Multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners

Multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners Tianxu Chen, Ruohan Su, Mengyue Wang, Qing Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9026197/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract As a fundamental skill for language ability, reading comprehension involves intricate information processing that is closely constrained by readers’ cognitive ability (i.e., working memory). Although most previous studies acknowledge that both the capacity and processing efficiency of working memory affects reading comprehension, the multidimensional nature of these constructs has led to inconsistent findings, and empirical evidence specifically targeting L2 Chinese remains scarce. This study investigated the multi-dimensional associations between working memory and reading comprehension among 74 intermediate-level L2 Chinese learners whose native language was English. Three tasks of working memory (i.e., digit-span, phonological short-term-memory, and reading span tasks) and two tasks of reading comprehension (for simple and complex comprehension) were conducted. The results showed that 1) the storage, auditory, and dual-task capacities (storage and processing capacities) of working memory were significantly and positively associated with simple comprehension, while both storage and dual-task capacities were positively correlated with complex comprehension; 2) al l capacities of working memory were found to be independent predictors of simple comprehension, while the storage and dual-task capacities were independently predictive of complex comprehension; and 3) the dual-task capacity contributed most to both simple and complex reading comprehension when all three working memory capacities were present. Therefore, it is advisable for tutors to progressively integrate daily training of working memory into L2 Chinese reading instruction. Humanities/Language and linguistics Social science/Language and linguistics Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Chinese as a second language working memory reading comprehension multi-dimensional correlation Introduction Reading comprehension is a complex cognitive process in which learners construct meaning from text (Hao et al., 2020 ; Zhu et al., 2018 ). In this process, learners continuously associate current active information in working memory with subsequent content to construct coherent mental representations (Kintsch, 1988 ). Working memory represents a cognitive hub that connects word recognition with overall semantic construction, and is therefore key to predicting the reading comprehension of individuals. This concept has received widespread support from numerous studies of first language (L1) reading (Daneman & Carpenter, 1980 ; Kintsch & van Dijk, 1978 ; Nouwens et al., 2016 ). While L2 reading is subject to a wider range of variables than L1 reading (e.g., language proficiency, L1 background, and cultural differences), there is no doubt that working memory plays an indispensable role. Indeed, the core cognitive processes associated with reading are common to both L1 and L2 reading, and involve the extraction of basic information and the integration of complex meaning (Grabe & Jiang, 2018 ). Working memory has been consistently found to be positively correlated with L2 reading comprehension (Alptekin & Erçetin, 2010 ; Jeon & Yamashita, 2014 ; Service et al., 2002 ). However, the reported correlation coefficients vary considerably among different studies, and some studies have even questioned the existence of such a correlation (Van Dyke et al., 2014 ). These discrepancies suggest that the relationship between working memory and L2 reading may be multi-dimensional and complex. However, experimental evidence on this topic remains limited, and a consensus has yet to be reached. To clarify the multi-dimensional associations between working memory and reading comprehension, this study defines the two concepts first. Working memory is a system responsible for information storage and processing during cognitive tasks (Baddeley & Hitch, 1974 ), and is limited by its capacity for handling information. Various theoretical models of working memory have been suggested, among which the multi-component model proposed by Baddeley et al. (2000) is noteworthy due to its strong explanatory power and ability to be continuously refined. It describes a dynamic cognitive structure with the central executive at the core. The model contains a series of relatively independent subsystems, including the phonological loop, the visuospatial sketchpad, and the subsequently included episodic buffer. The central executive, as the hub of attentional control, coordinates cognitive resources, regulates attention, and interacts with long-term memory. The phonological and visuospatial subsystems are specialized for the temporary storage and preliminary processing of auditory-verbal and visual-spatial information, respectively. Therefore, working memory is a complex concept that includes multiple dimensions from the perspectives of structural components (e.g., the phonological loop and visuospatial sketchpad) and internal functions (e.g., storage, processing). Reading comprehension resembles working memory in its hierarchical and complex capabilities. The construction-integration model proposed by Kintsch ( 2018 ) provides a theoretical framework for understanding this hierarchy. This model conceptualizes reading comprehension as a dynamic process consisting of two stages, namely, construction and integration. Specifically, the construction stage primarily involves the activation of lexical semantics and formation of the textbase; it relies primarily on both basic storage and local processing. In contrast, the integration stage represents a highly active and resource-intensive process involving the integration of new information with prior knowledge, suppression of irrelevant interference, logical inference, and the development of a coherent situational model or macrostructure. In this study, reading comprehension was operationalized as “simple” and “complex” comprehension based on this model. “Simple comprehension” essentially corresponds to the construction stage, associated with low resource demands, while “complex comprehension” corresponds to the integration stage, involving high demands on cognitive resources. As different levels of reading comprehension differ in terms of cognitive load and degree of activation, the relative participation and contributions of the different components of working memory also differ among these hierarchical tasks. However, most previous studies have not differentiated precisely between these inherent hierarchical stages at the operational level. When the question is narrowed to how the “specific dimensions” of working memory are linked to the “particular level” of reading comprehension, conclusions become inconsistent, if not contradictory. First, conclusions differ according to whether the “internal functional dimensions” (storage, processing) of working memory were analyzed separately or comprehensively. Several studies have emphasized the central role of the processing function. For instance, Chen and Xu ( 2010 ), using eye-tracking measurements, found that during the processing of ambiguous sentences in the second language, the processing dimension, rather than the storage dimension, of working memory predominated. Likewise, Alptekin and Erçetin ( 2010 ) reported that in second-language reading, only the processing dimension of working memory was significantly associated with the degree of reading comprehension. Nevertheless, other studies have argued that the storage function is equally indispensable. For example, both Bayliss et al. ( 2003 ) and Unsworth et al. ( 2009 ) demonstrated that the storage dimension could significantly predict reading comprehension scores even after statistically controlling for the influences of the processing component. In terms of the separate measurement approaches mentioned above, there are two explanations for the differences in opinion. First, although the storage component of working memory can be measured separately in operational tasks (e.g., digit span tasks) (Bayliss et al., 2003 ), the processing component cannot. This is essentially due to the reliance of all processing tasks involving language (including reading comprehension) on the successful maintenance and temporary storage of information (Daneman & Merikle, 1996 ; Streitberger et al., 2024 ). Consequently, attempting to measure the processing component without considering the storage component suffers from theoretical limitations and questionable validity. Second, some researchers have claimed that working memory essentially involves the simultaneous maintenance and processing of information under conditions of limited cognitive resources (Barrouillet & Camos, 2012 ). Therefore, the measurement of either storage or processing in isolation cannot predict complex cognitive activities such as reading comprehension. For this reason, it is believed that only dual-task paradigms measuring both storage and processing (e.g., reading span tasks) represent predictors with high ecological validity (Lépine et al., 2005 ; Unsworth & Engle, 2006 ). There are also marked discrepancies between the conclusions of studies on the “component dimension” (phonological, visuospatial) of working memory. Most previous studies employing auditory span tasks have supported the ability of the auditory-phonological dimension of working memory to predict reading comprehension (Daneman & Carpenter, 1980 ). In contrast, studies using visuospatial tasks of working memory demonstrated only a weak correlation between the auditory-phonological dimension of working memory and reading comprehension (Daneman & Tardiff, 1987 ; Seigneuric et al., 2000 ). Furthermore, there is a general lack of unified standards for both the selection of text materials and methods for the assessment of reading comprehension. Some studies have evaluated reading comprehension in terms of sentence-level processing skills, including grammatical judgment and semantic processing (Just & Carpenter, 1992 ; Waters & Caplan, 2004 ), while others have used self-adapted materials with varying criteria and standards (Chun & Payne, 2004 ). Overall, few previous studies have considered multi-dimensionality in the design and measurement of reading comprehension. This presents significant difficulties for the direct comparison of the results of different studies, and the relationships between various dimensions of working memory and reading comprehension remain to be confirmed. In this study, the specific associations between different dimensions of working memory and reading comprehension in L2 Chinese learners were investigated using an experimental approach. At the working-memory level, we focused on the core functional dimensions (storage and processing), paying particular attention to the auditory-phonological dimension that is closely linked to language processing. Reading comprehension was stratified into two hierarchical levels: simple comprehension (construction stage) and complex comprehension (integration stage). Therefore, this study aims to address the following research questions: RQ1 Are there significant correlations between the dimensions of working memory and the different levels of reading comprehension in L2 Chinese learners? RQ2 : If so, to what extent do working memory dimensions predict learners' performance in simple versus complex reading comprehension? Methods Participants A total of 78 intermediate-level native English speakers who were learning Chinese as a second language were enrolled. Of these, 74 completed all tasks as required, resulting in a valid response rate of 95%. Twenty-three of the 74 participants were male, and 51 were female, with an overall average age of 25. All participants had passed Hanyu Shuiping Kaoshi (HSK, a national, standardized test measuring Chinese profciency) Level 3, while 39 had passed HSK Level 4. All participants had normal or corrected-to-normal vision, possessed basic computer operational skills, and provided written informed consent before the start of the study. Tasks The tasks used in the study were all validated and demonstrated good reliability. The tasks were administered using Gorilla Experimenter Builder ( http://gorilla.sc ), a professional online experimental platform, to ensure procedural standardization and consistency. All tasks underwent and passed prior pilot testing to confirm appropriate difficulty and length. Digit span task. The storage dimension (i.e., storage capacity) of the working memory of the participants was assessed using the digit span task (Chen et al., 2020 ). This task comprised forward and backward digit span tasks. The task required the participants to recall a series of progressively longer sequences of digits in either the original or reversed order. Fourteen sequences were included in total, and each correctly recalled sequence scored 1 point. The task took approximately 4 min to complete. The reliability of the task across all items was acceptable (Cronbach’s α = .723). Example 836; 9275; 37928; 254673; 2683048; 52864934; 372840823 (forward) 482; 1736; 50127; 379145; 6992643; 24953928; 482638127 (backward) Phonological short-term memory task. The auditory dimension of working memory was