TellMeWhy: Learning to Explain Corrective Feedback for Second Language Learners (D19-3)
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| Challenge: | Write & Improve and Grammarly typically use canned text to explain grammatical errors, but corrective feedback with the most useful explanations may contain collocations, grammar, and contextsensitive examples. |
| Approach: | They propose to analyze sentences with corrections to identify error types and problem words and to extract grammar patterns, collocations and example sentences. |
| Outcome: | The proposed system can be used to customize explanations based on the context of the error. |
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| Challenge: | To help language learners better understand why the GEC system makes a correction, the causes of errors and the corresponding error types are two key factors. |
| Approach: | They propose to annotate large dataset with evidence words and grammatical error types to help language learners better understand corrections. |
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GEE! Grammar Error Explanation with Large Language Models (2024.findings-naacl)
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| Challenge: | Existing grammatical error correction tools do not provide natural language explanations of errors . a system needs to provide one-sentence explanations for each grammamatical errors in a pair of erroneous and corrected sentences. |
| Approach: | They propose a grammar error explanation task that uses one-sentence explanations for each grammatical error in a pair of erroneous and corrected sentences. |
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Controlled Generation with Prompt Insertion for Natural Language Explanations in Grammatical Error Correction (2024.lrec-main)
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| Challenge: | Existing studies present tokens, examples, and hints for corrections, but do not directly explain the reasons in natural language. |
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A Chinese Writing Correction System for Learning Chinese as a Foreign Language (C18-2)
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| Challenge: | a new writing correction system for Chinese learners is available for learning as a second language . a classification approach to English GEC does not require exact recognition of error types . however, there is no general model that handles all types of Chinese writing errors. |
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Exploring Methods for Generating Feedback Comments for Writing Learning (2021.emnlp-main)
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| Challenge: | Existing methods for generating explanatory notes for language learners are inadequate . nagata et al. demonstrates that neural-retrieval-based methods can generate feedback comments for preposition use . |
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Toward a Task of Feedback Comment Generation for Writing Learning (D19-1)
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| Challenge: | Existing work on feedback comment generation has been limited . despite its usefulness, there is no publicly available dataset for research on feedback comments . |
| Approach: | They introduce a task of automatically generating feedback comments such as a hint or an explanatory note for writing learning for non-native learners of English. |
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Closing the Loop: Learning to Generate Writing Feedback via Language Model Simulated Student Revisions (2024.emnlp-main)
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| Challenge: | Recent advances in language models (LMs) have made it possible to automatically generate feedback that is actionable and well-aligned with human-specified attributes. |
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Automated Writing Support Using Deep Linguistic Parsers (2020.lrec-1)
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Luís Morgado da Costa, Roger V P Winder, Shu Yun Li, Benedict Christopher Lin Tzer Liang, Joseph Mackinnon, Francis Bond
| Challenge: | Automated Grammar Error Detection (GED) and Grammar Erreor Correction (GEC) are tasks that have attracted some attention within the NLP community. |
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Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset (2022.acl-long)
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| Challenge: | Automated short answer grading systems lack content-focused elaborated feedback datasets. |
| Approach: | They propose to use the Short Answer Feedback dataset to encourage research on explainable and understandable feedback systems. |
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FEAT-writing: An Interactive Training System for Argumentative Writing (2025.coling-demos)
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| Challenge: | Argumentative writing is a critical skill for academic success, but many students struggle to develop these skills. |
| Approach: | They developed an online system that provides students with automated feedback and exercises for argumentative writing. |
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