Prof. GUO Kai

BA (NEU), MA (SJTU), PhD (HKU)

Assistant Professor

Prof. GUO Kai

Prof. GUO Kai

Assistant Professor

HTB Rm. 408
3943 5457


Introduction
Prof. GUO Kai is an Assistant Professor in the Department of Curriculum and Instruction at The Chinese University of Hong Kong (CUHK). He obtained his PhD in Technology-enhanced Language Learning from The University of Hong Kong (HKU). Prior to his current appointment, he served as a Post-doctoral Fellow in the Faculty of Education at HKU and as a Research Assistant Professor in the Department of Curriculum and Instruction at CUHK under the RGC Junior Research Fellow Scheme.
Research Areas
Prof. GUO Kai’s research interests include technology-enhanced language learning, computer-supported collaborative learning, artificial intelligence in education, and digital gamification. He investigates how new technologies are transforming student learning.
Selected Publications
(* corresponding author)

For an up-to-date list of publications, please refer to:
Google Scholar: https://scholar.google.com/citations?user=IxDwG28AAAAJ&hl=en
ResearchGate: https://www.researchgate.net/profile/Kai-Guo-4

2026
  1. Guo, K., Li, D., & Jiang, L. (2026). Evaluating generative artificial intelligence’s role in enhancing feedback for digital multimodal compositions: A comparative study. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2026.2640476
  2. Guo, K., Zou, S., & Zou, D. (2026). Integrated feedback as networked activity: A systematic review of multi-source feedback in ESL/EFL writing through an activity theory lens. Language Teaching Research. https://doi.org/10.1177/13621688261424479
  3. Guo, K., Li, D., Pan, M., & Lai, C. (2026). Investigating students’ engagement with GenAI-supported peer feedback generation in EFL writing. Interactive Learning Environments. https://doi.org/10.1080/10494820.2026.2679729
  4. Li, D., & Guo, K.* (2026). Leveraging GenAI for automated feedback on source-based writing: A three-stage model. TESOL Quarterly. http://doi.org/10.1002/tesq.70170
  5. Wang, H., & Guo, K.* (2026). Student-AI collaboration in peer feedback: Effects on perceived feedback quality, emotional responses, and feedback literacy development. Assessing Writing. https://doi.org/10.1016/j.asw.2026.101100
  6. Lai, C., Pan, M., Guo, K., & Cui, Y. (2026). What task to offload to GenAI in the writing feedback process? – Effects of task-offloading approaches on EFL learners’ writing skill development. Computers & Education. https://doi.org/10.1016/j.compedu.2026.105675
  7. Zhong, Y., Guo, K., Xu, L., & Fryer, L. K. (2026). From virtual to reality: A systematic review of the impact of virtual reality on skill acquisition, retention, and transfer. Educational Research Review. https://doi.org/10.1016/j.edurev.2026.100767
  8. Zhang, D., Li, D., & Guo, K. (2026). From passive consumers to critical creators: Enhancing university students’ new media literacy through AI-enhanced digital multimodal composing. Interactive Learning Environments. https://doi.org/10.1080/10494820.2026.2617985
  9. Woo, D. J., Kizilates, M. S., Guo, K., & Wang, D. (2026). Developing English academic writing and AI literacy in an EFL co-curricular secondary school context. Innovation in Language Learning and Teaching. https://doi.org/10.1080/17501229.2026.2636962
  10. Woo, D. J., Susanto, H., & Guo, K. (2026). EFL students’ attitudes and contradictions in a machine-in-the-loop writing activity system. In T. Wang, & T. Keane (Eds.), Artificial intelligence for advancing education quality and inclusion: Practices across educational settings (pp. 341–362). Switzerland: Springer. https://doi.org/10.1007/978-3-032-12174-5_19

