[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-582243-105":59,"doc-detail-582243-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","content-adaptation-for-language-learning-a-hybrid-ai-approach","Content Adaptation for Language Learning - A Hybrid AI Approach","","In foreign language learning, access to comprehensible input is a decisive success factor, yet early-stage learners struggle to find materials matched to their proficiency and interests. This research and development project investigates whether large language model capabilities can transform authentic audio, video, and text into comprehensible input for independent elementary-level learners. A hybrid pipeline combines LLM affordances, careful prompt engineering, and rule-based refinement, then evaluates two rounds using teacher ratings and automated text analysis indices. Findings indicate efficient simplification of authentic content for lower-proficiency learners.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/content-adaptation-for-language-learning-a-hybrid-ai-approach/582243/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/content-adaptation-for-language-learning-a-hybrid-ai-approach/582243.png","ImageObject",300,407,{"name":92,"@type":93},"Ophelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is comprehensible input critical for language learners?","Question",{"text":112,"@type":113},"Comprehensible input supports L2 acquisition, because progress depends on access to input obtained through reading, listening, and communication, not only grammar awareness or vocabulary memorization.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What problem does the study address at early learning stages?",{"text":117,"@type":113},"Early-stage learners below intermediate proficiency often cannot find level-appropriate and engaging materials, because most authentic text and multimedia are too difficult to be useful.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the proposed hybrid AI approach simplify authentic materials?",{"text":121,"@type":113},"The approach uses a hybrid sequential pipeline that combines large language model capabilities with careful prompt engineering and rule-based refinement to produce comprehensible input.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},582243,1792231676,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},7971461741311,"https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826","The EuroCALL Review  \nVolume 32, No. 2, 2025, 169-182 ISSN: 1695-2618  \n[https://doi.org/10.4995/eurocall.2025.23898](https://doi.org/10.4995/eurocall.2025.23898)  \nRESEARCH PAPER  \nContent Adaptation for Language Learning: A Hybrid AI Approach  \nJatin Arora*; Irina Elgort  * *; Junhong Zhao  *** Victoria University of Wellington, New Zealand  \n*[jarora864@gmail.com](jarora864@gmail.com |)[ |](jarora864@gmail.com |) ** [irina.elgort@vuw.ac.nz](irina.elgort@vuw.ac.nz |)[ |](irina.elgort@vuw.ac.nz |) ***[j.zhao@vuw.ac.nz](j.zhao@vuw.ac.nz)  \nHow to cite this article:  \nArora, J., Elgort, I., & Zhao, J. (Year) . Content adaptation for language learning: A hybrid AI approach. The EuroCALL Review, 32 (2), 169-182.  \n[https://doi.org/10.4995/eurocall.2025.23898](https://doi.org/10.4995/eurocall.2025.23898)  \nAbstract  \nIn learning a foreign language, access to comprehensible input is a critical success factor. However, at early stages, when learners are still below an intermediate-proficiency level, finding level-appropriate and engaging materials is highly problematic. Although the Internet abounds in text and multimedia materials in many languages, most of them are too difficult to be useful for lower-proficiency language learners. The present project aimed to establish whether the affordances of large language models (LLMS) can be harnessed to turn authentic audio, video, and text materials into comprehensible input for independent elementary-level language learners. The present article reports on the outcomes of a research and development project that adopts a hybrid approach to simplifying authentic materials, combining affordances of LLMs with careful prompt engineering and rule-based refinement. The article details the hybrid sequential pipeline system and the results of two rounds of evaluation: language teacher ratings and automated text analysis indices. Based on the outcome of these evaluations, it is concluded that the proposed approach can provide an efficient way of simplifying authentic content for and by lower-proficiency language learners. Directions for future research and development are also proposed.  \nKeywords  \nLarge Language Models; Artificial Intelligence; comprehensible input; simplification; second language learning  \n1. Introduction  \nComprehensible input is key in second and foreign language (L2) acquisition (e.g., Krashen, 1985; Larsen-Freeman & Long, 1991) . Although studying grammar rules creates metacognitive linguistic awareness and memorising high-frequency vocabulary forms a foundation for building L2 knowledge, substantial progress in language learning is not possible without access to L2 input, obtained through reading, listening, and communication. However, unmodified authentic language input tends to be too difficult to be useful for low-proficiency language learners. Second-language acquisition research provides extensive evidence that input enhancement facilitates learning (Norris & Ortega, 2000) . Therefore, language courses, textbooks, and classroom teaching instruction are commonly developed with learners of a specific proficiency level in mind (e.g., the Headway series, by Oxford University Press, has textbooks at six proficiency levels), with L2 materials simplified to be at a difficulty level just beyond the learners’ existing knowledge.  \nIn independent language study, in particular, most running words in the text or speech should be familiar to the learner, in order to understand and learn from the input. For optimal reading with understanding, Hu and Nation (2000) recommended using texts, in which learners are likely to know 98% of the running words, while a minimal lexical coverage of 95% was proposed by Laufer and Ravenhorst-Kalovski (2010) . In reading authentic texts in English, this threshold translates into the knowledge of 8000–9000 most frequent word-families for written texts; in learning from unmodified spoken input, the knowledge of 6000-7000 word-families is needed (Nati","cbCaio0L3kv15sWx","https://ap.wps.com/l/cbCaio0L3kv15sWx","pdf",504123,14,"English","# Abstract\n# Keywords\n# 1. Introduction","[{\"question\":\"Why is comprehensible input critical for language learners?\",\"answer\":\"Comprehensible input supports L2 acquisition, because progress depends on access to input obtained through reading, listening, and communication, not only grammar awareness or vocabulary memorization.\"},{\"question\":\"What problem does the study address at early learning stages?\",\"answer\":\"Early-stage learners below intermediate proficiency often cannot find level-appropriate and engaging materials, because most authentic text and multimedia are too difficult to be useful.\"},{\"question\":\"How does the proposed hybrid AI approach simplify authentic materials?\",\"answer\":\"The approach uses a hybrid sequential pipeline that combines large language model capabilities with careful prompt engineering and rule-based refinement to produce comprehensible input.\"}]","Content Adaptation for Language Learning - A Hybrid AI Approach | PDF",1792042883,35]