measured by recognition of non-word sequences (Gathercole et al., 2001 ), enabling assessment of an individual’s ability to temporarily store and activate auditory information in memory (representing the “auditory capacity”). First, the participants listened to a list of pseudowords that conformed to English phonotactic rules but were meaningless. They then listened to a second list and were required to judge whether the order of the pseudowords was identical in the two lists. A practice trial was conducted before the formal task to enable the participants to familiarize themselves with the task. Correct responses scored 1 point, while incorrect or omitted responses scored 0 points. The duration of the task was approximately 13 min. The reliability of the task across all items was acceptable (Cronbach’s α = .720). Specifically, according to the multi-component model, the phonological loop is a subsystem that integrates both storage and processing functions. The storage function is reflected by brief retention of phonological information, while processing involves the reactivation of fading phonological representations. Most tasks involving the repetition of non-words (Chun & Payne, 2004 ) primarily assess the storage capacity and do not reflect the processing function. Therefore, this study used a phonological short-term memory task that incorporated a word sequence-recognition task. This engaged both storage and processing functions simultaneously, thereby enabling a comprehensive evaluation of the auditory dimension. To avoid potential homogeneity issues arising from the use of auditory span and reading span tasks with similar formats, we used the “non-word sequence recognition task” for measuring the auditory dimension of working memory. Additionally, pseudowords, instead of real words, were used to eliminate the influence of existing lexical knowledge on the task performance, thereby providing an effective measurement of the core functions of the phonological loop (Chun & Payne, 2004 ). Example Group 1 (Same) Table 1 : marl; coll; pab; meb Task Table 1 : marl; coll; pab; meb Group 2 (Different) Table 1 : cark; mup; gop; norb; jooch Task Table 1 : mup; cark; jooch; norb; gop Reading span task. The storage and processing dimensions of working memory (described as “dual-task capacity”) were assessed using a modified reading span task (Daneman & Carpenter, 1980 ), this is currently the most widely used task for working memory. The participants followed a dual-task paradigm, in which they were first required to judge, within a time limit, whether a presented sentence was semantically plausible. Then, after completing a set of sentences (between 2 and 5 sentences), they were asked to recall the final word of each sentence in the correct order. The task materials consisted of four groups, each of which contained three sets of sentences. There were two sentences in the first group (six sentences in total), while the second group contained sets of three sentences (nine sentences in total), the third group had sets of four sentences (12 sentences in total), and the fourth group had sets of five sentences (15 sentences in total). Overall, the task comprised 42 semantically unrelated sentences, half of which were semantically plausible and half were not. All sentences were 10–13 words in length and ended with different words. There were no semantic or phonological similarities between the last words of sentences in different sentence groups or within the same group. Practice trials were provided for the participants before they undertook the formal tasks. In the semantic judgment task, each correct response scored 1 point, while incorrect or omitted responses scored 0 points. In the final word-recall task, each correctly recalled word in the correct order scored 1 point, an incorrect or omitted response scored 0 points, and a correct word but in the wrong order scored 0.5 points. The maximum score was 84 points, and the task took approximately 13 min. The reliability of the task across all items was acceptable (Cronbach’s α = .733). Notably, while previous studies have varied in their use of L1 or L2, evidence suggests a positive correlation between working memory in both languages (Alptekin et al., 2014 ). To minimize potential confounds related to L2 proficiency and language transfer, we conducted the semantic judgment task in the participants' L1. The reading materials were sourced from Harrington and Sawyer ( 1992 ). Example (Group 1, Set 1): ① Semantic judging: At night, the prisoners danced through a hole in the wall. (unreasonable) The young woman and her boyfriend thought they saw a dog. (reasonable) ② Recall the last word: Wall; dog Reading comprehension task. Considering the Chinese proficiency levels of the participants, the text materials for the reading comprehension task used in this study were retrieved from 11 sets of authentic HSK Level 4 past year papers (H40000, H41001–H41009, H41110, H41111). The questions were divided into two dimensions: simple and complex comprehension. Ten questions for the simple comprehension dimension were obtained from items 66‒79 of the above papers. Each question consisted of 1‒3 sentences, with character counts ranging from 20 to 80. The total score for this section was 10 points, with 1 point awarded for each correct answer and 0 points for incorrect or unanswered questions. The duration of the task was approximately 10 min. The reliability of the task across all items was acceptable (Cronbach’s α = .644). Example 我们有两只耳朵, 一个嘴, 应该多听少说.(We have two ears and one mouth, so we should listen more and speak less.) 问题: 这段话告诉我们:(Question: This tells us that:) A 要多听别人说(We should listen more to what others say) B 要准时发言(We should speak on time) C 要多表扬别人(We should praise others more) D 要严格要求自己(We should be strict with ourselves) Five questions for the complex comprehension dimension were retrieved from items 80‒85. Each question consisted of two sub-questions, resulting in a total of nine items[1]. These items contained five‒eight sentences, with total character counts ranging from 150 to 200. The maximum score for this section was nine points, with 1 point awarded for each correct answer and 0 points for incorrect or unanswered items. The duration of the task was approximately 10 min. The reliability of the task across all items was acceptable (Cronbach’s α = .649). Example (The task was originally in Chinese, and we translated it into English for the convenience of readers.) Scientific studies have demonstrated that colors can influence one’s mood, and different colors can evoke different emotions. For instance, red can make people feel passionate and excited; yellow and white tend to induce a cheerful and happy mood; black, however, can easily make people feel sad; when people see blue, they often feel comfortable and become calm; green allows our eyes to rest and is also beneficial to our health. (1) According to the paragraph, which color makes people feel upset? A. White; B. Black; C. Yellow; D. Blue. (2) This paragraph discusses: A. The differences between colors; B. Stories about colors; C. The benefits of colors for the eyes; D. The relationship between colors and mood. Results The study utilized a 3×2 within-subjects design accompanied by online tasking of the participants. After completion of the tasks, the overall scores of the participants were recorded. SPSS 27.0 was used for all analyses, including descriptive statistics, correlation analysis, and hierarchical regression analysis, to explore the multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners. The scores from all tasks were standardized by dividing the original score by the corresponding total number of items, and these standardized scores were used for subsequent statistical analyses. Theoretically, the score on a task was proportional to the learner’s performance in terms of that specific capability. Table 1 summarizes the descriptive statistics of the various tasks. Table 1 Descriptive statistics (N = 74) Item Number of questions Mean Variance Standard deviation 95%CI Lower limit Upper limit Digit span task (storage capacity) 14 0.602 0.030 0.172 0.564 0.639 Phonological short-term memory task (auditory capacity) 24 0.815 0.020 0.142 0.781 0.847 Reading span task (dual-task capacity) 84 0.770 0.006 0.080 0.751 0.789 Simple comprehension task 10 0.930 0.015 0.124 0.899 0.955 Complex comprehension task 9 0.835 0.033 0.180 0.796 0.874 Correlation analysis Following Kline ( 2015 ), we adopted the criteria that absolute values exceeding 3.0 for skewness (SI) and 10.0 for kurtosis (KI) indicate severe non-normality. Inspection of the data showed that all variables were well within these limits; therefore, no significant violations of normality were observed. Pearson correlation analysis was conducted on the task results to answer Research Question 1 (Table 2 ). The results showed that the storage, auditory, and dual-task capacities in working memory were significantly positively correlated with simple comprehension capability, while the storage and dual-task capacities in working memory were significantly positively associated with complex comprehension capability. Table 2 Results of Pearson correlation analysis (N = 74) 1. Digit span task (storage capacity) 1 2 3 4 5 -- 2. Phonological short-term memory task (auditory capacity) 0.501 *** -- 3. Reading span task (dual-task capacity) 0.412 *** 0.185 -- 4. Simple comprehension task (simple comprehension capability) 0.307 *** 0.273 * 0.454 *** -- 5. Complex comprehension task (complex comprehension capability) 0.244 * 0.101 0.291 * 0.414 ** -- Note . p *** < .001, p ** < .01, p * < .05. All tasks were two-tailed. In the correlation analysis, the effect size represents the strength of the correlations between different variables (Zhang, 2021 ). Cohen ( 1988 ) reported that the small, medium, and large effect sizes correspond to r values of approximately ± 0.1, ± 0.3, and ± 0.5, respectively. In this study, a moderate positive correlation was observed between the storage capacity of working memory and simple comprehension capability, with a weaker correlation between the storage capacity of working memory and complex comprehension capability. Furthermore, the auditory capacity of working memory showed a moderate positive association with simple comprehension capability. Additionally, a significant association was found between the dual-task capacity of working memory and simple comprehension capability, together with a moderate positive correlation between dual-task capacity and complex comprehension capability. Overall, dual-task capacity was most strongly associated with reading comprehension. Hierarchical regression analysis Hierarchical regression analysis was conducted using simple and complex comprehension capabilities as dependent variables to answer Research Question 2. The effects of different dimensions of working memory on simple comprehension capability were investigated. At Level 1, the digit-span, phonological short-term memory, and reading-span tasks were incorporated in the model, followed by the subsequent introduction of the other two tasks. Table 3 summarizes the results of the hierarchical regression prediction of simple comprehension capability based on the different dimensions of working memory. Table 3 Hierarchical regression prediction of simple comprehension capability based on different dimensions of working memory (N = 74) R R 2 R 2 change B SE β t Sig. VIF Level 1 Model 1 0.307 0.094 ** Digit span task 0.220 0.081 0.307 2.732 0.008 Model 2 0.273 0.074 * Phonological short-term memory task 0.238 0.099 0.273 2.407 0.019 Model 3 0.454 0.207 *** Reading span task 0.706 0.163 0.454 4.329 *** Level 2 Model 1 0.336 0.113 * 0.019 Digit span task 0.163 0.093 0.227 1.756 0.083 1.335 Phonological short-term memory task 0.139 0.112 0.159 1.234 0.221 1.335 Model 2 0.493 0.243 *** 0.169 *** Phonological short-term memory task 0.170 0.091 0.195 1.860 0.067 1.036 Reading span task 0.649 0.163 0.418 3.982 *** 1.036 Model 3 0.473 0.224 *** 0.017 Reading span task 0.614 0.178 0.395 3.445 *** 1.204 Digit span task 0.103 0.083 0.144 1.253 0.214 1.204 Level 3 Model 1/2/3 0.495 0.246 *** Digit span task 0.041 0.093 0.057 0.438 0.663 1.553 Phonological short-term memory task 0.149 0.104 0.171 1.421 0.160 1.335 Reading span task 0.620 0.177 0.400 3.506 *** 1.205 Note . R , correlation coefficient; R 2 , coefficient of determination; R 2 change, change in the coefficient of determination; B , regression coefficient; SE, standard error; β , standardized regression coefficient; t , statistical value; Sig., significance level; VIF, variance inflation factor; p *** < .001, p ** < .01, p * < .05. At Level 1, storage capacity ( B = 0.220, β = 0.307, p < .01), auditory capacity ( B = 0.238, β = 0.273, p < .05), and dual-task capacity ( B = 0.706, β = 0.454, p < .001) were found to be significantly predictive of simple comprehension capability. At Level 2, with the other dimensions controlled, the inclusion of the phonological short-term memory task did not significantly enhance the explanatory power of Model 1 (Δ R 2 = 0.019, p > .05), while the introduction of the reading-span task significantly improved the explanatory power of Model 2 (Δ R 2 = 0.169, B = 0.649, β = 0.418, p < .001), suggesting that dual-task capacity was an independent predictor of simple comprehension capability. Model 3 verified this