2025
  1. Guo, K., Li, D., Wang, J., & Chu, S. K. W. (2025). From retrieval to generative models: A design-based research approach to developing a chatbot for argumentative writing. Innovation in Language Learning and Teaching, 1–15. https://doi.org/10.1080/17501229.2025.2511273
  2. Xiao, Y., Li, D., & Guo, K.* (2025). Using ChatGPT to bring non-player characters to life: Effects on students’ storyline-driven game-based writing learning. Computers & Education, 238, 105414. https://doi.org/10.1016/j.compedu.2025.105414
  3. Xiao, Y., Li, D., & Guo, K.* (2025). Generative AI-powered non-player characters in digital storyline-based learning: An innovative approach to EFL writing. Innovation in Language Learning and Teaching, 1–15. https://doi.org/10.1080/17501229.2025.2545397
  4. Li, D., Xia, S., & Guo, K.* (2025). Investigating L2 learners’ text-to-video resemiotisation in AI-enhanced digital multimodal composing. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2025.2481402
  5. Li, D., Xia, S., & Guo, K.* (2025). Using AI to enhance digital multimodal composing: EFL learners’ semiotic decision-making, self-efficacy, enjoyment, and continuance intention. Language Learning & Technology, 29(1), 1–15. https://doi.org/10.64152/10125/73636
  6. Wang, J., & Guo, K.* (2025). Impacts of GenAI-assisted collaborative prewriting on university EFL students’ interactions with GenAI, outline quality, and task motivation. System, 135, 103857. https://doi.org/10.1016/j.system.2025.103857
  7. Pan, M., Lai, C., Guo, K., & Huang, J. (2025). Self-regulation plus individual interests? A design-based study on the development of a GenAI-empowered platform for self-directed out-of-class reading. Computers & Education, 241, 105474. https://doi.org/10.1016/j.compedu.2025.105474
  8. Pan, M., Lai, C., & Guo, K. (2025). AI chatbots as reading companions in self-directed out-of-class reading: A self-determination theory perspective. British Journal of Educational Technology, 1–29. https://doi.org/10.1111/bjet.70002
  9. Pan, M., Lai, C., & Guo, K. (2025). Technology-enhanced self-regulated second language learning interventions: A systematic review. System, 131, 103675. https://doi.org/10.1016/j.system.2025.103675
  10. Zou, S., Guo, K., Wang, J., & Liu, Y. (2025). Investigating students’ uptake of teacher- and ChatGPT-generated feedback in EFL writing: A comparison study. Computer Assisted Language Learning, 1–30. https://doi.org/10.1080/09588221.2024.2447279
  11. Woo, D. J., Wang, D., Yung, T., & Guo, K. (2025). Effects of a prompt engineering intervention on undergraduate students’ AI self-efficacy, AI knowledge, and prompt engineering ability: A mixed methods study. British Educational Research Journal. https://doi.org/10.1002/berj.70087
  12. Woo, D. J., Guo, K., & Susanto, H. (2025). EFL secondary students’ use of ChatGPT for writing task completion pathways. The Journal of Educational Research, 1–14. https://doi.org/10.1080/00220671.2025.2510382
  13. Woo, D. J., Wang, D., & Guo, K. (2025). Comparing Hong Kong secondary school students’ perceptions of ChatGPT-assisted EFL writing. The Journal of Educational Research, 1–21. https://doi.org/10.1080/00220671.2025.2525243

