Mapping AI’s Integration into Linguistics- A Bibliometric and Thematic Analysis of ChatGPT’s Influence

References:

Aljuaid, H. (2024). The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic Review. Arab World English Journal (AWEJ) Special Issue on ChatGPT.
An, X., Chai, C. S., Li, Y., Zhou, Y., & Yang, B. (2023). Modeling students’ perceptions of artificial intelligence assisted language learning. Computer Assisted Language Learning, 1-22. https://doi.org/10.1080/09588221.2023.2246519
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
Aryadoust, V. (2023). The vexing problem of validity and the future of second language assessment. Language Testing, 40(1), 8-14.
Baños, R. (2023). Key challenges in using automatic dubbing to translate educational YouTube videos. Linguistica Antverpiensia, New Series–Themes in Translation Studies, 22.
Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and
potentials. Assessing Writing, 57, 100745.
Belinkov, Y., Durrani, N., Dalvi, F., Sajjad, H., & Glass, J. (2020). On the
linguistic representational power of neural machine translation models. Computational Linguistics, 46(1), 1-52.
Cao, Y., Kementchedjhieva, Y., Cui, R., Karamolegkou, A., Zhou, L., Dare, M., & Hershcovich, D. (2024). Cultural adaptation of recipes. Transactions of the Association for Computational Linguistics, 12, 80-99.
Church, K. W. (2018). Emerging trends: Artificial Intelligence, China and my new job at Baidu. Natural Language Engineering, 24(4), 641-647.
Church, K. W., & Hestness, J. (2019). A survey of 25 years of evaluation. Natural Language Engineering, 25(6), 753-767.
Church, K. W., & Yue, R. (2023). Emerging trends: Smooth-talking machines. Natural Language Engineering, 29(5), 1402-1410.
Cummins, J. (2024). How can emerging technologies advance the creation of language-friendly and literacy-friendly schools? Language, Culture and Curriculum, 37(1), 106–119. https://doi.org/10.1080/07908318.2024.2306286
Dale, R. (2023). Navigating the text generation revolution: Traditional data-to-text NLG companies and the rise of ChatGPT. Natural Language Engineering, 29(4), 1188-1197.
Dale, R. (2024). A year’s a long time in generative AI. Natural Language Engineering, 30(1), 201-213.
Dang, J., & Liu, L. (2022). A growth mindset about human minds promotes positive responses to intelligent technology. Cognition, 220, 104985. https://doi.org/10.1016/j.cognition.2021.104985
De los Reyes Lozano, J., & Mejías-Climent, L. (2023). Beyond the black mirror effect: The impact of machine translation in the audiovisual translation environment. Linguistica Antverpiensia, New Series – Themes in Translation Studies, 22. https://doi.org/10.52034/lans-tts.v22i.790
Divekar, R. R. et al. (2022). Foreign language acquisition via artificial intelligence and extended reality: design and evaluation. Computer Assisted Language Learning, 35(9), 2332-2360. https://doi.org/10.1080/09588221.2021.1879162
Elish, M. C., & Boyd, D. (2017). Situating methods in the magic of Big Data and AI. Communication monographs, 85(1), 57-80.
Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105, 1809–1831.
Evans, R., & Gazdar, G. (1996). DATR: A language for lexical knowledge representation. Computational linguistics, 22(2), 167-216.
Fernandes, P. et al. (2023). Bridging the gap: A survey on integrating (human) feedback for natural language generation. Transactions of the Association for Computational Linguistics, 11, 1643-1668. 10.1162/tacl_a_00626
Ghafouri, M. (2024). ChatGPT: The catalyst for teacher-student rapport and grit development in L2 class. System, 120, 103209. https://doi.org/10.1016/j.system.2023.103209
Godwin-Jones, R. (2023). Presence and agency in real and virtual spaces: The promise of extended reality for language learning. Language Learning & Technology, 27(3), 6–26. https://hdl.handle.net/10125/73529
Godwin-Jones, R. (2021). Big data and language learning: Opportunities and challenges. Language Learning & Technology, 25(1), 4–19. http://hdl.handle.net/10125/44747
Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning & Technology, 26(2), 5–24. http://doi.org/10125/73474
Godwin-Jones, R. (2023). Emerging spaces for language learning: AI bots, ambient
intelligence, and the metaverse. Language Learning & Technology, 27(2), 6–27.
https://hdl.handle.net/10125/73501
Graves, B. C. (2023). Specifications grading to promote student engagement, motivation, and learning: Possibilities and cautions. Assessing Writing, 57, 100754. https://doi.org/10.1016/j.asw.2023.100754
Guerreiro, N. M., Alves, D. M., Waldendorf, J., Haddow, B., Birch, A., Colombo, P., & Martins, A. F. (2023). Hallucinations in large multilingual translation models. Transactions of the Association for Computational Linguistics, 11, 1500-1517.
