研究生: |
林柏陞 Lin, Po-Sheng |
---|---|
論文名稱: |
英文寫作中的人工智能:四種大型語言模型驅動寫作工具與Grammarly的語法錯誤更正性能和反饋提供的比較分析 Artificial Intelligence in English Writing: A Comparative Analysis of Error Correction Performance and Feedback Provision Across Four LLM-Powered Writing Tools and Grammarly |
指導教授: |
陳浩然
Chen, Hao-Jan |
口試委員: |
陳浩然
Chen, Hao-Jan 王宏均 Wang, Hung-Chun 賴淑麗 Lai, Shu-Li |
口試日期: | 2024/06/14 |
學位類別: |
碩士 Master |
系所名稱: |
英語學系 Department of English |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 英文 |
論文頁數: | 134 |
中文關鍵詞: | 大型語言驅動模型 、ChatGPT 、Gemini 、Claude 3 、常見文法錯誤 、文法解釋 |
英文關鍵詞: | Large Language Models, ChatGPT, Gemini, Claude 3, grammatical error, grammatical error explanation |
DOI URL: | http://doi.org/10.6345/NTNU202401552 |
論文種類: | 學術論文 |
相關次數: | 點閱:137 下載:0 |
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Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., & Anadkat, S. (2023). GPT-4 technical report. arXiv preprint, arXiv:2303.08774. https://doi.org/10.48550/arXiv.2303.08774
Al-Garaady, J., & Mahyoob, M. (2023). ChatGPT's capabilities in spotting and analyzing writing errors experienced by EFL learners. Arab World English Journals(9), 3-17. https://doi.org/10.24093/awej/call9.1
Allen, L. K., Jacovina, M. E., & McNamara, D. S. (2016). Computer-based writing instruction. In Handbook for Writing Research (2nd ed., pp. 316-329). The Guilford Press.
Anthropic. (2024). Introducing the next generation of Claude. https://www.anthropic.com/news/claude-3-family
Barrot, J. S. (2023). Using automated written corrective feedback in the writing classrooms: effects on L2 writing accuracy. Computer Assisted Language Learning, 36(4), 584-607. https://doi.org/10.1080/09588221.2021.1936071
Baskara, F. R. (2023). Integrating ChatGPT into EFL writing instruction: Benefits and challenges. International Journal of Education and Learning, 5(1), 44-55. https://doi.org/10.31763/ijele.v5i1.858
Bibi, Z., & Atta, A. (2024). The role of ChatGPT as AI English writing assistant: A study of student’s perceptions, experiences, and satisfaction. Annals of Human and Social Sciences, 5(1), 433-443. https://doi.org/10.35484/ahss.2024(5-I)39
Bok, E., & Cho, Y. (2023). Examining Korean EFL college students’ experiences and perceptions of using ChatGPT as a writing revision tool. Journal of English Teaching through Movies and Media, 24(4), 15-27. https://doi.org/10.16875/stem.2023.24.4.15
Borji, A., & Mohammadian, M. (2023). Battle of the wordsmiths: Comparing ChatGPT, GPT-4, Claude, and Bard. GPT-4, Claude, and Bard (June 12, 2023). http://dx.doi.org/10.2139/ssrn.4476855
Chapelle, C. A., Cotos, E., & Lee, J. (2015). Validity arguments for diagnostic assessment using automated writing evaluation. Language Testing, 32(3), 385-405. https://doi.org/10.1177/0265532214565386
Chen, S., Nassaji, H., & Liu, Q. (2016). EFL learners’ perceptions and preferences of written corrective feedback: a case study of university students from Mainland China. Asian-Pacific Journal of Second and Foreign Language Education, 1(1), 5. https://doi.org/10.1186/s40862-016-0010-y
Chen, X., Ye, J., Zu, C., Xu, N., Zheng, R., Peng, M., Zhou, J., Gui, T., Zhang, Q., & Huang, X. (2023). How robust is GPT-3.5 to predecessors? A comprehensive study on language understanding tasks. arXiv preprint arXiv:2303.00293. https://doi.org/10.48550/arXiv.2303.00293
Coyne, S., Sakaguchi, K., Galván-Sosa, D., Zock, M., & Inui, K. (2023). Analyzing the performance of GPT-3.5 and GPT-4 in grammatical error correction. arXiv preprint arXiv:2303.00293. https://doi.org/10.48550/arXiv.2303.14342
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805. https://doi.org/10.48550/arXiv.1810.04805
Dikli, S., & Bleyle, S. (2014). Automated Essay Scoring feedback for second language writers: How does it compare to instructor feedback? Assessing Writing, 22, 1-17. https://doi.org/10.1016/j.asw.2014.03.006
Dodigovic, M., & Tovmasyan, A. (2021). Automated writing evaluation: The accuracy of Grammarly’s feedback on form. International Journal of TESOL Studies, 3(2), 71-87. https://doi.org/10.46451/ijts.2021.06.06
