FACULTY

Judy Wang

WANG, Qiao (ワン チャオ, Judy), Assistant Professor

ResearchMap site : https://researchmap.jp/wangqiao

Personal web site : https://www.judywang.jp

E-mail : [judy.wang@aoni.waseda.jp]

My research intersects second language acquisition (SLA), natural language processing (NLP), and artificial intelligence (AI), focusing on the evolving role of digital technology in language education. Over the past 7 years, my work has primarily revolved around Computer-Assisted Language Learning (CALL), covering areas like Game-Based Language Learning (GBLL), corpus studies, automated essay evaluation, and computer-based testing.

I categorize my CALL research into two streams: responsive and inventive CALL. In responsive CALL, I evaluate and apply emerging technologies in language learning, with significant work in GBLL and automated content scoring using NLP tools. I also investigate online learning technologies like live transcripts and metaverse applications in synchronous environments. In inventive CALL, my focus is on creating tools that address real-world needs identified through teaching. Key projects include developing a web-based vocabulary application supporting autonomous learning, integrating gamification features, and leveraging Large Language Models (LLMs) for automated quiz generation. Additionally, I'm collaborating on fine-tuning an automatic grammar error detection model for Japanese learners, aiming to improve its accuracy and adaptability to specific learner challenges.

Education

  • B.A., English Language Studies, Changchun University of Science and Technology, 2011
  • Master in Translation and Interpreting, Beijing Foreign Studies University, 2013
  • Master in Foreign Language Acquisition and Education, Kyoto University, 2017
  • Ph.D. in Computer-Assisted Language Learning (CALL), Kyoto University, 2020

Current CELESE responsibilities

Administrative roles : CELESE minutes management, Teacher Moodle Helpdesk

Courses : Academic Reading, Concept Building and Discussion, Special Topics in Functional English-Computer Assisted Language Learning

Research areas and interests

Computer-Assisted Language Learning, Natural language processing, Large Language Models and their application in language education

Representative works

  • Wang, Q., Huang, Y., & Yuan, Z. (2024). Reducing Redundancy in Japanese-to-English Translation: A Multi-Pipeline Approach for Translating Repeated Elements. In Proceedings of the Ninth Conference on Machine Translation (WMT) (pp. 1047-1055). Association for Computational Linguistics. https://www2.statmt.org/wmt24/pdf/2024.wmt-1.107.pdf
  • Wang, Q., & Gayed, M. J. (2024). Effectiveness of Large Language Models in Automated Evaluation of Argumentative Essays: Finetuning vs. Zero-Shot Prompting. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2024.2371395
  • Wang, Q., & Yuan, Z. (2024). Assessing the efficacy of grammar error correction: A human evaluation approach in the Japanese context. In Proceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING) (pp. 1667-1672). https://aclanthology.org/2024.lrec-main.146.pdf
  • Wang, Q., Rose, R., Orita, N., & Sugawara A. (2023). Automated generation of multiple-choice cloze questions for assessing English vocabulary using GPT-turbo 3.5. Proceedings of the NLP4DH-IWCLUL 2023 Conference.
  • Wang, Q., & Li, K. (2023). The role of computer games in Chinese students’ narrative writing: A case study with The Sims. Osaka JALT Journal, 10.
  • Wang, Q., Anthony, L., & Arshad, N. I. (2023). A content-controlled monolingual comparable corpus approach to comparing learner and proficient argumentative writing. Research Methods in Applied Linguistics, 2(2), 100053. https://doi.org/10.1016/j.rmal.2023.100053
  • Wang, Q., & Yijun, C. (2023). The role of live transcripts in synchronous online L2 classrooms: Learning outcomes and learner perceptions. Education and Information Technologies. 28, 14783–14804. https://doi.org/10.1007/s10639-023-11784-8
  • Wang, Q. (2022). The use of semantic similarity tools in automated content scoring of fact-based essays written by EFL learners. Education and Information Technologies. 27(9), 13021-13049. https://doi.org/10.1007/s10639-022-11179-1
  • Wang, Q. (2020). The role of classroom-situated game-based language learning in promoting students’ communicative competence. International Journal of Computer-Assisted Language Learning and Teaching, 10(2), 59-82.
  • Wang, Q. (2019). Classroom intervention for integrating simulation games into language classrooms: An exploratory study with the SIMs 4. CALL-EJ, 20(2), 101-128.

Other

  • Competitive Funding
    • Grant-in-aid for Cross-Disciplinary Research, Telecommunications Advancement Foundation, Japan: The development of an automated writing evaluation system for argumentative essays with large language models.
    • JSPS Grant-in-aid for Early-Career Scientists: 日本人大学生向けのコンピュータ適応型英文法診断テストの開発(The development of a computerized adaptive diagnostic grammar test for Japanese university students).
  • Academic Affiliations
    • CALICO
    • EUROCALL
    • The Japanese Association for Language Teaching
    • The Japanese Association of College English Teachers
    • Japanese Association for Language Education and Technology
    • Japanese Association for Natural Language Processing
  • Review work
    • Reviewer for ReCALL
    • Reviewer for Computer Assisted Language Learning (Top 100 in 2022)