<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">EIR</journal-id><journal-title-group><journal-title>Educational Innovation Research</journal-title></journal-title-group><issn>3029-1844</issn><eissn>3029-1852</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18063/EIR.v3i8.938</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>AI-Empowered Journalism English Writing under an OBE Framework: An Intervention Study</title><url>https://artdesignp.com/journal/EIR/3/8/10.18063/EIR.v3i8.938</url><author>NiQi</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>3</volume><issue>8</issue><history><date date-type="pub"><published-time>2025-09-26</published-time></date></history><abstract>The outcome-based education (OBE) framework emphasizes rigorous constructive alignment among learning outcomes, instructional activities, and assessment criteria.&amp;nbsp;Within English for Specific Purposes, particularly Commentary&amp;nbsp;Writing, providing detailed, genre-specific and pedagogically coherent teacher feedback remains challenging. The emergence of&amp;nbsp;artificial intelligence large language models (AI LLMs) offers a potential solution by enhancing&amp;nbsp;feedback quality&amp;nbsp;and enabling an efficient scaffolding approach. This study proposes an AI-empowered teacher scaffolding model in commentary&amp;nbsp;writing&amp;nbsp;teaching, where AI specifically focuses&amp;nbsp;on genre features, informational completeness, and linguistic quality, while the teacher acts as a pedagogical mediator, strategically designing prompts, critically evaluating AI output, and transforming it into personalized and outcome-oriented feedback. It also explores the design principles of this human-machine collaborative feedback system in aligning with OBE outcomes, and students&amp;rsquo; perceptions of its efficacy. This&amp;nbsp;quasi-experimental intervention study&amp;nbsp;compares an experimental group (AI-mediated scaffolding) with a control group (traditional teacher feedback).&amp;nbsp;Students&amp;rsquo; pre-revision text (version 1) and post-revision text (version 2) were collected&amp;nbsp;and analyzed. Quantitative analyses included multi-dimensional textual comparisons. Qualitative data from&amp;nbsp;teacher logs and student interviews helped to assess the instructional process and subjective experiences.&amp;nbsp;Findings&amp;nbsp;showed this AI-empowered scaffolding model significantly enhanced students&amp;rsquo;&amp;nbsp;ability to master news genre conventions and overall writing competencies&amp;nbsp;compared with traditional feedback. Teachers&amp;rsquo; mediation of AI feedback ensured alignment with OBE learning outcomes and fostered learners&amp;rsquo; autonomy and critical evaluation skills regarding AI suggestions.&amp;nbsp;This study presents an effective methodology for incorporating LLMs into journalism commentary writing instruction while maintaining pedagogical integrity.</abstract><keywords>AI-empowered education, OBE framework, Large language models, English for Specific Purposes</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Hyland K, 2007, Genre Pedagogy: Language, Literacy and L2 Writing Instruction. Journal of Second Language Writing, 16(3): 148&amp;ndash;164.
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