CoChat
Sign Up
Cited by 1Technology Adoption and User BehaviourArtificial Intelligence in EducationEnglish Language Learning and Teaching

Investigating EFL Students’ ChatGPT Usage and Attitudes Through the Lens of the Technology Acceptance Model (TAM)

Open access
Alghasab, Maha·2025·Educational Process International Journal
DOI 10.22521/edupij.2025.18.507
Open this paper in CoChat — free account

Abstract

Background/purpose. Due to its significant potential, ChatGPT has recently revolutionized global education, particularly in the field of language learning. Against this backdrop, this study examines the perceptions of English as a Foreign Language (EFL) students regarding the use of ChatGPT to enhance their English language skills. It examines whether gender and prior experience with technology influence EFL learners' perceptions of ChatGPT and their intentions to utilize it. Materials/methods. Based on the Technology Acceptance Model (TAM), this study examines several key attributes: perceived ease of use, perceived usefulness, attitude, behavioral intention, actual use, perceived enjoyment, facilitating conditions, and technological complexity. Employing a sequential explanatory mixed methods design, the data were collected using an adapted TAM questionnaire (n=108), followed by semi-structured interviews with selected students who exhibited the highest and lowest positive responses (20 students). Descriptive and inferential statistics were employed to analyze the quantitative data, while a thematic analysis was utilized for qualitative data analysis. Results. Findings revealed overall positive perceptions towards using ChatGPT. Statistical analysis indicated that gender did not significantly influence TAM attributes. However, prior experience with technology emerged as a statistically significant predictor, demonstrating a measurable impact on both intentions to use and the actual use of ChatGPT. Conclusion. These findings suggest that one of the most effective ways to overcome resistance to adopting ChatGPT is to increase users' familiarity and confidence in the technology.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.22521/edupij.2025.18.507

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Learners generally report high perceived usefulness and ease of use of generative AI tools, in line with TAM.

    “Learners generally report high perceived usefulness and ease of use, in line with the TAM (Alsaedi, 2025; Alghasab, 2025).”

    From A New Era with Artificial Intelligence Powered Learner Corpora for Teaching and Learning of English as a Second Language in Primary School Education (2025) · cites this paper as Alghasab, 2025

    The Abstract reports overall positive perceptions of ChatGPT among the EFL students studied and says the TAM questionnaire measured perceived usefulness and ease of use. It does not separately report high ratings for both attributes, and a study of ChatGPT among EFL students does not establish the claim for learners or generative AI tools generally. (LLM, conf=0.80)

    Experimental — accuracy not yet measured

  • Many EFL learners already rely on generative AI tools to generate ideas, reorganise sentences and correct grammar.

    “Recent studies indicate that many EFL learners already rely on such tools to generate ideas, reorganise sentences and correct grammar.”

    From A New Era with Artificial Intelligence Powered Learner Corpora for Teaching and Learning of English as a Second Language in Primary School Education (2025) · cites this paper as Alghasab, 2025

    The retrieved passages from the paper’s References section list studies on EFL writing and ChatGPT, but do not report that many learners use these tools to generate ideas, reorganise sentences, or correct grammar. Searches for those activities and close paraphrases did not retrieve a passage from the paper’s body that addresses the claim. (LLM, conf=0.70)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Still being checked.