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
Hannah, L., Kim, H., & Jang, E. E. (2022). Investigating the effects of task type and linguistic background on accuracy in automated speech recognition systems: Implications for use in language assessment of young learners. Language Assessment Quarterly, 19(3), 289-313. https://doi.org/10.1080/15434303.2022.2038172
Hannah, L., Jang, E. E., Shah, M., & Gupta, V. (2023). Validity Arguments for Automated Essay Scoring of Young Students’ Writing Traits. Language Assessment Quarterly, 20(4-5), 399-420. https://doi.org/10.1080/15434303.2023.2288253
Huang, T. H., & Wang, L. Z. (2023). Artificial intelligence learning approach through total physical response embodiment teaching on French vocabulary learning retention. Computer Assisted Language Learning, 36(8), 1608-1632. https://doi.org/10.1080/09588221.2021.2008980
Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. Relc Journal, 54(2), 445-451.
Karakaya, K., & Bozkurt, A. (2022). Mobile-assisted language learning (MALL) research trends and patterns through bibliometric analysis: Empowering language learners through ubiquitous educational technologies. System, 110, 102925. https://doi.org/10.1016/j.system.2022.102925
Jeon, J., Lee, S., & Choi, S. (2023). A systematic review of research on speech-recognition chatbots for language learning: Implications for future directions in the era of large language models. Interactive Learning Environments, 1–19. https://doi.org/10.1080/10494820.2023.2204343
Jungherr, A., & Schroeder, R. (2023). Artificial intelligence and the public arena. Communication Theory, 33(2-3), 164-173.
Kessler, G. (2018). Technology and the future of language teaching. Foreign language annals, 51(1), 205-218.
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. Relc Journal, 54(2), 537-550.
Lee, T. K. (2023). Artificial intelligence and posthumanist translation: ChatGPT versus the translator. Applied Linguistics Review, (0).
Lei, L., & Liu, D. (2019). Research trends in applied linguistics from 2005 to 2016: A bibliometric analysis and its implications. Applied Linguistics, 40(3), 540–561. https://doi.org/10.1093/applin/amy003
Leong, K., Sung, A., & Jones, L. (2023). The core technology behind and beyond ChatGPT: A comprehensive review of language models in educational research. IJERI: International Journal of Educational Research and Innovation, (20), 1-21.
Liu, G. L., Darvin, R., & Ma, C. (2024). Exploring AI-mediated informal digital learning of English (AI-IDLE): a mixed-method investigation of Chinese EFL learners’ AI adoption and experiences. Computer Assisted Language Learning, 1-29. https://doi.org/10.1080/09588221.2024.2310288
Liu, G., & Ma, C. (2024). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 18(2), 125-138.
Martín-Martín, A., Thelwall, M., Orduna-Malea, E., et al. (2021). Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: A multidisciplinary comparison of coverage via citations. Scientometrics, 126, 871–906. https://doi.org/10.1007/s11192-020-03690-4
Mohsen, M. A. (2021). A bibliometric study of the applied linguistics research output of Saudi institutions in the Web of Science for the decade 2011-2020. The Electronic Library, 39(6), 865–884. https://doi.org/10.1108/EL-06-2021-0121
Mousavinasab, E., Zarifsanaiey, N., Niakan Kalhori, R., Rakhshan, M., Keikha, L., & Ghazi Saeedi, M. (2018). Intelligent tutoring systems: A systematic review of characteristics, applications, and evaluation methods. Interactive Learning Environments, 29(1), 142–163. https://doi.org/10.1080/10494820.2018.1558257
Page, M. J. et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.
Payne, A. L., Austin, T., & Clemons, A. M. (2024). Beyond the front yard: The dehumanizing message of accent-altering technology. Applied Linguistics, amae002.