Face, H. (2024). Chatbot arena leaderboard. Retrieved 05/28 from https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard
Fang, T., Yang, S., Lan, K., Wong, D. F., Hu, J., Chao, L. S., & Zhang, Y. (2023). Is chatgpt a highly fluent grammatical error correction system? A comprehensive evaluation. arXiv preprint arXiv:2304.01746. https://doi.org/10.48550/arXiv.2304.01746
Ferris, D. (2006). Does error feedback help student writers? New evidence on the short- and long-term effects of written error correction. In F. Hyland & K. Hyland (Eds.), Feedback in Second Language Writing: Contexts and Issues (pp. 81-104). Cambridge University Press. https://doi.org/10.1017/CBO9781139524742.007
Ferris, D., & Kurzer, K. (2019). Does error feedback help L2 writers?: Latest evidence on the efficacy of written corrective feedback. In F. Hyland & K. Hyland (Eds.), Feedback in Second Language Writing: Contexts and Issues (2 ed., pp. 106-124). Cambridge University Press. https://doi.org/10.1017/9781108635547.008
Fitikides, T. J. (2000). Common mistakes in English: With exercises. Longman.
Fitria, T. N. (2021). Grammarly as AI-powered English writing assistant: Students’ alternative for writing English. Metathesis: Journal of English Language, Literature, and Teaching, 5(1), 65-78. http://dx.doi.org/10.31002/metathesis.v5i1.3519
Ghufron, M. A., & Rosyida, F. (2018). The role of Grammarly in assessing English as a Foreign Language (EFL) writing. Lingua Cultura, 12(4), 395-403. https://doi.org/10.21512/lc.v12i4.4582
Guo, K., & Wang, D. (2024). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feedback in EFL writing. Education and Information Technologies, 29(7), 8435–8463. https://doi.org/10.1007/s10639-023-12146-0
Guo, Q., Feng, R., & Hua, Y. (2022). How effectively can EFL students use automated written corrective feedback (AWCF) in research writing? Computer Assisted Language Learning, 35(9), 2312-2331. https://doi.org/10.1080/09588221.2021.1879161
Han, J., Yoo, H., Kim, Y., Myung, J., Kim, M., Lim, H., Kim, J., Lee, T. Y., Hong, H., & Ahn, S.-Y. (2023). RECIPE: How to integrate ChatGPT into EFL writing education. arXiv preprint arXiv:2305.11583. https://doi.org/10.48550/arXiv.2305.11583
Hartshorn, K. J., & Evans, N. W. (2015). The effects of dynamic written corrective feedback: A 30-week study. Journal of response to writing, 1(2), 2. https://scholarsarchive.byu.edu/journalrw/vol1/iss2/2
Hoffmann, J., Borgeaud, S., Mensch, A., Buchatskaya, E., Cai, T., Rutherford, E., Casas, D. d. L., Hendricks, L. A., Welbl, J., & Clark, A. (2022). Training compute-optimal large language models. arXiv preprint arXiv:2203.15556. https://doi.org/10.48550/arXiv.2203.15556
Huang, H.-W., Li, Z., & Taylor, L. (2020). The effectiveness of using grammarly to improve students' writing skills. Proceedings of the 5th International Conference on Distance Education and Learning, 122-127. https://doi.org/10.1145/3402569.3402594
Hyland, K., & Hyland, F. (2019). Contexts and issues in feedback on L2 writing. In F. Hyland & K. Hyland (Eds.), Feedback in second language writing: Contexts and issues (2 ed., pp. 1-22). Cambridge University Press. https://doi.org/10.1017/9781108635547.003
John, P., & Woll, N. (2020). Using grammar checkers in an ESL context: An Investigation of automatic corrective feedback. CALICO Journal, 37(2), 169-192. https://doi.org/10.1558/cj.36523
Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., & Amodei, D. (2020). Scaling laws for neural language models. arXiv preprint arXiv:2001.08361. https://doi.org/10.48550/arXiv.2001.08361
Karim, K., & Nassaji, H. (2019). The effects of written corrective feedback: A critical synthesis of past and present research. Instructed Second Language Acquisition, 3(1), 28-52. https://doi.org/10.1558/isla.37949
Khoshnevisan, B. (2019). The affordances and constraints of automatic writing evaluation (AWE) tools: A case for Grammarly. ARTESOL EFL Journal, 2(2), 12-25.