conclusion, demonstrating that dual-task capacity significantly predicted simple comprehension capability even if the storage capacity was controlled ( B = 0.614, β = 0.395, p < .001), with a 1.7% increase in the explanation rate of the model. At Level 3, the explanatory power of the model was R ² = 0.246 ( p < .001), with the predictive effect of dual-task capacity remaining significant ( B = 0.620, β = 0.400, p < .001), while the predictive effects of the other two capacities were no longer significant (storage capacity: p = .663; auditory capacity: p = .160). The variance inflation factor (VIF) was below 2 in all cases, ruling out multicollinearity concerns. The effects of the different dimensions of working memory on complex comprehension capability were also explored. As auditory capacity showed no significant association with complex comprehension capability, storage capacity (measured by the digit-span task) and dual-task capacity (assessed by the reading-span task) were used as independent variables in the hierarchical regression analysis, while complex comprehension capability was used as the dependent variable. Specifically, the digit-span and reading-span tasks were introduced at Levels 1 and 2, respectively, in Model 4, while the reading-span and digit-span tasks were included at Levels 1 and 2, respectively, in Model 5. Table 4 summarizes the results of the hierarchical regression analysis of complex comprehension based on the different dimensions of working memory. Table 4 Hierarchical regression analysis results of complex comprehension based on different dimensions of working memory (N = 74) R R 2 R 2 change B SE β t Sig. VIF Model 4 Level 1 0.244 0.060 * Digit-span task 0.256 0.120 0.244 2.135 0.036 Level 2 0.321 0.103 * 0.044 Digit-span task 0.157 0.130 0.150 1.215 0.229 1.204 Reading span task 0.519 0.280 0.229 1.875 0.067 1.204 Model 5 Level 1 0.291 0.084 * Reading-span task 0.659 0.256 0.291 2.577 0.012 Level 2 0.321 0.103 * 0.019 Reading-span task 0.519 0.280 0.229 1.857 0.067 1.204 Digit-span task 0.157 0.130 0.150 1.215 0.229 1.204 Note . R , correlation coefficient; R 2 , coefficient of determination; R 2 change, change in the coefficient of determination; B , regression coefficient; SE, standard error; β , standardized regression coefficient; t , statistical value; Sig., significance level; VIF, variance inflation factor; p *** < .001, p ** < .01, p * < .05. Regardless of the variable sequence, the explanatory power of the models remained relatively low ( R 2 = 0.060–0.103), although all models achieved overall statistical significance ( p < .05). Following the separate introduction of the variables to the model, both the storage capacity ( B = 0.256, β = 0.244, p = .036) and dual-task capacity ( B = 0.659, β = 0.291, p = .012) were found to significantly predict complex comprehension capability. However, when the two variables were introduced simultaneously, the predictive effect of the dual-task capacity dropped to being marginally significant ( B = 0.519, β = 0.229, p = .067), and that of the storage capacity was no longer significant ( p > .05). Additionally, the VIF was 1.204, indicating an absence of multicollinearity issues in the models. Discussion The multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners were investigated using a multi-component model and a construction-integration model of working memory. The results demonstrated the significant role of working memory in the reading comprehension of L2 Chinese learners, and revealed complex correlations between the internal dimensions of working memory and reading comprehension levels. It was found that the storage, auditory, and dual-task (representing both storage and processing capacity) capacities of working memory were significantly and positively correlated with simple comprehension capability, while storage and dual-task capacities showed significant positive correlations with complex comprehension capability. Furthermore, the storage, auditory, and dual-task capacities of working memory were independently predictive of simple comprehension capability, while the storage and dual-task capacities independently predicted complex comprehension capability. In terms of both simple and complex reading comprehension, dual-task capacity made the greatest contribution to reading comprehension when all three working-memory capacities are considered together. Contributions of different dimensions of working memory to reading comprehension First, it was found that storage capacity was significantly positively correlated with both dimensions of reading comprehension and demonstrated a significant yet modest predictive effect on reading comprehension. Although several studies employing traditional pure-recall tasks did not identify significant associations between storage capacity and reading comprehension (Dixon et al., 1988 ; Perfetti & Goldman, 1976 ), a meta-analysis conducted by Daneman & Merikle ( 1996 ) revealed that pure-recall tasks primarily measure short-term memory rather than working memory. In the present study, backward digit-span tasks were incorporated alongside traditional forward digit-span tasks to enhance the validity of assessments of storage capacity, which would impose greater demands on the central executive component of working memory. Nevertheless, the predictive power of the storage capacity remained relatively limited. It has been suggested by Alloway ( 2009 ) that numerical materials have low relevance to the semantic processing required for language comprehension, indicating that this task reflects general cognitive resource capacity rather than language-specific processing. Therefore, differences in the methods used for measurement contribute markedly to inconsistencies in the reported correlations and predictive power of storage capacity. Second, auditory capacity had a relatively small but significant effect on simple reading comprehension only. The multi-component model used in this study employed non-word sequence-recognition tasks to provide a comprehensive assessment of the auditory dimension by simultaneous engagement of both storage and processing functions, thereby addressing the limitations of the pure storage tasks (e.g., non-word repetition tasks) used in previous studies (Chun & Payne, 2004 ). The results indicated that the coordinated operation of storage and processing provided foundational support for local information processing even in the auditory dimension, consistent with previous studies (Daneman & Carpenter, 1980 ), which showed that the auditory-span task (which integrates storage and processing) can predict reading comprehension. Nevertheless, the present study observed that auditory capacity had a negligible correlation with complex reading comprehension. This may be because these tasks primarily assess the short-term retention and processing of auditory information, while complex comprehension involves cross-sentence semantic integration and macro-structure construction, placing demands on the central executive that far exceed the localized, sequential processing necessary for auditory tasks. Chun and Payne ( 2004 ) also observed that when the reading of complex literary texts requires higher-order cognitive abilities, phonological memory tasks are poorly associated with comprehension levels. Hence, it can be deduced that while auditory capacity plays a key role in local information processing, its contribution is limited in complex reading tasks that rely on the central executive for deep processing. Third, dual-task capacity was observed to be significantly predictive of reading comprehension, which is consistent with the findings of previous studies (Alloway, 2009 ; Alptekin et al., 2014 ; Seigneuric et al., 2000 ). In the reading-span task used in this study, the participants were required to comprehend the meanings of sentences while memorizing the last word of the sentence, enabling measurement of both the storage and processing capacities of linguistic information. Consequently, the results of the reading-span task are widely regarded as one of the most effective indicators for verbal working memory (Daneman & Carpenter, 1980 ; Juffs & Harrington, 2011 ). Several studies have failed to identify a significant correlation due to issues with the task version used (Hartley, 1986 ; Light & Anderson, 1985 ). Specifically, the first version of the reading-span task did not include a semantic judgment component, with participants only required to read sentences aloud, thus failing to adequately engage the critical processing process. Overall, simultaneous activation of both the storage and processing processes by a measurement task is a key determinant of the effectiveness of the task in predicting reading comprehension. In summary, the different dimensions of working memory vary in their influence on reading comprehension. Factors such as the design, method, and dimensions of the measurement task affect the association between working memory and reading comprehension. Cognitive differences associated with simple and complex reading comprehension The results of this study showed that the effect of dual-task capacity on simple comprehension was significantly greater than that on complex comprehension, which is inconsistent with the findings of some previous studies (Alptekin & Erçetin, 2010 , 2011). From the perspective of the construction-integration theory, this finding suggests that reading comprehension tasks of different levels rely on different processing pathways in working memory as well as different cognitive resources. According to this theory, reading comprehension is a dynamic process composed of two stages, namely, construction and integration. In the construction stage, readers extract information from the text and activate relevant background knowledge, while in the integration stage, irrelevant information is suppressed and semantic connections are established to integrate propositional units into coherent mental representations. Hence, reading tasks of varying complexity essentially involve different processing pathways in working memory and impose varying degrees of cognitive load. Simple comprehension tasks essentially involve the extraction of literal meaning, syntax, and semantic processing, while the cognitive load focuses on temporary maintenance and immediate integration of the local information. This results in a greater reliance on such processing on the storage and processing capacities of working memory, particularly for simultaneous semantic judgment and information integration at the sentence level (Linares & Pelegrina, 2023 ). Additionally, the reading-span tasks required participants to comprehend the meaning of individual sentences while remembering and updating the last word of the sentence. This cognitive demand is highly consistent with that for processing sentences in simple comprehension tasks. Therefore, the reading-span task is more effective in predicting simple comprehension. In contrast, complex comprehension involves integration and inferential capabilities at the level of discourse. Readers are required to integrate propositional information over broader contexts, activate background knowledge, and construct semantic networks, leading to the development of a coherent meaning model of the text by inference. Although such processing also depends on working memory to maintain the intermediate representations, the focus is shifted toward semantic construction and knowledge integration at higher levels instead of immediate retention and manipulation of information (Latini et al., 2021 ). Hence, complex comprehension depends less directly on working memory. Instead, it relies on the background knowledge, reading strategies, and higher-order cognitive capabilities of the readers (Molokopeeva & Simard, 2024 ; Peng et al., 2024 ). In other words, simple comprehension relies primarily on the dual-task “storage + processing” capacity of working memory, while complex comprehension necessitates the engagement of higher-order cognitive capabilities. Conclusions The role of working memory in reading comprehension in L2 Chinese learners was investigated by determining the multi-dimensional associations between working memory and reading comprehension. The results indicated that working memory does not influence reading comprehension singularly or holistically, but instead its internal components exhibit dimension-specific associations with different types of reading tasks. This finding contributes to both theory and practice, enriching the theoretical framework of reading of Chinese as a second language and providing targetable insights for teaching. As both the storage and processing dimensions of working memory can significantly influence reading comprehension, teachers of Chinese should integrate cognitive training of working memory (e.g., strengthening storage capacity, designing tasks that coordinate storage and processing) into their daily teaching schedules, as well as offering specifically graded training for L2 Chinese learners. This study has several limitations. First, the study focused on learners at HSK 3–4 levels, which may present difficulties in generalizing the findings to beginner- or advanced-level learners. Furthermore, the tasks were conducted online, which may have affected the performance of the participants. Also, the investigation did not include comprehensive coverage