Research works printed but not linked: 71

  1. Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., Farhan, S. S., Khatib, S. E., Rahal, M., Sahban, A., Abdelaziz, D. H., Mansour, N. O., AlZayer, R., Khalil, R., Fekih-Romdhane, F., & Hallit, R., ... (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Scientific Reports, 14, Article 52549. https://doi.org/10.1038/s41598-024-52549-8 · DOI
  2. Aksakallı, C., & Daşer, Z. (2025). Unlocking EFL learners’ insights into ChatGPT use for L2 writing: The impacts of usage frequency and gender variations. Current Psychology, 44(9), 7957–7977. https://doi.org/10.1007/s12144-025-07437-3 · DOI
  3. Alenezi, W. (2024). Potentiality and apprehensions of artificial intelligence in education: Perspectives of education staff. International Journal of Education in Mathematics, Science and Technology, 12(4), 942–956. https://doi.org/10.46328/ijemst.4177 · DOI
  4. Alharathi, M. S. (2024). Beyond traditional language learning: EFL student views on ChatGPT in Saudi Arabia. Arab World [Journal]. https://doi.org/10.31235/osf.io/7b34j · DOI
  5. Alkandari, H. (2025). Students’ learning in the time of artificial intelligence (AI): Students’ perceptions of using AI tools to improve their language learning in Kuwait. Educational Process International Journal, 15(1), Article e2025154. https://doi.org/10.22521/edupij.2025.15.154 · DOI
  6. Al-Khreshehm, M. (2024). The future of artificial intelligence in English language teaching: Pros and Cons of ChatGPT implementation through a systematic review. Teaching. Research Quarterly, 43, 54–80. https://doi.org/10.32038/ltrq.2024.43.04 · DOI
  7. Allen, T. J., & Mizumoto, A. (2024). ChatGPT over my friends: Japanese EFL learners’ preferences for editing and proofreading strategies. RELC Journal. https://doi.org/10.1177/00336882241262533 · DOI
  8. Almansour, N. (2024). Investigating factors influencing EFL learners’ behavioural intentions to adopt ChatGPT for language learning. Journal of Language Teaching and Research, 15(6), 1910–1918. https://doi.org/10.17507/jltr.1506.16 · DOI
  9. Alotaibi, H. M., Sonbul, S. S., & El-Dakhs, D. A. (2025). Factors Influencing the Acceptance and Use of ChatGPT among English as a Foreign Language Learners in Saudi Arabia. Humanities and Social Sciences Communications, 12(1), 628. https://doi.org/10.1057/s41599-025-04945-2 · DOI
  10. Alsalem, M. S. (2024). EFL students’ perception and attitude towards the use of ChatGPT to promote English speaking skills in the Saudi context. Arab World English Journal, 15(4), 73–84. https://doi.org/10.24093/awej/vol15no4.5 · DOI
  11. Baek, C., Tate, T., & Warschauer, M. (2024). ‘GhatGPT seems too good to be true’: College students’ use and perceptions of generative AI. Computers and education. Artificial Intelligence, 7. https://doi.org/10.1016/j.caeai.2024.100294 · DOI · Paper page
  12. Bao, Y., & Li, B. (2023). A preliminary study on graduate student instructors’ exploration, perception, and use of ChatGPT. International Journal of Computer-Assisted Language Learning and Teaching, 13(1), 1–23. https://doi.org/10.4018/IJCALLT.332873 · DOI
  13. Barrot, J. S. (2023a). Using automated written corrective feedback in the writing classrooms: Effects on L2 writing accuracy. Computer Assisted Language Learning, 36(4), 584–607. https://doi.org/10.1080/09588221.2021.1936071 · DOI · Paper page
  14. Barrot, J. S. (2023b). Using ChatGPT for Second Language Writing: Pitfalls and Potentials. Assessing Writing, 57. https://doi.org/10.1016/j.asw.2023.100745 · DOI · Paper page
  15. Baytak, A. (2023). The acceptance and diffusion of generative artificial intelligence in education: A literature review. Current Perspectives in Educational Research, 6(1), 7–18. https://doi.org/10.46303/cuper.2023.2 · DOI
  16. Bodani, N., Lal, A., Maqsood, A., Altamash, S., Ahmed, N., & Heboyan, A. (2023). Knowledge, attitude, and practices of general population toward utilizing ChatGPT: A cross-sectional study. Sage Open, 13(4). https://doi.org/10.1177/21582440231211079 · DOI · Paper page