Kim, Y., Choi, B., Kang, S., Kim, B., & Yun, H. (2020). Comparing the effects of direct and indirect synchronous written corrective feedback: Learning outcomes and students' perceptions. Foreign Language Annals, 53(1), 176-199. https://doi.org/10.1111/flan.12443
Link, S., Mehrzad, M., & Rahimi, M. (2022). Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement. Computer Assisted Language Learning, 35(4), 605-634. https://doi.org/10.1080/09588221.2020.1743323
Mahapatra, S. (2024). Impact of ChatGPT on ESL students’ academic writing skills: A mixed methods intervention study. Smart Learning Environments, 11(1), 9. https://doi.org/10.1186/s40561-024-00295-9
Meyer, J. G., Urbanowicz, R. J., Martin, P. C., O’Connor, K., Li, R., Peng, P.-C., Bright, T. J., Tatonetti, N., Won, K. J., & Gonzalez-Hernandez, G. (2023). ChatGPT and large language models in academia: Opportunities and challenges. BioData Mining, 16(1), 20. https://doi.org/10.1186/s13040-023-00339-9
Nguyen Thi Thu, H. (2023). EFL teachers’ perspectives toward the use of ChatGPT in writing classes: A case study at Van Lang University. International Journal of Language Instruction, 2(3), 1-47. https://doi.org/10.54855/ijli.23231
Ningrum, S. (2023). ChatGPT’s impact: The AI revolution in EFL writing. Borneo Engineering & Advanced Multidisciplinary International Journal, 2(Special Issue (TECHON 2023)), 32-37. https://beam.pmu.edu.my/index.php/beam/article/view/109
O'Neill, R., & Russell, A. M. (2019). Grammarly: Help or hindrance? Academic learning advisors’ perceptions of an online grammar checker. Journal of Academic Language and Learning, 13(1), A88-A107. https://journal.aall.org.au/index.php/jall/article/view/591
ONeill, R., & Russell, A. (2019). Stop! Grammar time: University students’ perceptions of the automated feedback program Grammarly. Australasian Journal of Educational Technology, 35(1), 42-56. https://doi.org/10.14742/ajet.3795
OpenAI. (2023). GPT. https://platform.openai.com/docs/guides/gpt
Pfau, A., Polio, C., & Xu, Y. (2023). Exploring the potential of ChatGPT in assessing L2 writing accuracy for research purposes. Research Methods in Applied Linguistics, 2(3), 100083. https://doi.org/10.1016/j.rmal.2023.100083
Ranalli, J. (2018). Automated written corrective feedback: how well can students make use of it? Computer Assisted Language Learning, 31(7), 653-674. https://doi.org/10.1080/09588221.2018.1428994
Rasul, T., Nair, S., Kalendra, D., Robin, M., de Oliveira Santini, F., Ladeira, W. J., Sun, M., Day, I., Rather, R. A., & Heathcote, L. (2023). The role of ChatGPT in higher education: Benefits, challenges, and future research directions. Journal of Applied Learning and Teaching, 6(1), 41-56. https://doi.org/10.37074/jalt.2023.6.1.29
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Sahu, S., Vishwakarma, Y. K., Kori, J., & Thakur, J. S. (2020). Evaluating performance of different grammar checking tools. International Journal, 9(2), 2227-2233. https://doi.org/10.30534/ijatcse/2020/201922020
Schmidt-Fajlik, R. (2023). ChatGPT as a grammar checker for Japanese English language learners: A comparison with Grammarly and ProWritingAid. AsiaCALL Online Journal, 14(1), 105-119. https://doi.org/10.54855/acoj.231417