of all dimensions of working memory and reading comprehension. It is suggested that future studies focus on the following aspects: 1) the moderating role of individual differences in working memory capacity on reading comprehension; 2) analysis of reading comprehension at different levels of understanding (e.g., literal, inferential, and evaluative comprehension); and 3) the application of new methods, such as eye-tracking techniques, to further analyze the cognitive processes of learners, thereby enabling further clarification of the complex mechanisms underlying the function of working memory in reading comprehension of second languages. Declarations Data availability The datasets and materials (Raw data, processed data and test items ) supporting the findings of this study are available for editors and reviewers during peer review. They can be accessed througn Ralated files in the system. Due to the sensitivity of human-participant data and confidentiality commitments, the de-identified data are available under controlled access from the corresponding author upon reasonable request. Competing interests The author(s) declare no competing interests. Ethical statements The study was conducted in accordance with the Declaration of Helsinki. Ethical approval for this study was granted by the Ethics Committee of [Name of Institution Redacted] on December 12, 2022 (Approval No. [Redacted]). Informed consent Consent was obtained electronically from the participants prior to the commencement of the study (between January and February 2024). Participants were assured of their anonymity and right to withdraw from the study at any time. Author contributions Author 1 contributed to the study conception, design, data analysis, and drafting and revision of all versions of the manuscript. Author 2 contributed to the study conception, design, data analysis, and drafting and revision of all versions of the manuscript. Author 3 contributed to the study conception, design, data analysis, and drafting of the initial manuscript. Author 4 contributed to the study conception, design, data curation, and revision of all versions of the manuscript. All authors have read and approved the final manuscript. References Alptekin C, Erçetin G (2010) The role of L1 and L2 working memory in literal and inferential comprehension in L2 reading. J Res Reading 33(2):206–219 Alptekin C, Ercetin G (2011) Effects of working memory capacity and content familiarity on literal and inferential comprehension in L2 reading. TESOL Q 45(2):235–266 Alptekin C, Erçetin G, Özemir O (2014) Effects of variations in reading span task design on the relationship between working memory capacity and second language reading. Mod Lang J 98(2):536–552 Alloway TP (2009) Working memory, but not IQ, predicts subsequent learning in children with learning difficulties. Eur J Psychol Assess 25(2):1–10 Baddeley AD (2000) The episodic buffer: A new component of working memory? Trends Cogn Sci 4(11):417–423 Baddeley AD, Hitch G (1974) Working memory. In: Bower GH (ed) The psychology of learning and motivation: Advances in research and theory, vol 8. Academic, pp 47–89 Barrouillet P, Camos V (2012) As time goes by: Temporal constraints in working memory. Curr Dir Psychol Sci 21(6):413–419 Bayliss DM, Jarrold C, Gunn DM, Baddeley AD (2003) The complexities of complex span: Explaining individual differences in working memory in children and adults. J Exp Psychol Gen 132(1):71–92 Chen B, Xu H (2010) Differences in working memory capacity: Influences on the processing of syntactic ambiguous sentences in second language. 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J Educ Psychol 80(4):465–472 Grabe W, Jiang X (2018) First language and second language reading. In: Liontas JI (ed) The TESOL encyclopedia of English language teaching. Wiley Gathercole SE, Pickering SJ, Hall M, Peaker SM (2001) Dissociable lexical and phonological influences on serial recognition and serial recall. Q J Experimental Psychol Sect A: Hum Experimental Psychol 54(1):1–30 Hao M, Sun Z, Cao J (2020) The development of reading comprehension in Chinese as a second language from the perspective of the Simple View of Reading. J Chin Lang Stud (in Chinese), (2), 9–20 Hartley JT (1986) Reader and text variables as determinants of discourse memory in adulthood. Psychol Aging 1(2):150–158 Harrington M, Sawyer M (1992) L2 working memory capacity and L2 reading skill. Stud Second Lang Acquisition 14(1):25–38 Jeon E, Yamashita J (2014) L2 reading comprehension and its correlates: A meta-analysis. Lang Learn 64(1):160–212 Juffs A, Harrington M (2011) Aspects of working memory in L2 learning. Lang Teach 44(2):137–166 Just MA, Carpenter PA (1992) A capacity theory of comprehension: Individual differences in working memory. Psychol Rev 99(1):122–149 Kintsch W (1988) The role of knowledge in discourse comprehension: A construction-integration model. Psychol Rev 95(2):163–182 Kintsch W (2018) Revisiting the construction–integration model of text comprehension and its implications for instruction. In: Alvermann DE, Unrau NJ, Sailors M, Ruddell RB (eds) Theoretical models and processes of literacy, 7th edn. Routledge, pp 178–203 Kintsch W, van Dijk TA (1978) Toward a model of text comprehension and production. Psychol Rev 85(5):363–394 Kline RB (2015) Principles and practice of structural equation modeling, 3rd edn. Guilford Press. (Methodology in the Social Sciences Series) Latini N, Bråten I, Haverkamp YE (2021) Breadth and depth of strategic processing during text comprehension. Learn Individual Differences 91:102058 Lépine R, Barrouillet P, Camos V (2005) What makes working memory spans so predictive of high-level cognition? Psychon Bull Rev 12(1):165–170 Light LL, Anderson PA (1985) Working-memory capacity, age, and memory for discourse. J Gerontol 40(6):737–747 Linares R, Pelegrina S (2023) The relationship between working memory updating components and reading comprehension. Cogn Process 24:253–265 Nouwens S, Groen MA, Verhoeven L (2016) How storage and executive functions contribute to children's reading comprehension. Learn Individual Differences 47:96–102 Peng P, Wang W, Filderman MJ, Zhang W, Lin L (2024) The active ingredient in reading comprehension strategy intervention for struggling readers: A Bayesian network meta-analysis. Rev Educ Res 94(2):228–267 Perfetti CA, Goldman SR (1976) Discourse memory and reading comprehension skill. J Verbal Learn Verbal Behav 14(1):33–42 Seigneuric A, Ehrlich M-F, Oakhill JV, Yuill NM (2000) Working memory resources and children's reading comprehension. Read Writ 13(1):81–103 Service E, Simola M, Metsänheimo O, Maury S (2002) Bilingual working memory span is affected by language skill. Eur J Cogn Psychol 14(3):383–407 Simard D, Molokopeeva T (2024) Interaction between levels of text representation and working memory during L2 reading comprehension: What about it? Int J Appl Linguistics 34(2):568–585 Streitberger C, Kuhlmann BG, Meier ME, Arnold NR (2024) Connecting working and long-term memory: Bayesian‐hierarchical multinomial model‐based analyses reveal storage next to retrieval differences. Mem Cognit 52:1915–1927 Unsworth N, Redick TS, Heitz RP, Broadway JM, Engle RW (2009) Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage. Memory 17(6):635–654 Unsworth N, Engle RW (2006) Simple and complex memory spans and their relation to fluid abilities: Evidence from list-length effects. J Mem Lang 54(1):68–80 Van Dyke JA, Johns CL, Kukona A (2014) Low working memory capacity is only spuriously related to poor reading comprehension. Cognition 131(3):373–403 Waters G, Caplan D (2004) Verbal working memory and on-line syntactic processing: Evidence from self-paced listening. Q J Experimental Psychol Sect A 57(1):139–163 Zhang H (2021) The application of effect size in studies on international Chinese education. Chinese Lang Globalization Studies (in Chinese) 12:39–49 Zhu W, Cheng L, Chen T (2018) A study on the relationship between homographic morpheme awareness, word meaning inference, and reading comprehension among elementary Chinese learners. Chinese Teaching in the World . (in Chinese) 32(2):270–279 Footnotes The second sub-question of Item 1 was removed because the pilot task revealed that all participants answered it incorrectly, with inconsistent error patterns. Post-task interviews indicated that the item was ambiguous; therefore, it was excluded from the formal experiment. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9026197","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":615361092,"identity":"1fc82875-b326-456e-91b8-0c0e095bfccf","order_by":0,"name":"Tianxu Chen","email":"","orcid":"","institution":"Minzu University of China","correspondingAuthor":false,"prefix":"","firstName":"Tianxu","middleName":"","lastName":"Chen","suffix":""},{"id":615361093,"identity":"728d15f4-1e2e-41de-a825-7e6591c140f1","order_by":1,"name":"Ruohan Su","email":"","orcid":"","institution":"Minzu University of China","correspondingAuthor":false,"prefix":"","firstName":"Ruohan","middleName":"","lastName":"Su","suffix":""},{"id":615361094,"identity":"9a8cbad4-ebe2-4b46-b087-a484a995d6fb","order_by":2,"name":"Mengyue Wang","email":"","orcid":"","institution":"Minzu University of China","correspondingAuthor":false,"prefix":"","firstName":"Mengyue","middleName":"","lastName":"Wang","suffix":""},{"id":615361095,"identity":"f6fb3ced-3d35-4746-87de-ffaaf5f99dfe","order_by":3,"name":"Qing Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACfvbGhgMfDP7JQbhsRGiR7Dl88OGMigPGxGsxuJGWbMxz5kBiAwlacswkZ7bdSV87I/kBw4eywwz8sxsIOOzMGzOJj23PcrfdSDNgnHHuMIPEnQP4tfAdB9vCDNSSw8DM23aYwUAigYDLDuSYSfO2MaebgbT8JUaLwAmw9w8ngLUwEqMFGshphtvOPDM42HMunUfiBgEt0Ki0kTc7nvzwwY8yazn+GYT8ggwOADEPCepHwSgYBaNgFOACAOoFTQxHA26XAAAAAElFTkSuQmCC","orcid":"","institution":"Minzu University of China","correspondingAuthor":true,"prefix":"","firstName":"Qing","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2026-03-04 05:54:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9026197/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9026197/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106094005,"identity":"a38085e9-44fc-42a3-8939-22fc7fab691c","added_by":"auto","created_at":"2026-04-03 11:40:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":966499,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9026197/v1/05597104-0d70-4bc3-a846-d303a00eeaec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners","fulltext":[{"header":"Introduction","content":"\u003cp\u003eReading comprehension is a complex cognitive process in which learners construct meaning from text (Hao et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this process, learners continuously associate current active information in working memory with subsequent content to construct coherent mental representations (Kintsch, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Working memory represents a cognitive hub that connects word recognition with overall semantic construction, and is therefore key to predicting the reading comprehension of individuals. This concept has received widespread support from numerous studies of first language (L1) reading (Daneman \u0026amp; Carpenter, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Kintsch \u0026amp; van Dijk, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Nouwens et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile L2 reading is subject to a wider range of variables than L1 reading (e.g., language proficiency, L1 background, and cultural differences), there is no doubt that working memory plays an indispensable role. Indeed, the core cognitive processes associated with reading are common to both L1 and L2 reading, and involve the extraction of basic information and the integration of complex meaning (Grabe \u0026amp; Jiang, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Working memory has been consistently found to be positively correlated with L2 reading comprehension (Alptekin \u0026amp; Er\u0026ccedil;etin, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Jeon \u0026amp; Yamashita, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Service et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, the reported correlation coefficients vary considerably among different studies, and some studies have even questioned the existence of such a correlation (Van Dyke et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These discrepancies suggest that the relationship between working memory and L2 reading may be multi-dimensional and complex. However, experimental evidence on this topic remains limited, and a consensus has yet to be reached.\u003c/p\u003e \u003cp\u003eTo clarify the multi-dimensional associations between working memory and reading comprehension, this study defines the two concepts first. Working memory is a system responsible for information storage and processing during cognitive tasks (Baddeley \u0026amp; Hitch, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), and is limited by its capacity for handling information. Various theoretical models of working memory have been suggested, among which the multi-component model proposed by Baddeley et al. (2000) is noteworthy due to its strong explanatory power and ability to be continuously refined. It describes a dynamic cognitive structure with the central executive at the core. The model contains a series of relatively independent subsystems, including the phonological loop, the visuospatial sketchpad, and the subsequently included episodic buffer. The central executive, as the hub of attentional control, coordinates cognitive resources, regulates attention, and interacts with long-term memory. The phonological and visuospatial subsystems are specialized for the temporary storage and preliminary processing of auditory-verbal and visual-spatial information, respectively. Therefore, working memory is a complex concept that includes multiple dimensions from the perspectives of structural components (e.g., the phonological loop and visuospatial sketchpad) and internal functions (e.g., storage, processing).