  17. Boudouaia, A., Mouas, S., & Kouider, B. (2024). A study on ChatGPT-4 as an innovative approach to enhancing English as a foreign language writing learning. Journal of Educational Computing Research, 62(6), 1289–1317. https://doi.org/10.1177/07356331241247465 · DOI
  18. Creely, E. (2024). Exploring the role of generative AI in enhancing language learning: Opportunities and challenges. International Journal of Changes in Education, 1(3), 158–167. https://doi.org/10.47852/bonviewIJCE42022495 · DOI · Paper page
  19. Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
  20. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339. https://doi.org/10.2307/249008 · DOI · Paper page
  21. Draxler, F., Buschek, D., Tavast, M., Hämäläinen, P., Schmidt, A., Kulshrestha, J., & Welsch, R. (2023). Gender, age, and technology education influence the adoption and appropriation of LLMs. arXiv preprint arXiv:2310.06556. https://doi.org/10.48550/arXiv.2310.06556 · DOI · Paper page
  22. Ekundayo, T., Khanm, Z., & Chaudhry, S. A. (2024). GhatGPT’s Integration in GCC Higher Education: A Bibliometric Analysis of Trends. Education and Information Technologies, 29(1), 1–22. https://doi.org/10.22521/edupij.2024.133.4 · DOI
  23. Elshaer, I. A., Hasanein, A. M., & Sobaih, A. E. E. (2024). The moderating effects of gender and study discipline in the relationship between university students’ acceptance and use of ChatGPT. European Journal of Investigation in Health, Psychology and Education, 14(7), 1981–1995. https://doi.org/10.3390/ejihpe14070132 · DOI
  24. Faisal, E. (2024). Unlock the potential for Saudi Arabian higher education: A systematic review of the benefits of ChatGPT. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1325601 · DOI · Paper page
  25. Frank, K. A., Zhao, Y., & Borman, K. M. (2004). Social capital and the diffusion of innovations within organizations: The case of computer technology in schools. Sociology of Education, 77(2), 148–171. https://doi.org/10.1177/003804070407700203 · DOI
  26. Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216 · DOI · Paper page
  27. Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning and Technology, 26(2), 5–24. http://doi.org/10125/73474
  28. Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593. https://doi.org/10.1111/bjet.12864 · DOI · Paper page
  29. Grassini, S., Aasen, M. L., & Møgelvang, A. (2024). Understanding university students’ acceptance of ChatGPT: Insights from the UTAUT2 model. Applied Artificial Intelligence, 38(1), Article 2371168. https://doi.org/10.1080/08839514.2024.2371168 · DOI
  30. Holmes, W., Porayska‐Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1 · DOI · Paper page
  31. Horn, K. (2024). ChatGPT in English language learning: Exploring Perceptions and Promoting autonomy in a University EFL context. The Electronic Journal for English as a Second Language TESL-EJ, 28(1). https://doi.org/10.55593/ej.28109a8 · DOI
  32. Hu, W.-C., & Škultéty, R. (2024). Unlocking the learning potential: ChatGPT as a virtual platform for cross-interaction in English language learning. Eng. Proc., 74, 59. https://doi.org/engproc2024074059
  33. Huang, F., Teo, T., & Scherer, R. (2022). Investigating the antecedents of university students’ perceived ease of using the Internet for learning. Interactive Learning Environments, 30(6), 1060–1076. https://doi.org/10.1080/10494820.2019.1710540 · DOI
  34. Huang, H.-M., & Liaw, S.-S. (2018). An analysis of learners’ intentions toward virtual reality learning based on constructivist and technology acceptance approaches. The International Review of Research in Open and Distributed Learning, 19(1). https://doi.org/10.19173/irrodl.v19i1.2503 · DOI
  35. Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning -are they really useful? A Systematic Review of Chatbot-Supported Language Learning. Journal of Computer Assisted Learning, 38(1), 237–257. https://doi.org/10.1111/jcal.12610 · DOI · Paper page
  36. Hwang, M., Lee, E., & Lee, H.-K. (2025). Exploring EFL learners’ acceptance of ChatGPT: Application of the extended technology acceptance model. English Teaching, 80(1), 45–69. https://doi.org/10.15858/engtea.80.1.202503.45 · DOI
