A systematic review of artificial intelligence technologies used for story writing
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Fang et al. (2023) systematic review reported that AI technologies increased writing proficiency, student engagement, and motivation, with potential benefits for language acquisition.
“Fang et al. (2023) systematic review of AI in story writing, on the other hand, reported that AI technologies increased writing proficiency, student engagement, and motivation, with potential benefits for language acquisition.”
From How Creative Is AI Writing? Generative and Collaborative AI in Japanese Fiction (2026) · cites this paper as Fang et al. (2023)
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., et al. (2018) · Annals of Internal Medicine · doi:10.7326/m18-0850 · Cited by 43,565 · see citing works
Braun, V., & Clarke, V. (2012) · APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological. · doi:10.1037/13620-004 · Cited by 10,299 · see citing works
Artificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133 · cited 2× · see citing works
“Chen et al. (2020) mentioned that AI improves students’ learning quality and experience by adjusting AI based on students’ individual needs.”
BackgroundDevelopment and use of the ARCS model of instructional design
Keller, J. M. (1987) · Journal of Instructional Development · doi:10.1007/bf02905780 · Cited by 2,332 · see citing works
Augmented reality for STEM learning: A systematic review
Ibáñez, M.-B., & Delgado-Kloos, C. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.05.002 · Cited by 1,036 · see citing works
Ouyang, F., Zheng, L., & Jiao, P. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10925-9 · Cited by 831 · see citing works
Mapping the Landscape of Creativity Support Tools in HCI
Frich, J., MacDonald Vermeulen, L., Remy, C., Biskjaer, M. M., & Dalsgaard, P. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300619 · Cited by 410 · see citing works
Takacs, Z. K., Swart, E. K., & Bus, A. G. (2015) · Review of Educational Research · doi:10.3102/0034654314566989 · Cited by 403 · see citing works
Wordcraft: Story Writing With Large Language Models
Yuan, A., Coenen, A., Reif, E., & Ippolito, D. (2022) · 27th International Conference on Intelligent User Interfaces · doi:10.1145/3490099.3511105 · Cited by 374 · see citing works
Artificial intelligence in early childhood education: A scoping review
Su, J., & Yang, W. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100049 · Cited by 357 · cited 1× · see citing works
“It is aligned with the existing literature, AI technologies benefit learning outcomes (i.e., affective, cognitive, academic, linguistic, and social) in preschool and primary education and higher/ adult education (Ouyang et al., 2022; Su & Yang, 2022).”
BackgroundLee, M., Liang, P., & Yang, Q. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502030 · Cited by 345 · cited 7× · see citing works
“Similarly, Lee et al. (2022) mentioned that although AI was incorporated into story generators, they still have multiple aspects that need to be improved, such as language technicalities and story suggestions.”
BackgroundMethodInfluentialUsing digital story writing as a pedagogy to develop AI literacy among primary students
Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100054 · Cited by 266 · see citing works
Self-citationLiu, C., Hou, J., Tu, Y.-F., Wang, Y., & Hwang, G.-J. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.2012812 · Cited by 231 · see citing works
Affordances and challenges of artificial intelligence in K-12 education: a systematic review
Crompton, H., Jones, M. V., & Burke, D. (2024) · Journal of Research on Technology in Education · doi:10.1080/15391523.2022.2121344 · Cited by 213 · cited 1× · see citing works
“Technological advances in artificial intelligence (AI) have impacted the education industry and the field of language education (Chow, 2020; Crompton et al., 2022; Klima-shevskaia et al., 2021; Ng et al., 2021).”
BackgroundTaleBrush: Sketching Stories with Generative Pretrained Language Models
Chung, J. J. Y., Kim, W., Yoo, K. M., Lee, H., Adar, E., & Chang, M. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501819 · Cited by 206 · see citing works
Sparks: Inspiration for Science Writing using Language Models
Gero, K. I., Liu, V., & Chilton, L. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533533 · Cited by 161 · see citing works
Osone, H., Lu, J.-L., & Ochiai, Y. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411763.3450391 · Cited by 74 · cited 3× · see citing works
“Overall, AI has become a new language learning trend for students to create stories, and foster their creative writing, logic, presentation, and collaboration skills (Osone et al., 2021; Yuan et al., 2022).”
BackgroundChang, T.-S., Li, Y., Huang, H.-W., & Whitfield, B. (2021) · 2021 2nd International Conference on Education Development and Studies · doi:10.1145/3459043.3459065 · Cited by 74 · see citing works
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Pellas, N. (2023) · Education Sciences · doi:10.3390/educsci13111155 · Cited by 95 · see citing works
Supporting learner agency in collaborative writing with generative <scp>AI</scp>
Kim, S., So, H., & Park, K. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70015 · Cited by 30 · see citing works
Wang, S.-C., & Yang, Y.-F. (2025) · Proceedings of the International CALL Research Conference · doi:10.29140/97817637116240-24 · Cited by 1 · see citing works
How Creative Is AI Writing? Generative and Collaborative AI in Japanese Fiction
Asano, Y., & Bastos, M. (2026) · Journal of Creative Communications · doi:10.1177/09732586261463934
- Authors
- Fang, X., Ng, D. T. K., Leung, J. K. L., & Chu, S. K. W.
- Affiliations
- Education University of Hong Kong (HK)
- University of Hong Kong (HK)
- Hong Kong University of Science and Technology (HK)
- Corresponding author
- Fang, Xiaoxuan
- Venue
- Education and Information Technologies
- Published
- 2023-04-05
- Volume
- 28
- Issue
- 11
- Pages
- 14361-14397
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4362632896
- Cited by
- 82
- References
- 19
- Citations by year
- 2026: 23 · 2025: 36 · 2024: 19 · 2023: 4
- FWCI
- 3.40
- Type
- journal article
- Language
- en
- Open access
- green
- hub.hku.hk
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion, cc-by-nc-nd)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Health Professions › Speech and Hearing › Digital Storytelling and Education
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Keywords
- artificial intelligence in education, story writing, human-AI collaboration, creativity, writing skills, student motivation, student satisfaction, presentation skills, language teaching
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