Can comprehend sentences with following basic patterns: Directional compounds.</p> <p>Item 24: Can be aware of the appropriate position of adverbial phrases in Chinese sentences.</p> <p>Item 25: Can comprehend sentences with following unique Chinese syntactic features: Nominal sentences (i.e., sentences contain no verbs).</p> <p>Item 26: Can comprehend sentences with following unique Chinese syntactic features: "<emph>Shi...de</emph>" structure.</p> <p>Item 27: Can comprehend sentences with following unique Chinese syntactic features: Topic-comments structure.</p> <p>Item 28: Can comprehend text successfully when the number of features and structural devices from the literary/classical stratum is limited.</p> <p>Item 29: Can have emerging control of high-frequency grammatical constructions common to expository prose.</p> <p></p> <ulist> <item> <emph>Knowledge of cohesive devices and coherence building</emph> </item> </ulist> <p>Item 31: Can know meanings and functions of a limited number of cohesive devices.</p> <p>Item 32: Can be aware of commonly used cohesive devices within and across paragraphs.</p> <p>Item 33: Can use knowledge on cohesive devices to facilitate reading comprehension.</p> <p></p> <ulist> <item> <emph>Basic reading comprehension</emph> </item> </ulist> <p>Item 38: Can comprehend set expressions using basic vocabulary.</p> <p>Item 39: Can read simple connected, specially prepared material for basic survival and social needs (<emph>Note.</emph> "specially prepared material" refers to "material specially prepared for adult second language learners of Chinese").</p> <p>Item 40: Can comprehend sufficiently specially-prepared discourse for informative purposes.</p> <p>Item 41: With use of a dictionary, can comprehend sufficiently main ideas and some facts in authentic material paralleling oral language.</p> <p>Item 42: Can decode authentic materials, which are harder than oral language, for key points with use of a bilingual dictionary.</p> <p>Item 43: Can decode critical elements of public announcements to determine who, when, and where regarding such subjects as public events by using a dictionary.</p> <p>Item 54: When reading text on their level, can only draw simplest inferences from reading.</p> <p></p> <ulist> <item> <emph>Advanced reading comprehension</emph> </item> </ulist> <p>Item 44: Can follow the narrative thread in extended, specially-prepared discourse.</p> <p>Item 45: Can decode authentic prose (including newspapers and magazines) for general ideas.</p> <p>Item 46: Can glean a range of specific facts from short authentic pieces on sports, movies, and current events, but with error.</p> <p>Item 48: Can comprehend authentic expository prose without reliance on a dictionary where such prose tends to reflect the spoken language.</p> <p>Item 49: Can comprehend, not just decode, a narrow range of authentic, expository material, including areas of professional interest, without the use of a dictionary.</p> <p>Item 50: Can comprehend, with some dictionary use, authentic material over a wide range of subject matter and topics.</p> <p>Item 51: Can comprehend standard newspaper items addressed to the general public, routine correspondence, reports and technical material in field of interest.</p> <p>Item 52: Can decode, with a dictionary and with substantial effort and moderate error, popular novels, essays, and most literature for the general public.</p> <p>Item 53: Can understand minimally, yet with significant difficulties, prose which is more characteristic of the literary/classical style.</p> <p>Item 56: Can appreciate, to a limited degree, nuances or stylistics, but gaps in detail may be frequent.</p> <hd id="AN0187667274-23">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0187667274-24"> <title> References </title> <blist> <bibl id="bib1" idref="ref17" type="bt">1</bibl> <bibtext> Adolf SM, Perfetti CAStone CA, Silliman ER, Ehren BJ. 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  Label: Title
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  Data: Subskills and Sub-Knowledge in Chinese as a Second Language Reading Comprehension: A Structural Equation Modeling Study
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  Data: English
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Jia+Lin%22">Jia Lin</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-6002-8887">0000-0002-6002-8887</externalLink>)<br /><searchLink fieldCode="AR" term="%22Li+Yang%22">Li Yang</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-4608-2705">0000-0002-4608-2705</externalLink>)
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Reading+and+Writing%3A+An+Interdisciplinary+Journal%22"><i>Reading and Writing: An Interdisciplinary Journal</i></searchLink>. 2025 38(7):2059-2085.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 27
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
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  Label: Document Type
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  Data: Journal Articles<br />Reports - Research<br />Tests/Questionnaires
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  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Skills%22">Reading Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+Equation+Models%22">Structural Equation Models</searchLink><br /><searchLink fieldCode="DE" term="%22Vocabulary+Development%22">Vocabulary Development</searchLink><br /><searchLink fieldCode="DE" term="%22Grammar%22">Grammar</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Attitude+Measures%22">Attitude Measures</searchLink><br /><searchLink fieldCode="DE" term="%22Prior+Learning%22">Prior Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Rhetoric%22">Rhetoric</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Instruction%22">Second Language Instruction</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s11145-024-10588-7
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  Label: ISSN
  Group: ISSN
  Data: 0922-4777<br />1573-0905
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To achieve efficient reading comprehension, Chinese as a second language (L2) learners adopt various component skills and knowledge, including the aspects of vocabulary, grammar, and coherence. However, there is no consensus regarding the relative predictive powers of these three areas in L2 reading comprehension. Instead of employing direct measurement of student reading performance, this study aims to explore this issue by analyzing teacher perception data. Using a Likert-scale questionnaire, 95 experienced teachers rated L2 Chinese learners' reading comprehension, subskills, and sub-knowledge of reading. The results of structural equation modeling reveal that the three areas of subskills and sub-knowledge (i.e., "Vocabulary," "Grammar," and "Coherence") all positively and significantly predicted reading comprehension. "Grammar" exhibits the strongest predictive power, followed by "Coherence," and "Vocabulary." This study enhances our understanding of the relative contributions of subskills and sub-knowledge to L2 Chinese reading. Implications for L2 Chinese instruction are provided.
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  Data: 2025
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        PageCount: 27
        StartPage: 2059
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      – TitleFull: Subskills and Sub-Knowledge in Chinese as a Second Language Reading Comprehension: A Structural Equation Modeling Study
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