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June 20, 2026ComputersOpen Access

Boundary Conditions for LLM-Generated Feedback in Primary Writing: An Educator-Aligned Evaluation and Design Considerations

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Authors

DZDan ZhangChangchun University of Science and TechnologyTHThuong HoangDeakin UniversityYZYe ZhuHarbin University of Science and Technology

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Implication

Randomized trial compares LLM feedback with tutor feedback in primary writing, suggesting design considerations for educators.

Key Points

  • This study aims to evaluate the effectiveness and safety of LLM-generated feedback for primary writing by comparing it to tutor feedback.
  • Conducted an educator-centered evaluation of GPT-4 Turbo for Year 5 narrative and persuasive writing.
  • Utilized authentic student drafts and tutor feedback to generate parallel LLM feedback via rubric-aligned prompting.
  • Four experienced English specialists rated the feedback using a six-dimensional rubric and analyzed reflections thematically.
  • Tutor feedback received higher mean ratings on clarity and helpfulness, but differences were not statistically significant after correction.
  • LLM feedback was rated similarly for clarity and feasibility but often identified as generic and surface-focused.
  • Identified conditions for optimal use of LLM feedback, highlighting risks when used without mediation.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a3632a0db0793dc1a539240https://doi.org/10.3390/computers15060393
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1LLM-Generated Feedback in L2 Writing: A Scoping Review2026 · 1 citations
  2. 2LLM-generated formative feedback in education: A qualitative systematic literature review2026 · 4 citations
  3. 3When and How Does LLM-Generated Feedback Surpass Traditional Automated Writing Evaluation? A Learning Trajectory Analysis of Writing Improvement2025
  4. 4From evaluation to emulation: LLMs as agents of iterative pedagogical design2026
  5. 5Empirische Arbeit: Comparing Generative AI and Expert Feedback to Students’ Writing: Insights from Student Teachers2024 · 50 citations