Abstract
A common way of assessing language learners’ mastery of vocabulary is via multiple-choice cloze (i.e., fill-in-the-blank) questions. But the creation of test items can be laborious for individual teachers or in large-scale language programs. In this paper, we evaluate a new method for automatically generating these types of questions using large language models (LLM). The VocaTT (vocabulary teaching and training) engine is written in Python and comprises three basic steps: pre-processing target word lists, generating sentences and candidate word options using GPT, and finally selecting suitable word options. To test the efficiency of this system, 60 questions were generated targeting academic words. The generated items were reviewed by expert reviewers who judged the well-formedness of the sentences and word options, adding comments to items judged not well-formed. Results showed a 75% rate of well-formedness for sentences and 66.85% rate for suitable word options. This is a marked improvement over the generator used earlier in our research which did not take advantage of GPT’s capabilities. Post-hoc qualitative analysis reveals several points for improvement in future work including cross-referencing part-of-speech tagging, better sentence validation, and improving GPT prompts.- Anthology ID:
- 2023.nlp4dh-1.7
- Volume:
- Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages
- Month:
- December
- Year:
- 2023
- Address:
- Tokyo, Japan
- Editors:
- Mika Hämäläinen, Emily Öhman, Flammie Pirinen, Khalid Alnajjar, So Miyagawa, Yuri Bizzoni, Niko Partanen, Jack Rueter
- Venues:
- NLP4DH | IWCLUL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 52–61
- Language:
- URL:
- https://aclanthology.org/2023.nlp4dh-1.7
- DOI:
- Cite (ACL):
- Qiao Wang, Ralph Rose, Naho Orita, and Ayaka Sugawara. 2023. Automated Generation of Multiple-Choice Cloze Questions for Assessing English Vocabulary Using GPT-turbo 3.5. In Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages, pages 52–61, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- Automated Generation of Multiple-Choice Cloze Questions for Assessing English Vocabulary Using GPT-turbo 3.5 (Wang et al., NLP4DH-IWCLUL 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2023.nlp4dh-1.7.pdf