WrAFT: a Modularized Automated Writing Evaluation System for Argumentative Essays
This study presents WrAFT, a Writing Assessment and Feedback Tool, that delivers both accurate and reliable scores and effective comprehensive feedback to argumentative essays. WrAFT adopts a modular design by dividing automated writing evaluation (AWE) tasks into scoring, surface-level feedback, and deep-level feedback. In building the system, various Large Language Models (LLMs) have been evaluated, including LLaMA-3.3-70B-Instruct, GPT-4o, and Claude 3.7, through both direct prompting and supervised fine-tuning approaches. A proprietary dataset of 480 TOEFL Independent Writing essays with official benchmark scores was utilized. Benchmark-based evaluation shows that WrAFT achieves state...
| Authors | Adnan Labib, Yixuan Huang, Jiahui Wu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 July 2026 |
| Last updated at source | 16 July 2026 |
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