Shanahan, M. (2024). Talking about large language models. Communications of the ACM, 67(2), 68-79. https://doi.org/10.1145/3624724
Sinha, T. S., & Nassaji, H. (2022). ESL learners’ perception and its relationship with the efficacy of written corrective feedback. International Journal of Applied Linguistics, 32(1), 41-56. https://doi.org/10.1111/ijal.12378
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: Assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J., Moon, Y., Tseng, W., Warschauer, M., & Olson, C. B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894. https://doi.org/10.1016/j.learninstruc.2024.101894
Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752. https://doi.org/10.1016/j.asw.2023.100752
Sundar, P., & Demis, H. (2023, June 2). Introducing Gemini: our largest and most capable AI model. Google Blog. https://blog.google/technology/ai/google-gemini-ai/#sundar-note
Truscott, J. (2007). The effect of error correction on learners’ ability to write accurately. Journal of Second Language Writing, 16(4), 255-272. https://doi.org/10.1016/j.jslw.2007.06.003
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. arXiv preprint, arXiv:1706.03762. https://arxiv.org/abs/1706.03762
Wilson, J., & Czik, A. (2016). Automated essay evaluation software in English Language Arts classrooms: Effects on teacher feedback, student motivation, and writing quality. Computers & Education, 100, 94-109. https://doi.org/10.1016/j.compedu.2016.05.004
Wirantaka, A. (2022). Effective written corrective feedback on EFL students’ academic writing. Jurnal Pendidikan Bahasa Asing Dan Sastra, 6(2), 387-399. https://doi.org/10.26858/eralingua.v6i2.34996
Wu, H., Wang, W., Wan, Y., Jiao, W., & Lyu, M. R. (2023). ChatGPT or Grammarly? Evaluating ChatGPT on grammatical error correction benchmark. arXiv preprint, arXiv:2303.13648. https://doi.org/10.48550/arXiv.2303.13648
Xu, L., & Zhang, T. (2023). Engaging with multiple sources of feedback in academic writing: postgraduate students’ perspectives. Assessment & Evaluation in Higher Education, 48(7), 995-1008. https://doi.org/10.1080/02602938.2022.2161089
Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies, 28, 13943-13967. https://doi.org/10.1007/s10639-023-11742-4
Younis, H. A., Alyasiri, O. M., Muthmainnah, Sahib, T. M., Akhtom, D. a., Hayder, I. M., Salisu, S., & Shahid, M. (2023). ChatGPT evaluation: Can it replace Grammarly and Quillbot tools? British Journal of Applied Linguistics, 3(2), 34-46. https://doi.org/10.32996/bjal.2023.3.2.4
Zhang, J., Zorluel Özer, H., & Bayazeed, R. (2020). Grammarly vs. face-to-face tutoring at the writing center: ESL student writers' perceptions. Praxis: A Writing Center Journal, 17(2), 33-47. http://dx.doi.org/10.26153/tsw/8523
Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., & Dong, Z. (2023). A survey of large language models. arXiv preprint arXiv:2303.18223. https://doi.org/10.48550/arXiv.2303.18223
Zhou, J.-L. (2022). A study on the comparison and accuracy evaluation of grammar auto-detection tools (Master's thesis). National Taiwan Normal University. Taiwan Dissertation and Thesis Knowledge Value-Added System. https://hdl.handle.net/11296/k24npd