\u003c/p\u003e \u003cp\u003eReading comprehension resembles working memory in its hierarchical and complex capabilities. The construction-integration model proposed by Kintsch (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) provides a theoretical framework for understanding this hierarchy. This model conceptualizes reading comprehension as a dynamic process consisting of two stages, namely, construction and integration. Specifically, the construction stage primarily involves the activation of lexical semantics and formation of the textbase; it relies primarily on both basic storage and local processing. In contrast, the integration stage represents a highly active and resource-intensive process involving the integration of new information with prior knowledge, suppression of irrelevant interference, logical inference, and the development of a coherent situational model or macrostructure. In this study, reading comprehension was operationalized as \u0026ldquo;simple\u0026rdquo; and \u0026ldquo;complex\u0026rdquo; comprehension based on this model. \u0026ldquo;Simple comprehension\u0026rdquo; essentially corresponds to the construction stage, associated with low resource demands, while \u0026ldquo;complex comprehension\u0026rdquo; corresponds to the integration stage, involving high demands on cognitive resources. As different levels of reading comprehension differ in terms of cognitive load and degree of activation, the relative participation and contributions of the different components of working memory also differ among these hierarchical tasks.\u003c/p\u003e \u003cp\u003eHowever, most previous studies have not differentiated precisely between these inherent hierarchical stages at the operational level. When the question is narrowed to how the \u0026ldquo;specific dimensions\u0026rdquo; of working memory are linked to the \u0026ldquo;particular level\u0026rdquo; of reading comprehension, conclusions become inconsistent, if not contradictory.\u003c/p\u003e \u003cp\u003eFirst, conclusions differ according to whether the \u0026ldquo;internal functional dimensions\u0026rdquo; (storage, processing) of working memory were analyzed separately or comprehensively. Several studies have emphasized the central role of the processing function. For instance, Chen and Xu (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), using eye-tracking measurements, found that during the processing of ambiguous sentences in the second language, the processing dimension, rather than the storage dimension, of working memory predominated. Likewise, Alptekin and Er\u0026ccedil;etin (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) reported that in second-language reading, only the processing dimension of working memory was significantly associated with the degree of reading comprehension. Nevertheless, other studies have argued that the storage function is equally indispensable. For example, both Bayliss et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and Unsworth et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) demonstrated that the storage dimension could significantly predict reading comprehension scores even after statistically controlling for the influences of the processing component.\u003c/p\u003e \u003cp\u003eIn terms of the separate measurement approaches mentioned above, there are two explanations for the differences in opinion. First, although the storage component of working memory can be measured separately in operational tasks (e.g., digit span tasks) (Bayliss et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), the processing component cannot. This is essentially due to the reliance of all processing tasks involving language (including reading comprehension) on the successful maintenance and temporary storage of information (Daneman \u0026amp; Merikle, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Streitberger et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Consequently, attempting to measure the processing component without considering the storage component suffers from theoretical limitations and questionable validity. Second, some researchers have claimed that working memory essentially involves the simultaneous maintenance and processing of information under conditions of limited cognitive resources (Barrouillet \u0026amp; Camos, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Therefore, the measurement of either storage or processing in isolation cannot predict complex cognitive activities such as reading comprehension. For this reason, it is believed that only dual-task paradigms measuring both storage and processing (e.g., reading span tasks) represent predictors with high ecological validity (L\u0026eacute;pine et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Unsworth \u0026amp; Engle, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere are also marked discrepancies between the conclusions of studies on the \u0026ldquo;component dimension\u0026rdquo; (phonological, visuospatial) of working memory. Most previous studies employing auditory span tasks have supported the ability of the auditory-phonological dimension of working memory to predict reading comprehension (Daneman \u0026amp; Carpenter, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). In contrast, studies using visuospatial tasks of working memory demonstrated only a weak correlation between the auditory-phonological dimension of working memory and reading comprehension (Daneman \u0026amp; Tardiff, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Seigneuric et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, there is a general lack of unified standards for both the selection of text materials and methods for the assessment of reading comprehension. Some studies have evaluated reading comprehension in terms of sentence-level processing skills, including grammatical judgment and semantic processing (Just \u0026amp; Carpenter, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Waters \u0026amp; Caplan, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), while others have used self-adapted materials with varying criteria and standards (Chun \u0026amp; Payne, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Overall, few previous studies have considered multi-dimensionality in the design and measurement of reading comprehension. This presents significant difficulties for the direct comparison of the results of different studies, and the relationships between various dimensions of working memory and reading comprehension remain to be confirmed.\u003c/p\u003e \u003cp\u003eIn this study, the specific associations between different dimensions of working memory and reading comprehension in L2 Chinese learners were investigated using an experimental approach. At the working-memory level, we focused on the core functional dimensions (storage and processing), paying particular attention to the auditory-phonological dimension that is closely linked to language processing. Reading comprehension was stratified into two hierarchical levels: simple comprehension (construction stage) and complex comprehension (integration stage). Therefore, this study aims to address the following research questions:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRQ1\u003c/strong\u003e \u003cp\u003eAre there significant correlations between the dimensions of working memory and the different levels of reading comprehension in L2 Chinese learners?\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ2\u003c/b\u003e: If so, to what extent do working memory dimensions predict learners' performance in simple versus complex reading comprehension?\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 78 intermediate-level native English speakers who were learning Chinese as a second language were enrolled. Of these, 74 completed all tasks as required, resulting in a valid response rate of 95%. Twenty-three of the 74 participants were male, and 51 were female, with an overall average age of 25. All participants had passed Hanyu Shuiping Kaoshi (HSK, a national, standardized test measuring Chinese profciency) Level 3, while 39 had passed HSK Level 4. All participants had normal or corrected-to-normal vision, possessed basic computer operational skills, and provided written informed consent before the start of the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTasks\u003c/h3\u003e\n\u003cp\u003eThe tasks used in the study were all validated and demonstrated good reliability. The tasks were administered using Gorilla Experimenter Builder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gorilla.sc\u003c/span\u003e\u003cspan address=\"http://gorilla.sc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a professional online experimental platform, to ensure procedural standardization and consistency. All tasks underwent and passed prior pilot testing to confirm appropriate difficulty and length.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDigit span task.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe storage dimension (i.e., storage capacity) of the working memory of the participants was assessed using the digit span task (Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This task comprised forward and backward digit span tasks. The task required the participants to recall a series of progressively longer sequences of digits in either the original or reversed order. Fourteen sequences were included in total, and each correctly recalled sequence scored 1 point. The task took approximately 4 min to complete. The reliability of the task across all items was acceptable (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.723).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExample\u003c/strong\u003e \u003cp\u003e836; 9275; 37928; 254673; 2683048; 52864934; 372840823 (forward)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e482; 1736; 50127; 379145; 6992643; 24953928; 482638127 (backward)\u003c/p\u003e \u003cp\u003e \u003cb\u003ePhonological short-term memory task.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe auditory dimension of working memory was measured by recognition of non-word sequences (Gathercole et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), enabling assessment of an individual\u0026rsquo;s ability to temporarily store and activate auditory information in memory (representing the \u0026ldquo;auditory capacity\u0026rdquo;). First, the participants listened to a list of pseudowords that conformed to English phonotactic rules but were meaningless. They then listened to a second list and were required to judge whether the order of the pseudowords was identical in the two lists. A practice trial was conducted before the formal task to enable the participants to familiarize themselves with the task. Correct responses scored 1 point, while incorrect or omitted responses scored 0 points. The duration of the task was approximately 13 min. The reliability of the task across all items was acceptable (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.720).\u003c/p\u003e \u003cp\u003e Specifically, according to the multi-component model, the phonological loop is a subsystem that integrates both storage and processing functions. The storage function is reflected by brief retention of phonological information, while processing involves the reactivation of fading phonological representations. Most tasks involving the repetition of non-words (Chun \u0026amp; Payne, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) primarily assess the storage capacity and do not reflect the processing function. Therefore, this study used a phonological short-term memory task that incorporated a word sequence-recognition task. This engaged both storage and processing functions simultaneously, thereby enabling a comprehensive evaluation of the auditory dimension. To avoid potential homogeneity issues arising from the use of auditory span and reading span tasks with similar formats, we used the \u0026ldquo;non-word sequence recognition task\u0026rdquo; for measuring the auditory dimension of working memory. Additionally, pseudowords, instead of real words, were used to eliminate the influence of existing lexical knowledge on the task performance, thereby providing an effective measurement of the core functions of the phonological loop (Chun \u0026amp; Payne, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExample\u003c/strong\u003e \u003cp\u003eGroup 1 (Same)\u003c/p\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: marl; coll; pab; meb\u003c/p\u003e \u003cp\u003eTask Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: marl; coll; pab; meb\u003c/p\u003e \u003cp\u003eGroup 2 (Different)\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: cark; mup; gop; norb; jooch\u003c/p\u003e \u003cp\u003eTask Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: mup; cark; jooch; norb; gop\u003c/p\u003e \u003cp\u003e \u003cb\u003eReading span task.