Papers by Yuning Ding
When Argumentation Meets Cohesion: Enhancing Automatic Feedback in Student Writing (2024.lrec-main)
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| Challenge: | Argumentative essays require a high degree of cohesion, defined as a network of semantic relationships that link together. |
| Approach: | They investigate the role of arguments in the automatic scoring of cohesion in argumentative essays. |
| Outcome: | The proposed model improves on a multi-task learning process by adding argumentative elements as an auxiliary task. |
DARIUS: A Comprehensive Learner Corpus for Argument Mining in German-Language Essays (2024.lrec-main)
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Nils-Jonathan Schaller, Andrea Horbach, Lars Ingver Höft, Yuning Ding, Jan Luca Bahr, Jennifer Meyer, Thorben Jansen
| Challenge: | Existing corpora focus on specific out-of-school domains, such as legal documents. |
| Approach: | They present a digital argumentation instruction for science corpus on 4589 essays written by 1839 german secondary school students. |
| Outcome: | The proposed corpus is annotated according to a fine-grained annotation scheme on 4589 essays written by 1839 german secondary school students. |
Don’t take “nswvtnvakgxpm” for an answer –The surprising vulnerability of automatic content scoring systems to adversarial input (2020.coling-main)
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| Challenge: | Automated content scoring systems can be used on short answer tasks to save human effort, but can invite cheating strategies such as writing irrelevant answers. |
| Approach: | They generate adversarial answers for benchmark content scoring datasets based on different methods of increasing sophistication and examine countermeasures such as adversarials. |
| Outcome: | The proposed methods show that even simple methods can reduce content scoring performance but do not solve the problem. |
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. |
| Outcome: | The proposed system improves argumentative writing quality among native English speakers and english-as-a-foreign-language learners. |
Score It All Together: A Multi-Task Learning Study on Automatic Scoring of Argumentative Essays (2023.findings-acl)
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| Challenge: | a multi-task learning approach outperforms sequential approaches for scoring argumentative essays . segmentation and classification of argumentative elements are important steps towards providing feedback on writing structure, but assessing the quality of arguments is less researched . |
| Approach: | They use a student essay dataset to study how argumentative essays are scored . they use automated span detection, type and quality prediction to combine these tasks . |
| Outcome: | The proposed method outperforms sequential approaches for segmentation and quality prediction. |
Chinese Content Scoring: Open-Access Datasets and Features on Different Segmentation Levels (2020.aacl-main)
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| Challenge: | Unlike English, which uses spaces as natural separators between words, segmentation of Chinese texts into tokens is challenging. |
| Approach: | They present two data sets for Chinese content scoring that use Chinese short answer questions and a new scoring system that uses Chinese short-answer questions. |
| Outcome: | The proposed system performs better on lower segmentation levels than on token level. |