Pedersen, J. (2017). The FAR model: assessing quality in interlingual subtitling. Journal of Specialised Translation, (28), 210-229.
Praphan, P. W., & Praphan, K. (2023). AI technologies in the ESL/EFL writing classroom: The villain or the champion? Journal of Second Language Writing, 62, 101072.
Ramesh, D., & Sanampudi, S. K. (2022). An automated essay scoring system: A systematic literature review. Artificial Intelligence Review, 55(3), 2495–2527. https://doi.org/10.1007/s10462-021-10068-2
Saldana, J. (2015). The coding manual for qualitative researchers (3rd ed.). Sage.
Shafiee Rad, H. (2024). Revolutionizing L2 speaking proficiency, willingness to communicate, and perceptions through artificial intelligence: a case of Speeko application. Innovation in Language Learning and Teaching, 1-16. https://doi.org/10.1080/17501229.2024.2309539
Shi, H., & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback research. ReCALL, 1-23. https://doi.org/10.1017/S0958344023000265
Shin, D., & Lee, J. H. (2023). Can ChatGPT make reading comprehension testing items on par with human experts? Language Learning & Technology, 27(3), 27–40. https://hdl.handle.net/10125/73530
Stein, J. P., & Ohler, P. (2017). Venturing into the uncanny valley of mind: The influence of mind attribution on the acceptance of human-like characters in a virtual reality setting. Cognition, 160, 43–50. https://doi.org/10.1016/j.cognition.2016.12.010
Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752.
Voss, E., Cushing, S. T., Ockey, G. J., & Yan, X. (2023). The use of assistive technologies including generative AI by test takers in language assessment: A debate of theory and practice. Language Assessment Quarterly, 20(4-5), 520-532. https://doi.org/10.1080/15434303.2023.2288256
Wan, Y., & Moorhouse, B. L. (2024). Using Call Annie as a generative artificial intelligence speaking partner for language learners. RELC Journal, 00336882231224813.
Wang, X., Pang, H., Wallace, M. P., Wang, Q., & Chen, W. (2024). Learners’ perceived AI presences in AI-supported language learning: A study of AI as a humanized agent from community of inquiry. Computer Assisted Language Learning, 37(4), 814-840. https://doi.org/10.1080/09588221.2022.2056203
Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The affordances and contradictions of AI-generated text for writers of english as a second or foreign language. Journal of Second Language Writing, 62.
Xi, X. (2023). Advancing language assessment with AI and ML: Leaning into AI is inevitable, but can theory keep up? Language Assessment Quarterly, 20(4-5), 357–376. https://doi.org/10.1080/15434303.2023.2291488
Yang, H., Kim, H., Lee, J. H., & Shin, D. (2022). Implementation of an AI chatbot as an English conversation partner in EFL speaking classes. ReCALL, 34(3), 327-343. https://doi.org/10.1017/S0958344022000039
Yuan, Z., & Jin, H. (2023). The application of machine translation in automatic dubbing in China: A case study of the feature film Mulan. Linguistica Antverpiensia, New Series–Themes in Translation Studies, 22.
Youn, S. J. (2023). Test design and validity evidence of interactive speaking assessment in the era of emerging technologies. Language Testing, 40(1), 54–60.
Zampieri, M., Rosenthal, S., Nakov, P., Dmonte, A., & Ranasinghe, T. (2023). OffensEval 2023: Offensive language identification in the age of Large Language Models. Natural Language Engineering, 29(6), 1416-1435.
Zhang, R., Zou, D., & Cheng, G. (2023). A review of chatbot-assisted learning: pedagogical approaches, implementations, factors leading to effectiveness, theories, and future directions. Interactive Learning Environments, 1–29. https://doi-org.sdl.idm.oclc.org/10.1080/10494820.2023.2202704
Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2024). Benchmarking large language models for news summarization. Transactions of the Association for Computational Linguistics, 12, 39-57.
Zhao, X. (2023). Leveraging artificial intelligence (AI) technology for English writing: Introducing wordtune as a digital writing assistant for EFL writers. RELC Journal, 54(3), 890-894. https://doi.org/10.1177/00336882221094089
Zhang, X., Li, D., Wang, C., Jiang, Z., Ngao, A. I., Liu, D., … & Tian, H. (2023). From ChatGPT to China’s sci-tech: Implications for Chinese higher education. Beijing International Review of Education, 5(3), 296–314.