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe storage and processing dimensions of working memory (described as \u0026ldquo;dual-task capacity\u0026rdquo;) were assessed using a modified reading span task (Daneman \u0026amp; Carpenter, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), this is currently the most widely used task for working memory. The participants followed a dual-task paradigm, in which they were first required to judge, within a time limit, whether a presented sentence was semantically plausible. Then, after completing a set of sentences (between 2 and 5 sentences), they were asked to recall the final word of each sentence in the correct order. The task materials consisted of four groups, each of which contained three sets of sentences. There were two sentences in the first group (six sentences in total), while the second group contained sets of three sentences (nine sentences in total), the third group had sets of four sentences (12 sentences in total), and the fourth group had sets of five sentences (15 sentences in total). Overall, the task comprised 42 semantically unrelated sentences, half of which were semantically plausible and half were not. All sentences were 10\u0026ndash;13 words in length and ended with different words. There were no semantic or phonological similarities between the last words of sentences in different sentence groups or within the same group.\u003c/p\u003e \u003cp\u003ePractice trials were provided for the participants before they undertook the formal tasks. In the semantic judgment task, each correct response scored 1 point, while incorrect or omitted responses scored 0 points. In the final word-recall task, each correctly recalled word in the correct order scored 1 point, an incorrect or omitted response scored 0 points, and a correct word but in the wrong order scored 0.5 points. The maximum score was 84 points, and the task took approximately 13 min. The reliability of the task across all items was acceptable (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.733).\u003c/p\u003e \u003cp\u003eNotably, while previous studies have varied in their use of L1 or L2, evidence suggests a positive correlation between working memory in both languages (Alptekin et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). To minimize potential confounds related to L2 proficiency and language transfer, we conducted the semantic judgment task in the participants' L1. The reading materials were sourced from Harrington and Sawyer (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExample (Group 1, Set 1):\u003c/p\u003e \u003cp\u003e① Semantic judging:\u003c/p\u003e \u003cp\u003eAt night, the prisoners danced through a hole in the wall. (unreasonable)\u003c/p\u003e \u003cp\u003eThe young woman and her boyfriend thought they saw a dog. (reasonable)\u003c/p\u003e \u003cp\u003e② Recall the last word:\u003c/p\u003e \u003cp\u003eWall; dog\u003c/p\u003e \u003cp\u003e \u003cb\u003eReading comprehension task.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConsidering the Chinese proficiency levels of the participants, the text materials for the reading comprehension task used in this study were retrieved from 11 sets of authentic HSK Level 4 past year papers (H40000, H41001\u0026ndash;H41009, H41110, H41111). The questions were divided into two dimensions: simple and complex comprehension.\u003c/p\u003e \u003cp\u003eTen questions for the simple comprehension dimension were obtained from items 66‒79 of the above papers. Each question consisted of 1‒3 sentences, with character counts ranging from 20 to 80. The total score for this section was 10 points, with 1 point awarded for each correct answer and 0 points for incorrect or unanswered questions. The duration of the task was approximately 10 min. The reliability of the task across all items was acceptable (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.644).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExample\u003c/strong\u003e \u003cp\u003e我们有两只耳朵, 一个嘴, 应该多听少说.(We have two ears and one mouth, so we should listen more and speak less.)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e问题: 这段话告诉我们:(Question: This tells us that:)\u003c/p\u003e \u003cp\u003eA 要多听别人说(We should listen more to what others say)\u003c/p\u003e \u003cp\u003eB 要准时发言(We should speak on time)\u003c/p\u003e \u003cp\u003eC 要多表扬别人(We should praise others more)\u003c/p\u003e \u003cp\u003eD 要严格要求自己(We should be strict with ourselves)\u003c/p\u003e \u003cp\u003eFive questions for the complex comprehension dimension were retrieved from items 80‒85. Each question consisted of two sub-questions, resulting in a total of nine items[1]. These items contained five‒eight sentences, with total character counts ranging from 150 to 200. The maximum score for this section was nine points, with 1 point awarded for each correct answer and 0 points for incorrect or unanswered items. The duration of the task was approximately 10 min. The reliability of the task across all items was acceptable (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.649).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExample\u003c/strong\u003e \u003cp\u003e(The task was originally in Chinese, and we translated it into English for the convenience of readers.)\u003c/p\u003e \u003c/p\u003e \u003cp\u003eScientific studies have demonstrated that colors can influence one\u0026rsquo;s mood, and different colors can evoke different emotions. For instance, red can make people feel passionate and excited; yellow and white tend to induce a cheerful and happy mood; black, however, can easily make people feel sad; when people see blue, they often feel comfortable and become calm; green allows our eyes to rest and is also beneficial to our health.\u003c/p\u003e \u003cp\u003e(1) According to the paragraph, which color makes people feel upset?\u003c/p\u003e \u003cp\u003eA. White; B. Black; C. Yellow; D. Blue.\u003c/p\u003e \u003cp\u003e(2) This paragraph discusses:\u003c/p\u003e \u003cp\u003eA. The differences between colors; B. Stories about colors;\u003c/p\u003e\u003cp\u003eC. The benefits of colors for the eyes; D. The relationship between colors and mood.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study utilized a 3\u0026times;2 within-subjects design accompanied by online tasking of the participants. After completion of the tasks, the overall scores of the participants were recorded. SPSS 27.0 was used for all analyses, including descriptive statistics, correlation analysis, and hierarchical regression analysis, to explore the multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners.\u003c/p\u003e \u003cp\u003eThe scores from all tasks were standardized by dividing the original score by the corresponding total number of items, and these standardized scores were used for subsequent statistical analyses. Theoretically, the score on a task was proportional to the learner\u0026rsquo;s performance in terms of that specific capability. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the descriptive statistics of the various tasks.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDescriptive statistics (N\u0026thinsp;=\u0026thinsp;74)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of questions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span task (storage capacity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhonological short-term memory task (auditory capacity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task (dual-task capacity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimple comprehension task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplex comprehension task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCorrelation analysis\u003c/h3\u003e\n\u003cp\u003eFollowing Kline (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), we adopted the criteria that absolute values exceeding 3.0 for skewness (SI) and 10.0 for kurtosis (KI) indicate severe non-normality. Inspection of the data showed that all variables were well within these limits; therefore, no significant violations of normality were observed.\u003c/p\u003e \u003cp\u003ePearson correlation analysis was conducted on the task results to answer Research Question 1 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results showed that the storage, auditory, and dual-task capacities in working memory were significantly positively correlated with simple comprehension capability, while the storage and dual-task capacities in working memory were significantly positively associated with complex comprehension capability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eResults of Pearson correlation analysis (N\u0026thinsp;=\u0026thinsp;74)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1. Digit span task (storage capacity)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Phonological short-term memory task (auditory capacity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.501\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Reading span task (dual-task capacity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.412\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Simple comprehension task (simple comprehension capability)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.307\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.273\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.454\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Complex comprehension task (complex comprehension capability)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.244\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.291\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.414\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e \u0026lt; .001, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e \u0026lt; .01, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e \u0026lt; .05. All tasks were two-tailed.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the correlation analysis, the effect size represents the strength of the correlations between different variables (Zhang, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cohen (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) reported that the small, medium, and large effect sizes correspond to \u003cem\u003er\u003c/em\u003e values of approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1, \u0026plusmn;\u0026thinsp;0.3, and \u0026plusmn;\u0026thinsp;0.5, respectively. In this study, a moderate positive correlation was observed between the storage capacity of working memory and simple comprehension capability, with a weaker correlation between the storage capacity of working memory and complex comprehension capability. Furthermore, the auditory capacity of working memory showed a moderate positive association with simple comprehension capability. Additionally, a significant association was found between the dual-task capacity of working memory and simple comprehension capability, together with a moderate positive correlation between dual-task capacity and complex comprehension capability. Overall, dual-task capacity was most strongly associated with reading comprehension.\u003c/p\u003e\n\u003ch3\u003eHierarchical regression analysis\u003c/h3\u003e\n\u003cp\u003eHierarchical regression analysis was conducted using simple and complex comprehension capabilities as dependent variables to answer Research Question 2. The effects of different dimensions of working memory on simple comprehension capability were investigated. At Level 1, the digit-span, phonological short-term memory, and reading-span tasks were incorporated in the model, followed by the subsequent introduction of the other two tasks. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the results of the hierarchical regression prediction of simple comprehension capability based on the different dimensions of working memory.