Automated writing evaluation systems: A systematic review of Grammarly, Pigai, and Criterion with a perspective on future directions in the age of generative artificial intelligence
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Dizon (2024) and Ding et al. (2024) show that automated writing evaluation tools like Grammarly improve technical accuracy but not critical or creative thinking.
“Meanwhile, Dizon (2024) and Ding et al. (2024) show that automated writing evaluation tools like Grammarly improve technical accuracy but not critical or creative thinking -raising questions about the depth rather than the presence of learning when AI tools are used without pedagogical guidance.”
From Ethical Concerns and Institutional Policy Responses to Artificial Intelligence (AI) in Higher Education Across Sub-Saharan Africa (2025) · cites this paper as Ding et al. (2024)
Cites
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · see citing works
Shute, V. J. (2008) · Review of Educational Research · doi:10.3102/0034654307313795 · Cited by 4,631 · see citing works
ChatGPT for Language Teaching and Learning
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023) · RELC Journal · doi:10.1177/00336882231162868 · Cited by 1,371 · see citing works
Self-citationPavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · see citing works
Using ChatGPT for second language writing: pitfalls and potentials
Barrot, J. S. (2023) · Assessing Writing · doi:10.1016/j.asw.2023.100745 · Cited by 770 · see citing works
Exploring the potential of using an AI language model for automated essay scoring
Mizumoto, A., & Eguchi, M. (2023) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2023.100050 · Cited by 647 · see citing works
Student engagement with teacher and automated feedback on L2 writing
Zhang, Z. (., & Hyland, K. (2018) · Assessing Writing · doi:10.1016/j.asw.2018.02.004 · Cited by 546 · see citing works
Guo, K., & Wang, D. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12146-0 · Cited by 449 · see citing works
Koltovskaia, S. (2020) · Assessing Writing · doi:10.1016/j.asw.2020.100450 · Cited by 447 · see citing works
Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT
Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y.-S., Gašević, D., & Chen, G. (2023) · 2023 IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt58122.2023.00100 · Cited by 395 · see citing works
A scoping review of research on digital game-based language learning
Hung, H.-T., Yang, J. C., Hwang, G.-J., Chu, H.-C., & Wang, C.-C. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.07.001 · Cited by 319 · see citing works
Barrot, J. S. (2023) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1936071 · Cited by 248 · see citing works
Stop! Grammar time: University students’ perceptions of the automated feedback program Grammarly
ONeill, R., & Russell, A. (2019) · Australasian Journal of Educational Technology · doi:10.14742/ajet.3795 · Cited by 180 · see citing works
Examining the impact of Grammarly on the quality of mobile L2 writing
Dizon, G., & Gayed, J. M. (2021) · The JALT CALL Journal · doi:10.29140/jaltcall.v17n2.336 · Cited by 138 · see citing works
How Teacher and Grammarly Feedback Complement One Another in Myanmar EFL Students’ Writing
Thi, N. K., & Nikolov, M. (2022) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-021-00625-2 · Cited by 77 · see citing works
Exploring the Feedback Quality of an Automated Writing Evaluation System Pigai
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Shi, H., Chai, C. S., Zhou, S., & Aubrey, S. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2025.2454541 · Cited by 109 · see citing works
Testing the viability of ChatGPT as a companion in L2 writing accuracy assessment
Mizumoto, A., Shintani, N., Sasaki, M., & Teng, M. F. (2024) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2024.100116 · Cited by 104 · see citing works
Soko, J. J. (2025) · Journal of the Kenya National Commission for UNESCO · doi:10.62049/jkncu.v5i1.426 · Cited by 6 · see citing works
Hsu, H.-Y., Hakouz, A., & Fotouhi, G. (2025) · AI and Ethics · doi:10.1007/s43681-025-00794-6 · Cited by 5 · see citing works
AI Writing Assistants in Higher Education: A Comprehensive Review of Impact, Literacy, and Policy
Elharrouss, O., Mahmood, Y., Naouss, M., & Badidi, E. (2026) · Education Sciences · doi:10.3390/educsci16091571
- Authors
- Ding, L., & Zou, D.
- Affiliations
- Education University of Hong Kong (HK)
- Lingnan University (HK)
- Corresponding author
- Zou, Di
- ORCID
- Zou, Di
- Venue
- Education and Information Technologies
- Published
- 2024-01-03
- Volume
- 29
- Issue
- 11
- Pages
- 14151-14203
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4390545757
- Cited by
- 122
- References
- 18
- Citations by year
- 2026: 65 · 2025: 42 · 2024: 15
- FWCI
- 28.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- automated writing evaluation, Grammarly, criteria, writing feedback, generative AI, writing skills, student attitudes, peer feedback, non-native English speakers, university students
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