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The study analyzed 281 Chinese university students learning Japanese and compared partially- versus wholly-mediated causal models. SEM supported the wholly-mediated model.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/sentential-inference-bridging-between-lexicalgrammatical-knowledge-and-text-comprehension-among-native-chinese-speakers-learning-japanese/289981/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/sentential-inference-bridging-between-lexicalgrammatical-knowledge-and-text-comprehension-among-native-chinese-speakers-learning-japanese/289981.png","ImageObject",300,407,{"name":42,"@type":43},"Finn","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-10","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",14,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What does the study investigate about sentential inference in language learning?","Question",{"text":63,"@type":64},"It investigates how sentential inference mediates the relationship between lexical/grammatical knowledge and overall text comprehension in second-language learning.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How is the causal relationship tested in the research design?",{"text":68,"@type":64},"The study uses structural equation modeling (SEM) to compare two causal models: a partially-mediated model and a wholly-mediated model.",{"name":70,"@type":61,"acceptedAnswer":71},"What did the SEM comparison show about the mediation paths?",{"text":72,"@type":64},"The wholly-mediated model was supported, indicating sequential effects from lexical knowledge to sentential inference and then to text comprehension, with no significant contribution from grammatical knowledge.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},289981,1789639255,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},34359740700684,"https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487","PLOS ONE  \nOPEN ACCESS  \nCitation: Tamaoka K, Sakai H, Miyaoka Y, Ono H, Fukuda M, Wu Y, et al. (2023) Sentential inference bridging between lexical/grammatical knowledge and text comprehension among native Chinese speakers learning Japanese. PLoS ONE 18(4):  \ne0284331 . [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0284331  \nEditor: Lawrence Jun Zhang, The University of Auckland, NEW ZEALAND  \nReceived: December 1, 2022  \nAccepted: March 28, 2023  \nPublished: April 13, 2023  \nCopyright: © 2023 Tamaoka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData Availability Statement: Data are available on the Open Science Framework ([https://osf.io/k2f8h/](https://osf.io/k2f8h/)).  \nFunding: This study was supported by the Grantin-Aid (B) -number 23320106-the Japan Society for the Promotion of Science (KT) and Grant-in-Aid for Scientific Research (S) 19H05589 (MK, KT) . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  \nRESEARCH ARTICLE  \nSentential inference bridging between lexical/ grammatical knowledge and text comprehension among native Chinese speakers learning Japanese  \nKatsuo Tamaoka1,2, Hiromu Sakai3, Yayoi Miyaoka4, Hajime Ono5, Michiko Fukuda6, Yuxin Wu7, Rinus G. Verdonschot8 *  \n1 Hunan University, Changsha, China, 2 Nagoya University, Nagoya, Japan, 3 Waseda University, Shinjuku City, Japan, 4 Hiroshima University of Economics, Hiroshima, Japan, 5 Tsuda University, Kodaira, Japan, 6 Bunkyo University, Koshigaya, Japan, 7 Xi’an International Studies University, Xi’an, China, 8 Max Planck Institute for Psycholinguistics in Nijmegen, Nijmegen, The Netherlands  \n* [rinus.verdonschot@mpi.nl](rinus.verdonschot@mpi.nl)  \nAbstract  \nThe current study explored the role of sentential inference in connecting lexical/grammatical knowledge and overall text comprehension in foreign language learning. Using structural equation modeling (SEM), causal relationships were examined between four latent variables: lexical knowledge, grammatical knowledge, sentential inference, and text comprehension. The study analyzed 281 Chinese university students learning Japanese as a second language and compared two causal models: (1) the partially-mediated model, which suggests that lexical knowledge, grammatical knowledge, and sentential inference concurrently influence text comprehension, and (2) the wholly-mediated model, which posits that both lexical and grammatical knowledge impact sentential inference, which then further affects text comprehension. The SEM comparison analysis supported the wholly-mediated model, showing sequential causal relationships from lexical knowledge to sentential inference and then to text comprehension, without significant contribution from grammatical knowledge. The results indicate that sentential inference serves as a crucial bridge between lexical knowledge and text comprehension.  \nIntroduction  \nIn most written or spoken texts, a specific message is conveyed through a series of semantically related sentences that form meaningful connections. To understand these texts, one must grasp the meaning of the individual words [ 1–4] and have proficiency in the grammatical rules that prescribe word arrangement within sentences [5–9] . As a result, a combination of lexical and grammatical knowledge is essential for effective sentence comprehension.  \nHowever, there is a significant difference between understanding a single sentence and comprehending the overall message conveyed by a text. A text typically consists of multiple sentences, and the comprehension of its message relies on the rules of inference that connect  \nCompeting interests: The authors have declared that no competing interests exist.  \none sentence to another","cbCaiiZY33kzCFsa","https://ap.wps.com/l/cbCaiiZY33kzCFsa","pdf",909170,17,"English","# Abstract\n# Introduction\n## Sentential inference and text comprehension\n# Background\n## The role of lexical knowledge during text comprehension","[{\"question\":\"What does the study investigate about sentential inference in language learning?\",\"answer\":\"It investigates how sentential inference mediates the relationship between lexical/grammatical knowledge and overall text comprehension in second-language learning.\"},{\"question\":\"How is the causal relationship tested in the research design?\",\"answer\":\"The study uses structural equation modeling (SEM) to compare two causal models: a partially-mediated model and a wholly-mediated model.\"},{\"question\":\"What did the SEM comparison show about the mediation paths?\",\"answer\":\"The wholly-mediated model was supported, indicating sequential effects from lexical knowledge to sentential inference and then to text comprehension, with no significant contribution from grammatical knowledge.\"}]","Sentential inference bridging between lexical/grammatical knowledge and text comprehension among native Chinese speakers learning Japanese | PDF",43]