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eHierarchical regression prediction of simple comprehension capability based on different dimensions of working memory (N\u0026thinsp;=\u0026thinsp;74)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 1\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.094\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhonological short-term memory task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.207\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.113\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhonological short-term memory task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.243\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.169\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhonological short-term memory task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.224\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1/2/3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.246\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhonological short-term memory task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eR\u003c/em\u003e, correlation coefficient; \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, coefficient of determination; \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e change, change in the coefficient of determination; \u003cem\u003eB\u003c/em\u003e, regression coefficient; SE, standard error; \u003cem\u003eβ\u003c/em\u003e, standardized regression coefficient; \u003cem\u003et\u003c/em\u003e, statistical value; Sig., significance level; VIF, variance inflation factor; \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e \u0026lt; .001, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e \u0026lt; .01, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e \u0026lt; .05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt Level 1, storage capacity (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.220, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.307, \u003cem\u003ep\u003c/em\u003e \u0026lt; .01), auditory capacity (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.238, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.273, \u003cem\u003ep\u003c/em\u003e \u0026lt; .05), and dual-task capacity (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.706, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.454, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) were found to be significantly predictive of simple comprehension capability. At Level 2, with the other dimensions controlled, the inclusion of the phonological short-term memory task did not significantly enhance the explanatory power of Model 1 (Δ\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.019, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05), while the introduction of the reading-span task significantly improved the explanatory power of Model 2 (Δ\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.169, \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.649, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.418, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), suggesting that dual-task capacity was an independent predictor of simple comprehension capability. Model 3 verified this conclusion, demonstrating that dual-task capacity significantly predicted simple comprehension capability even if the storage capacity was controlled (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.614, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.395, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), with a 1.7% increase in the explanation rate of the model. At Level 3, the explanatory power of the model was \u003cem\u003eR\u003c/em\u003e\u0026sup2; = 0.246 (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), with the predictive effect of dual-task capacity remaining significant (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.620, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.400, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), while the predictive effects of the other two capacities were no longer significant (storage capacity: \u003cem\u003ep\u003c/em\u003e = .663; auditory capacity: \u003cem\u003ep\u003c/em\u003e = .160). The variance inflation factor (VIF) was below 2 in all cases, ruling out multicollinearity concerns.\u003c/p\u003e \u003cp\u003eThe effects of the different dimensions of working memory on complex comprehension capability were also explored. As auditory capacity showed no significant association with complex comprehension capability, storage capacity (measured by the digit-span task) and dual-task capacity (assessed by the reading-span task) were used as independent variables in the hierarchical regression analysis, while complex comprehension capability was used as the dependent variable. Specifically, the digit-span and reading-span tasks were introduced at Levels 1 and 2, respectively, in Model 4, while the reading-span and digit-span tasks were included at Levels 1 and 2, respectively, in Model 5. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the results of the hierarchical regression analysis of complex comprehension based on the different dimensions of working memory.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eHierarchical regression analysis results of complex comprehension based on different dimensions of working memory (N\u0026thinsp;=\u0026thinsp;74)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 4\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.060\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit-span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit-span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.084\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading-span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading-span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit-span task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eR\u003c/em\u003e, correlation coefficient; \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, coefficient of determination; \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e change, change in the coefficient of determination; \u003cem\u003eB\u003c/em\u003e, regression coefficient; SE, standard error; \u003cem\u003eβ\u003c/em\u003e, standardized regression coefficient; \u003cem\u003et\u003c/em\u003e, statistical value; Sig., significance level; VIF, variance inflation factor; \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e***\u003c/em\u003e\u003c/sup\u003e \u0026lt; .001, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e \u0026lt; .01, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e \u0026lt; .05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegardless of the variable sequence, the explanatory power of the models remained relatively low (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.060\u0026ndash;0.103), although all models achieved overall statistical significance (\u003cem\u003ep\u003c/em\u003e \u0026lt; .05). Following the separate introduction of the variables to the model, both the storage capacity (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.256, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.244, \u003cem\u003ep\u003c/em\u003e = .036) and dual-task capacity (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.659, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.291, \u003cem\u003ep\u003c/em\u003e = .012) were found to significantly predict complex comprehension capability. However, when the two variables were introduced simultaneously, the predictive effect of the dual-task capacity dropped to being marginally significant (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.519, \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.229, \u003cem\u003ep\u003c/em\u003e = .067), and that of the storage capacity was no longer significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). Additionally, the VIF was 1.204, indicating an absence of multicollinearity issues in the models.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners were investigated using a multi-component model and a construction-integration model of working memory. The results demonstrated the significant role of working memory in the reading comprehension of L2 Chinese learners, and revealed complex correlations between the internal dimensions of working memory and reading comprehension levels. It was found that the storage, auditory, and dual-task (representing both storage and processing capacity) capacities of working memory were significantly and positively correlated with simple comprehension capability, while storage and dual-task capacities showed significant positive correlations with complex comprehension capability. Furthermore, the storage, auditory, and dual-task capacities of working memory were independently predictive of simple comprehension capability, while the storage and dual-task capacities independently predicted complex comprehension capability. In terms of both simple and complex reading comprehension, dual-task capacity made the greatest contribution to reading comprehension when all three working-memory capacities are considered together.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eContributions of different dimensions of working memory to reading comprehension\u003c/h2\u003e \u003cp\u003eFirst, it was found that storage capacity was significantly positively correlated with both dimensions of reading comprehension and demonstrated a significant yet modest predictive effect on reading comprehension. Although several studies employing traditional pure-recall tasks did not identify significant associations between storage capacity and reading comprehension (Dixon et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Perfetti \u0026amp; Goldman, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1976\u003c/span\u003e), a meta-analysis conducted by Daneman \u0026amp; Merikle (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) revealed that pure-recall tasks primarily measure short-term memory rather than working memory. In the present study, backward digit-span tasks were incorporated alongside traditional forward digit-span tasks to enhance the validity of assessments of storage capacity, which would impose greater demands on the central executive component of working memory. Nevertheless, the predictive power of the storage capacity remained relatively limited. It has been suggested by Alloway (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) that numerical materials have low relevance to the semantic processing required for language comprehension, indicating that this task reflects general cognitive resource capacity rather than language-specific processing. Therefore, differences in the methods used for measurement contribute markedly to inconsistencies in the reported correlations and predictive power of storage capacity.\u003c/p\u003e \u003cp\u003eSecond, auditory capacity had a relatively small but significant effect on simple reading comprehension only. The multi-component model used in this study employed non-word sequence-recognition tasks to provide a comprehensive assessment of the auditory dimension by simultaneous engagement of both storage and processing functions, thereby addressing the limitations of the pure storage tasks (e.g., non-word repetition tasks) used in previous studies (Chun \u0026amp; Payne, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The results indicated that the coordinated operation of storage and processing provided foundational support for local information processing even in the auditory dimension, consistent with previous studies (Daneman \u0026amp; Carpenter, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), which showed that the auditory-span task (which integrates storage and processing) can predict reading comprehension. Nevertheless, the present study observed that auditory capacity had a negligible correlation with complex reading comprehension. This may be because these tasks primarily assess the short-term retention and processing of auditory information, while complex comprehension involves cross-sentence semantic integration and macro-structure construction, placing demands on the central executive that far exceed the localized, sequential processing necessary for auditory tasks. Chun and Payne (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) also observed that when the reading of complex literary texts requires higher-order cognitive abilities, phonological memory tasks are poorly associated with comprehension levels. Hence, it can be deduced that while auditory capacity plays a key role in local information processing, its contribution is limited in complex reading tasks that rely on the central executive for deep processing.\u003c/p\u003e \u003cp\u003eThird, dual-task capacity was observed to be significantly predictive of reading comprehension, which is consistent with the findings of previous studies (Alloway, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Alptekin et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Seigneuric et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In the reading-span task used in this study, the participants were required to comprehend the meanings of sentences while memorizing the last word of the sentence, enabling measurement of both the storage and processing capacities of linguistic information. Consequently, the results of the reading-span task are widely regarded as one of the most effective indicators for verbal working memory (Daneman \u0026amp; Carpenter, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Juffs \u0026amp; Harrington, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Several studies have failed to identify a significant correlation due to issues with the task version used (Hartley, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Light \u0026amp; Anderson, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Specifically, the first version of the reading-span task did not include a semantic judgment component, with participants only required to read sentences aloud, thus failing to adequately engage the critical processing process. Overall, simultaneous activation of both the storage and processing processes by a measurement task is a key determinant of the effectiveness of the task in predicting reading comprehension.\u003c/p\u003e \u003cp\u003eIn summary, the different dimensions of working memory vary in their influence on reading comprehension. Factors such as the design, method, and dimensions of the measurement task affect the association between working memory and reading comprehension.