Note: This paper is available in 9 languages: Chinese, English, Spanish, French, German, Russian, Arabic, Japanese, and Korean. If you are a non-native English speaker, I strongly recommend reading the version in your own language for easier understanding. I hope you find it useful. Abstract Targeting the core problems of low second-language (L2) reading efficiency among non-English speakers, the limitations of traditional teaching models rooted in vocabulary memorization and word order rearrangement, and the poor adaptability of existing theoretical systems, this paper proposes an original 0-to-1 theoretical framework for structured English reading — the Linear Logical Reading Method (LLRM; full name: Linear Structured English Reading Method Based on Logical Decomposition and Contextual Inferencing). Based on the reading cognition of non-English speakers, this study clarifies the original theoretical position of LLRM in the field of L2 reading research. It addresses the flaws of existing reading theories that prioritize linguistic form over cognitive logic, and native language contexts over cross-linguistic universality. Grounded in the reading practice of Chinese native speakers, the theory abandons the rigid routines of sentence splitting, inversion, and forced vocabulary memorization adopted in traditional English reading instruction. It establishes three core dimensions: linear processing (LLRP), logical structure decomposition, and contextual word meaning inference. The theory reduces the emphasis on vocabulary accumulation as a prerequisite and highlights the core function of logical thinking and structural analysis. It conforms to the human cognitive mechanism of linear information processing, with logical analysis aligned with the inherent order and semantic structure of written texts. Following the universal cognitive rules of structured information processing, it is not merely a targeted reading skill for non-English speakers, but also applicable to structured text reading training for native English beginners and adolescent learners. Through theoretical construction, international academic dialogue, theoretical deduction, scenario-based adaptability analysis, and universality demonstration, this study proves that the theory is universally applicable across languages, ages, and English proficiency levels. It can serve non-English speakers worldwide and facilitate academic enlightenment for young native English speakers, theoretically reducing the prerequisite knowledge barriers to L2 reading and improving the efficiency of interpreting structured English texts. The research indicates that the theory breaks through the limitations of traditional L2 learning paradigms, realizing the shift from memory-oriented language learning to cognition-oriented tool application. It provides an original theoretical perspective and research path for the innovation of international L2 reading theories, the optimization of language teaching systems, and cross-linguistic information communication. Update 1 | Right Confirmation one can even infer unfamiliar vocabulary from sentence meaning and word structure. I believe many non-native English learners worldwide face the same challenges as I do. Moreover, this reading method is also applicable to the literacy education and adolescent learning of native English speakers, with significantly higher efficiency than traditional methods, as it fully aligns with the principles of cognitive science and linguistics. Given the special nature of this paper, I have created versions in 9 languages: Chinese, English, Spanish, French, German, Russian, Arabic, Japanese, and Korean. Among these, only the Chinese and English versions are the most accurate and authoritative. All other language versions are translated from the English original using translation tools and may contain inaccuracies. My original intention is to enable more non-native English speakers to learn, master, and spread this theory and method. Hereby, I launch the LLRM Multilingual Translation Co-creation Campaign: Excluding Chinese and English, scholars are welcome to translate this paper into your native language or any other language (including the versions I have already uploaded, as well as those I have not yet produced), using the English version as the master template. Participation Requirements: Translate based on the original English version of LLRM I have published, ensuring the theoretical core remains unchanged, professional terminology is accurate, and sentences are fluent. Authorship Rules: The translated version retains my original author name and email address, with an additional line below: Translated by: XXX (Translator’s Full Name) I retain the status of original author, while the translator shall enjoy authorship rights for the translated version. Submission Method: Send the complete translated document (maintaining the original chapter structure and formatting) to my email, with the subject line labeled: LLRM Translation + Language Name + Translator’s Full Name Preferred formats: doc / docx. I will review, compare, and standardize the formatting. Approved translations will be uploaded to Zenodo with the translator’s information clearly marked. This is my first time translating a paper into so many languages. Please forgive any inaccuracies, as I am only proficient in Chinese and English. I have made every effort to cover major global languages, so more people can access this innovative reading method. In the field of English learning, existing methods are relatively mature, but the reading method I propose is truly unprecedented and original. I am confident its efficiency will benefit everyone. For my next paper, I will shift focus from English to launch a series of Chinese learning method papers, consisting of approximately 5 foundational theoretical papers plus 1 applied practice paper — all an entirely new, unprecedented learning system.Chinese is the second most popular language in the world after English, and as a native Chinese speaker, I will present this method with greater professionalism and thoroughness. I believe anyone who reads my work will achieve genuine breakthroughs, and will fall in love with both the Chinese language and this revolutionary learning system.
Relike Zhou (Thu,) studied this question.