AI-TELL Project

Establishing a Research Cluster for
Promoting Artificial Intelligence in Technology-Enhanced Language Learning (AI-TELL) Research

Objectives

This project aims to establish a research cluster to promote artificial intelligence in technology-enhanced language learning (AI-TELL) research in Hong Kong through the following ways:

Proposing Journal Special Issues

Proposing special issues in international journals for promoting AI-TELL research in the academic community.

Collecting Data for Research

Collecting data related to AI-TELL for providing a foundation to facilitate high-quality research collaboration.

Organizing Research Seminars 

Organizing research seminars delivered by internationally renowned scholars for acquainting EdUHK staff and students with the recent development of AI-TELL research.

Initiating Research Collaboration

Initiating research collaboration with local/international reputable scholars for increasing the capacity to bid for external competitive research funding.

About Us


Project Investigators

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Dr. CHENG, Kwok Shing Gary
Principal Investigator
Associate Professor
Department of Mathematics and Information Technology (MIT)
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Dr. GU, Ming Yue Michelle
Co-Investigator
Head & Associate Professor
Department of English
Language Education (ELE)
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Dr. ZOU, Di Daisy
Co-Investigator
Assistant Professor
Department of English
Language Education (ELE)
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Dr. LING, Man Ho Alpha
Co-Investigator
Associate Professor
Department of Mathematics and Information Technology (MIT)
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Dr. SO, Chi Fuk Henry
Co-Investigator
Senior Lecturer II
Department of Mathematics and Information Technology (MIT)
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Dr. LAM, Wai Man Winnie
Co-Investigator
Associate Head & Senior Lecturer II
Department of Mathematics and Information Technology (MIT)
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Prof. CHIU, Ming Ming
Co-Investigator
Director & Chair Professor
Analytics\Assessment Research Centre

Deliverables

Personalized Learning System:

  • Personalized Vocabulary Learning System for University Graduates Based on Context Readability and Task Diversity
    Video Demonstration


Prizes and Awards:

  • Excellent Paper Award. The 6th International Conference on Technology in Education 2023 (ICTE 2023). (Link)


Publications:

  • Cheng. G.*, & Zou, D. (2023). Towards the design of a personalized vocabulary learning system for university graduates based on context readability and task diversity. In: Cheung, S.K.S., Wang, F.L., Paoprasert, N., Charnsethikul, P., Li, K.C., Phusavat, K. (eds) Technology in Education. Innovative Practices for the New Normal. ICTE 2023. Communications in Computer and Information Science, vol 1974. Springer, Singapore. https://doi.org/10.1007/978-981-99-8255-4_12
  • Cheng, G.* (2022). Using the community of inquiry framework to support and analyse BYOD implementation in the blended EFL classroom. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2022.100854
  • Huang, X., Zou, D.*, Cheng, G., Chen, X., & Xie, H. (2023). Trends, Research Issues and Applications of Artificial Intelligence in Language Education. Educational Technology & Society, 26(1).
  • Cheng, G.* (2022). Using the community of inquiry framework to support and analyse BYOD implementation in the blended EFL classroom. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2022.100854
  • Fu, Q.-K., Zou, D.*, Xie, H., & Cheng, G. (2022). A review of AWE feedback: types learning outcomes, and implications. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2022.2033787
  • Zhang, R., Zou, D.*, Cheng, G., & Xie, H. (2022). Implementing technology-enhanced collaborative writing in second and foreign language learning: A review of practices, technology and challenges. Education and Information Technologies. https://doi.org/10.1007/s10639-022-10941-9
  • Chen, X., Cheng, G.*, Xie, H., Chen, G., & Zou, D. (2021). Understanding MOOC Reviews: Text Mining using Structural Topic Model. Human-Centric Intelligent Systems, 1(3-4), 55-65. https://doi.org/10.2991/hcis.k.211118.001
  • Huang, X., Zou, D.*, Cheng, G., & Xie, H. (2021). A Systematic Review of AR and VR Enhanced Language Learning. Sustainability, 13, 1-28. https://doi.org/10.3390/su13094639
  • Chen, X., Zou, D.*, Xie, H., & Cheng, G. (2021). Twenty years of personalized language learning: topic modeling and knowledge mapping. Educational Technology & Society, 24(1), 205-222.
  • Zhang, R., Cheng, G.*, & Chen, X. (2020). Game-based self-regulated language learning: Theoretical analysis and bibliometrics. PLoS One. 15(12). e0243827. https://doi.org/10.1371/journal.pone.0243827
  • Zou, D., Wang, M., Xie, H.*, Cheng, G., Wang, F. L., & Lee, L. K. (2020). A comparative study on linguistic theories for modelling EFL learners: facilitating personalized vocabulary learning via task recommendations. Interactive Learning Environments, 29(2), 270-282. https://doi.org/10.1080/10494820.2020.1789178
    • * Corresponding author


Datasets:


Journal Special Issues:

  • Special Issue on “Intelligent Language Acquisition in the Mobile Era”, International Journal of Mobile Learning and Organisation. (Link)
  • Special Issue on “Sustainable Education Technologies in Big Data and Artificial Intelligence Era”, Sustainability. (Link)


Conferences:

  • The 1st APSCE International Conference on Future Language Learning 2022 (ICFULL 2022), 1/7/2022 - 3/7/2022. (Link)
  • The 5th International Symposium on User Modeling and Language Learning (UMLL), Zhuhai, China, 11/11/2021 - 12/11/2021. (Link)
  • The International Conference on Education and Artificial Intelligence (ICEAI 2020), Hong Kong SAR, China, 9/11/2020 - 11/11/2020. (Link)