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCognitive differences associated with simple and complex reading comprehension\u003c/h2\u003e \u003cp\u003eThe results of this study showed that the effect of dual-task capacity on simple comprehension was significantly greater than that on complex comprehension, which is inconsistent with the findings of some previous studies (Alptekin \u0026amp; Er\u0026ccedil;etin, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, 2011). From the perspective of the construction-integration theory, this finding suggests that reading comprehension tasks of different levels rely on different processing pathways in working memory as well as different cognitive resources. According to this theory, reading comprehension is a dynamic process composed of two stages, namely, construction and integration. In the construction stage, readers extract information from the text and activate relevant background knowledge, while in the integration stage, irrelevant information is suppressed and semantic connections are established to integrate propositional units into coherent mental representations. Hence, reading tasks of varying complexity essentially involve different processing pathways in working memory and impose varying degrees of cognitive load.\u003c/p\u003e \u003cp\u003eSimple comprehension tasks essentially involve the extraction of literal meaning, syntax, and semantic processing, while the cognitive load focuses on temporary maintenance and immediate integration of the local information. This results in a greater reliance on such processing on the storage and processing capacities of working memory, particularly for simultaneous semantic judgment and information integration at the sentence level (Linares \u0026amp; Pelegrina, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, the reading-span tasks required participants to comprehend the meaning of individual sentences while remembering and updating the last word of the sentence. This cognitive demand is highly consistent with that for processing sentences in simple comprehension tasks. Therefore, the reading-span task is more effective in predicting simple comprehension.\u003c/p\u003e \u003cp\u003eIn contrast, complex comprehension involves integration and inferential capabilities at the level of discourse. Readers are required to integrate propositional information over broader contexts, activate background knowledge, and construct semantic networks, leading to the development of a coherent meaning model of the text by inference. Although such processing also depends on working memory to maintain the intermediate representations, the focus is shifted toward semantic construction and knowledge integration at higher levels instead of immediate retention and manipulation of information (Latini et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Hence, complex comprehension depends less directly on working memory. Instead, it relies on the background knowledge, reading strategies, and higher-order cognitive capabilities of the readers (Molokopeeva \u0026amp; Simard, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Peng et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In other words, simple comprehension relies primarily on the dual-task \u0026ldquo;storage\u0026thinsp;+\u0026thinsp;processing\u0026rdquo; capacity of working memory, while complex comprehension necessitates the engagement of higher-order cognitive capabilities.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe role of working memory in reading comprehension in L2 Chinese learners was investigated by determining the multi-dimensional associations between working memory and reading comprehension. The results indicated that working memory does not influence reading comprehension singularly or holistically, but instead its internal components exhibit dimension-specific associations with different types of reading tasks. This finding contributes to both theory and practice, enriching the theoretical framework of reading of Chinese as a second language and providing targetable insights for teaching. As both the storage and processing dimensions of working memory can significantly influence reading comprehension, teachers of Chinese should integrate cognitive training of working memory (e.g., strengthening storage capacity, designing tasks that coordinate storage and processing) into their daily teaching schedules, as well as offering specifically graded training for L2 Chinese learners.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the study focused on learners at HSK 3\u0026ndash;4 levels, which may present difficulties in generalizing the findings to beginner- or advanced-level learners. Furthermore, the tasks were conducted online, which may have affected the performance of the participants. Also, the investigation did not include comprehensive coverage of all dimensions of working memory and reading comprehension. It is suggested that future studies focus on the following aspects: 1) the moderating role of individual differences in working memory capacity on reading comprehension; 2) analysis of reading comprehension at different levels of understanding (e.g., literal, inferential, and evaluative comprehension); and 3) the application of new methods, such as eye-tracking techniques, to further analyze the cognitive processes of learners, thereby enabling further clarification of the complex mechanisms underlying the function of working memory in reading comprehension of second languages.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets and materials (Raw data, processed data and test items ) supporting the findings of this study are available for editors and reviewers during peer review. They can be accessed througn Ralated files in the system. Due to the sensitivity of human-participant data and confidentiality commitments, the de-identified data are available under controlled access from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. Ethical approval for this study was granted by the Ethics Committee of [Name of Institution Redacted] on December 12, 2022 (Approval No. [Redacted]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent was obtained electronically from the participants prior to the commencement of the study (between January and February 2024). Participants were assured of their anonymity and right to withdraw from the study at any time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor 1 contributed to the study conception, design, data analysis, and drafting and revision of all versions of the manuscript.\u003c/p\u003e\n\u003cp\u003eAuthor 2 contributed to the study conception, design, data analysis, and drafting and revision of all versions of the manuscript.\u003c/p\u003e\n\u003cp\u003eAuthor 3 contributed to the study conception, design, data analysis, and drafting of the initial manuscript.\u003c/p\u003e\n\u003cp\u003eAuthor 4 contributed to the study conception, design, data curation, and revision of all versions of the manuscript.\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlptekin C, Er\u0026ccedil;etin G (2010) The role of L1 and L2 working memory in literal and inferential comprehension in L2 reading. 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Eur J Cogn Psychol 14(3):383\u0026ndash;407\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimard D, Molokopeeva T (2024) Interaction between levels of text representation and working memory during L2 reading comprehension: What about it? Int J Appl Linguistics 34(2):568\u0026ndash;585\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStreitberger C, Kuhlmann BG, Meier ME, Arnold NR (2024) Connecting working and long-term memory: Bayesian‐hierarchical multinomial model‐based analyses reveal storage next to retrieval differences. Mem Cognit 52:1915\u0026ndash;1927\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnsworth N, Redick TS, Heitz RP, Broadway JM, Engle RW (2009) Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage. Memory 17(6):635\u0026ndash;654\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnsworth N, Engle RW (2006) Simple and complex memory spans and their relation to fluid abilities: Evidence from list-length effects. J Mem Lang 54(1):68\u0026ndash;80\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Dyke JA, Johns CL, Kukona A (2014) Low working memory capacity is only spuriously related to poor reading comprehension. Cognition 131(3):373\u0026ndash;403\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaters G, Caplan D (2004) Verbal working memory and on-line syntactic processing: Evidence from self-paced listening. Q J Experimental Psychol Sect A 57(1):139\u0026ndash;163\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H (2021) The application of effect size in studies on international Chinese education. Chinese Lang Globalization Studies (in Chinese) 12:39\u0026ndash;49\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu W, Cheng L, Chen T (2018) A study on the relationship between homographic morpheme awareness, word meaning inference, and reading comprehension among elementary Chinese learners. \u003cem\u003eChinese Teaching in the World\u003c/em\u003e. (in Chinese) 32(2):270\u0026ndash;279\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e The second sub-question of Item 1 was removed because the pilot task revealed that all participants answered it incorrectly, with inconsistent error patterns. Post-task interviews indicated that the item was ambiguous; therefore, it was excluded from the formal experiment.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chinese as a second language, working memory, reading comprehension, multi-dimensional correlation","lastPublishedDoi":"10.21203/rs.3.rs-9026197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9026197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs a fundamental skill for language ability, reading comprehension involves intricate information processing that is closely constrained by readers\u0026rsquo; cognitive ability (i.e., working memory). Although most previous studies acknowledge that both the capacity and processing efficiency of working memory affects reading comprehension, the multidimensional nature of these constructs has led to inconsistent findings, and empirical evidence specifically targeting L2 Chinese remains scarce. This study investigated the multi-dimensional associations between working memory and reading comprehension among 74 intermediate-level L2 Chinese learners whose native language was English. Three tasks of working memory (i.e., digit-span, phonological short-term-memory, and reading span tasks) and two tasks of reading comprehension (for simple and complex comprehension) were conducted. The results showed that 1) the storage, auditory, and dual-task capacities (storage and processing capacities) of working memory were significantly and positively associated with simple comprehension, while both storage and dual-task capacities were positively correlated with complex comprehension; 2) al\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003el\u003c/span\u003e capacities of working memory were found to be independent predictors of simple comprehension, while the storage and dual-task capacities were independently predictive of complex comprehension; and 3) the dual-task capacity contributed most to both simple and complex reading comprehension when all three working memory capacities were present. Therefore, it is advisable for tutors to progressively integrate daily training of working memory into L2 Chinese reading instruction.\u003c/p\u003e","manuscriptTitle":"Multi-dimensional associations between working memory and reading comprehension in L2 Chinese learners","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 15:14:21","doi":"10.21203/rs.3.rs-9026197/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T13:12:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T06:19:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76558185810317922564781612152014958675","date":"2026-03-31T14:33:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"250046700189457883839376793817035392966","date":"2026-03-31T07:57:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41898740978305542333436048874028768930","date":"2026-03-30T23:30:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178031304993775425719000979689200660045","date":"2026-03-30T14:41:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-30T12:51:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T11:46:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-18T10:59:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T09:13:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2026-03-12T05:08:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c41f5c11-cc1d-46fe-b830-a2b82afdbb46","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T13:12:47+00:00","index":41,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65476917,"name":"Humanities/Language and linguistics"},{"id":65476918,"name":"Social science/Language and linguistics"},{"id":65476919,"name":"Biological sciences/Neuroscience"},{"id":65476920,"name":"Biological sciences/Psychology"},{"id":65476921,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-04-01T15:14:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 15:14:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9026197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9026197","identity":"rs-9026197","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}