2024
  1. Guo, K. (2024). EvaluMate: Using AI to support students’ feedback provision in peer assessment for writing. Assessing Writing, 61, 100864. https://doi.org/10.1016/j.asw.2024.100864
  2. Guo, K., Zhang, D., Li, D., & Yu, S. (2024). Using AI-supported peer review to enhance feedback literacy: An investigation of students’ revision of feedback on peers’ essays. British Journal of Educational Technology, 56(4), 1612–1639. https://doi.org/10.1111/bjet.13540
  3. Guo, K., Pan, M., Li, Y., & Lai, C. (2024). Effects of an AI-supported approach to peer feedback on university EFL students’ feedback quality and writing ability. The Internet and Higher Education, 63, 100962. https://doi.org/10.1016/j.iheduc.2024.100962
  4. Guo, K. & Li, D. (2024). Understanding EFL students’ use of self-made AI chatbots as personalized writing assistance tools: A mixed methods study. System, 124, 103362. https://doi.org/10.1016/j.system.2024.103362
  5. 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, 8435–8463. https://doi.org/10.1007/s10639-023-12146-0
  6. Guo, K., Zhong, Y., Qin, J., & Chu, S. K. W. (2024). Investigating EFL teachers’ lesson planning for chatbot-assisted learning of argumentative writing: A TPACK perspective. Interactive Learning Environments, 1–22. https://doi.org/10.1080/10494820.2024.2372646
  7. Guo, K., Li, Y., Li, Y., & Chu, S. K. W. (2024). Understanding EFL students’ chatbot-assisted argumentative writing: An activity theory perspective. Education and Information Technologies, 29, 1–20. https://doi.org/10.1007/s10639-023-12230-5
  8. Guo, K., Li, Y., & Chu, S. K. W. (2024). Game on: Enhancing argumentative writing with digital gamification. Innovation in Language Learning and Teaching, 1–13. https://doi.org/10.1080/17501229.2024.2374347
  9. Yin, S., Guo, K.*, & Li, D. (2024). To assign a topic or not: Examining critical thinking in English as a foreign language speaking. RELC Journal, 1–14. https://doi.org/10.1177/00336882231222651
  10. Fang, X., Guo, K.*, & Ng, D. T. K. (2024). Sudowrite: Co-writing creative stories with artificial intelligence. RELC Journal, 56(3), 794–798. https://doi.org/10.1177/00336882241250109
  11. Pan, M., Lai, C., & Guo, K. (2024). Effects of GenAl-empowered interactive support on university EFL students’ self-regulated strategy use and engagement in reading. The Internet and Higher Education, 65, 100991. https://doi.org/10.1016/j.iheduc.2024.100991
  12. Pan, M., Guo, K., & Lai, C. (2024). Using artificial intelligence chatbots to support English-as-a-foreign language students’ self-regulated reading. RELC Journal. https://doi.org/10.1177/00336882241264030
  13. Woo, D. J., Susanto, H., Yeung, C. H., Guo, K., & Fung, A. K. Y. (2024). Exploring AI-generated text in student writing: How does AI help? Language Learning & Technology, 28(2), 183–209. https://hdl.handle.net/10125/73577
  14. Woo, D. J., Guo, K., & Susanto, H. (2024). Exploring EFL students’ prompt engineering in human-AI story writing: An activity theory perspective. Interactive Learning Environments, 1–20. https://doi.org/10.1080/10494820.2024.2361381
  15. Woo, D. J., Guo, K., & Salas‐Pilco, S. Z. (2024). Writing creative stories with AI: Learning designs for secondary school students. Innovation in Language Learning and Teaching, 1–13. https://doi.org/10.1080/17501229.2024.2384884
  16. Woo, D. J., Wang, D., Guo, K., & Susanto, H. (2024). Teaching EFL students to write with ChatGPT: Students’ motivation to learn, cognitive load, and satisfaction with the learning process. Education and Information Technologies, 29(18), 24963–24990. https://doi.org/10.1007/s10639-024-12819-4
  17. Zhong, Y., Guo, K., & Chu, S. K. W. (2024). Affordances and constraints of integrating esports into higher education from the perspectives of students and teachers: An ecological systems approach. Education and Information Technologies, 1–35. https://doi.org/10.1007/s10639-024-12482-9
  18. Zhong, Y., Guo, K., Fryer, L. K., Chu, S. K. W, & Deng, H. (2024). More than just fun: Investigating students’ perceptions towards the potential of leveraging esports for promoting the acquisition of 21st century skills. Education and Information Technologies, 1–33. https://doi.org/10.1007/s10639-024-13146-4

