AI‐Facilitated Article Revisions for Primary School Students With Writing Difficulties: Effects of a Large Language Model‐Based PDRPE Approach on Writing Performance, Attitude and Anxiety.

Background: Primary school is key to developing writing skills. However, students may face challenges in identifying and revising articles due to weak language skills, organisational thinking, comprehension, and analytical skills. Therefore, improving the writing skills of primary school students wi...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Computer Assisted Learning Vol. 41; no. 5; pp. 1 - 20
Autores principales: Zhang, Xinli, Huang, Ruiting, Zhang, Ruihua, Li, Mingyi, Tu, Yun‐Fang, Chen, Yuchen, Hu, Lailin, Hwang, Gwo‐Jen
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell Oct2025
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188234228&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 188234228
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        02664909
        6M1
      jtl: Journal of Computer Assisted Learning
      issn: 02664909
      maglogo: Y
    pubinfo:
      dt: Oct2025
      vid: 41
      iid: 5
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        188234228
        188234228
        188234228
        10.1111/jcal.70131
        188234228
      ppf: 1
      ppct: 19
      formats:
      tig:
        atl: AI‐Facilitated Article Revisions for Primary School Students With Writing Difficulties: Effects of a Large Language Model‐Based PDRPE Approach on Writing Performance, Attitude and Anxiety.
      aug:
        au:
          Zhang, Xinli
          Huang, Ruiting
          Zhang, Ruihua
          Li, Mingyi
          Tu, Yun‐Fang
          Chen, Yuchen
          Hu, Lailin
          Hwang, Gwo‐Jen
        affil: Department of Educational Technology, Wenzhou University, Wenzhou Zhejiang Province,, China
      sug:
        subj:
          Writing
          Artificial Intelligence
          Students, Elementary Psychosocial Factors
          Human
          Male
          Female
          Child
          Learning
          Student Attitudes
          Anxiety
          Language Disorders
          Educational Measurement
          China
          Teaching Methods
          Natural Language Processing
          Adaptation, Psychological
          Quasi-Experimental Studies
          Pretest-Posttest Design
          Interviews
          Thematic Analysis
          Quantitative Studies
          Coefficient alpha
          Mann-Whitney U Test
          T-Tests
          Child: 6-12 years
          Male
          Female
      ab: Background: Primary school is key to developing writing skills. However, students may face challenges in identifying and revising articles due to weak language skills, organisational thinking, comprehension, and analytical skills. Therefore, improving the writing skills of primary school students with writing difficulties has become important. Objective: Conventional writing instruction often lacks immediate, targeted feedback, whereas large language models (LLMs) offer personalised support to help students with writing difficulties improve their writing quality. Method: This study proposed an LLM‐supported PDRPE (plan, draft, revise, present, and evaluate) approach and explored its impact on the writing performance, learning attitude, and writing anxiety of primary school students with writing difficulties. Through screening, 56 participants were recruited. Among them, 29 students in the experimental group adopted the LLM‐based PDRPE approach, while 27 students in the control group used the C‐PDRPE approach. Results and Conclusions: The results showed that although there was no significant difference in the number of words, the LLM‐based PDRPE approach better facilitated students' writing performance regarding the basic competence index (including the level of detail, expression, rhetoric, and vocabulary, and transitions) and other hard measurement indexes (including the number of sentences, typo rate, and punctuation error rate). Additionally, the LLM‐based PDRPE approach better improved students' writing attitude and alleviated writing anxiety. Moreover, the interview results indicated that the LLM‐based PDRPE approach is effective in supporting the revision process. Therefore, this study provides valuable references and insights for future research on the application of LLM and effective instruction for students with writing difficulties.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N