2023
  1. Guo, K., Zhong, Y., Li, D., & Chu, S. K. W. (2023). Effects of chatbot-assisted in-class debates on students’ argumentation skills and task motivation. Computers & Education, 203, 104862. https://doi.org/10.1016/j.compedu.2023.104862
  2. Guo, K., Zhong, Y., Li, D., & Chu, S. K. W. (2023). Investigating students’ engagement in chatbot-supported classroom debates. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2207181
  3. Guo, K., Zhong, Y., Zainuddin, Z., & Chu, S. K. W. (2023). Applying game-related methods in the writing classroom: A scoping review. Education and Information Technologies, 29(4), 4481–4504. https://doi.org/10.1007/s10639-023-11998-w
  4. Woo, D. J., Wang, Y., Susanto, H., & Guo, K. (2023). Understanding English as a foreign language students’ idea generation strategies for creative writing with natural language generation tools. Journal of Educational Computing Research, 61(7), 1464–1482. https://doi.org/10.1177/07356331231175999
  5. Su, J., Guo, K., Chen, X., & Chu, S. K. W. (2023). Teaching artificial intelligence in K–12 classrooms: A scoping review. Interactive Learning Environments, 1–20. https://doi.org/10.1080/10494820.2023.2212706
  6. Wang, D., Shan, D., Zheng, Y., Guo, K., Chen, G., & Lu, Y. (2023). Can ChatGPT detect student talk moves in classroom discourse? A preliminary comparison with Bert. In M. Feng, T. Käser, & P. Talukdar (Eds.), Proceedings of the 16th International Conference on Educational Data Mining (pp. 515–519). International Educational Data Mining Society. https://doi.org/10.5281/zenodo.8115772

2022 and before
  1. Guo, K., Wang, J., & Chu, S. K. W. (2022). Using chatbots to scaffold EFL students’ argumentative writing. Assessing Writing, 54, 100666. https://doi.org/10.1016/j.asw.2022.100666
  2. Guo, K., Chen, X., & Qiao, S. (2022). Exploring a collaborative approach to peer feedback in EFL writing: How do students participate? RELC Journal, 1–15. https://doi.org/10.1177/00336882221143192
  3. Zhong, Y., Guo, K., Su, J., & Chu, S. K. W. (2022). The impact of esports participation on the development of 21st century skills in youth: A systematic review. Computers & Education, 191, 104640. https://doi.org/10.1016/j.compedu.2022.104640
  4. Guo, K., Gu, M., & Jin, T. (2021). Evaluating sources of evidence for argumentative writing: A collaborative learning design. TESOL Quarterly, 55(3), 1060–1070. https://doi.org/10.1002/tesq.3025
  5. Guo, K., Chen, J., Lei, J., & Jin, T. (2021). Teacher engagement with technology-enhanced text adaptation: A case study. International Journal of Computer-Assisted Language Learning and Teaching, 11(4), 100–112. https://doi.org/10.4018/IJCALLT.2021100107
  6. Jin, T., Duan, H., Lu, X., Ni, J., & Guo, K.* (2021). Do research articles with more readable abstracts receive higher online attention? Evidence from Science. Scientometrics, 126(10), 8471–8490. https://doi.org/10.1007/s11192-021-04112-9
  7. Bo, W., Chen, J., Guo, K., & Jin, T. (2019). Data-driven adapting for fine-tuning Chinese teaching materials: Using corpora as benchmarks. In X. Lu, & B. Chen (Eds.), Computational and corpus approaches to Chinese language learning (pp. 99–118). Singapore: Springer. https://doi.org/10.1007/978-981-13-3570-9_6
  8. Jin, T., Guo, K., Mak, B., & Wu, Q. (2017). Lexical profiles of reading texts in high-stakes tests: Where are the benchmarks? International Journal of Computer-Assisted Language Learning and Teaching, 7(1), 34–49. https://doi.org/10.4018/IJCALLT.2017010103