  37. Islahi, F., & Nasrin, N. (2019). Exploring teacher attitude towards information technology with a gender perspective. Contemporary Educational Technology, 10(1), 37–54. https://doi.org/10.30935/cet.512527 · DOI
  38. Jorge-Vázquez, J., Náñez Alonso, S. L., Fierro Saltos, W. R., & Pacheco Mendoza, S. (2021). Assessment of digital competencies of university faculty and their conditioning factors: Case study in a technological adoption context. Education Sciences, 11(10), 637. https://doi.org/10.3390/educsci11100637 · DOI
  39. Jushermi, J., Turnip, Y. D., & Musfar, T. F. (2024). Acceptance model for utilizing the e-marketplace Tokopedia with the Technology Acceptance Model among Pekanbaru city communities. West Science Business and Management, 2(1), 107–121. https://doi.org/10.58812/wsbm.v2i01.562 · DOI
  40. Kemp, A., Palmer, E., & Strelan, P. (2019). A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models. British Journal of Educational Technology, 50(5), 2394–2413. https://doi.org/10.1111/bjet.12833 · DOI
  41. Khanchel, H. (2023). Factors affecting social network use by students in Tunisia. Human Systems Management, 42(2), 131–148. https://doi.org/10.3233/HSM-220017 · DOI
  42. Kim, S.-W. (2023). Change in attitude toward artificial intelligence through experiential learning in artificial intelligence education. International Journal on Advanced Science, Engineering and Information Technology, 13(5), 1953–1959. https://doi.org/10.18517/ijaseit.13.5.19039 · DOI
  43. Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868 · DOI · Paper page
  44. Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. Teaching English as a Second or Foreign Language–TESL-EJ, 27(3). https://doi.org/10.55593/ej.27107int · DOI
  45. Kotsis, K. T. (2024). Artificial Intelligence creates plagiarism or academic research? European Journal of Arts, Humanities and Social Sciences, 1(6), 169–179. https://doi.org/10.59324/ejahss.2024.1(6).18 · DOI
  46. Li, B., Lowell, V., Wang, C., & Li, X. (2024a). A systematic review of the first year of publications on ChatGPT and language education: Examining research on ChatGPT’s use in language learning and teaching. Computers and education: Artificial Intelligence.7 article:100266 https://doi.org/10.1016/j.caeai.2024.100266 · DOI
  47. 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. https://doi.org/10.1080/17501229.2023.2240316 · DOI · Paper page
  48. Lo, C. K., Yu, P. L. H., Xu, S., Ng, D. T. K., & Jong, M. S. (2024). Exploring the application of ChatGPT in ESL/EFL education and related research issues: A systematic review of empirical studies. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00342-5 · DOI
  49. Ma, M. (2025). Exploring the acceptance of generative artificial intelligence for language learning among EFL postgraduate students: An extended tam approach. International Journal of Applied Linguistics, 35(1), 91–108. https://doi.org/10.1111/ijal.12603 · DOI
  50. Panagiotarou, A., Stamatiou, Y. C., Pierrakeas, C., & Kameas, A. (2020). Gamification acceptance for learners with different e-skills. International Journal of Learning, Teaching and Educational Research, 19(2), 263–278. https://doi.org/10.26803/ijlter.19.2.16 · DOI
  51. Polakova, P., & Ivenz, P. (2024). The impact of ChatGPT feedback on the development of EFL students’ writing skills. Cogent Education, 11(1). https://doi.org/10.1080/2331186X.2024.2410101 · DOI
  52. Romero-Rodríguez, J.-M., Ramírez-Montoya, M.-S., Buenestado-Fernández, M., & Lara-Lara, F. (2023). Use of ChatGPT at university as a tool for complex thinking: Students’ perceived usefulness. Journal of New Approaches in Educational Research, 12(2), 323–339. https://doi.org/10.7821/naer.2023.7.1458 · DOI · Paper page
  53. Sallam, M., Elsayed, W., Al-Shorbagy, M., Barakat, M., El Khatib, S., Ghach, W., Alwan, N., Hallit, S., & Malaeb, D. (2024). ChatGPT usage and attitudes are driven by perceptions of usefulness, ease of use, risks, and psycho-social impact: A study among university students in the UAE. Frontiers in Education, 9, Article 1414758. https://doi.org/10.3389/feduc.2024.1414758 · DOI
  54. Sindermann, C., Yang, H., Elhai, J. D., Yang, S., Quan, L., Li, M., & Montag, C. (2022). Acceptance and fear of artificial intelligence: Associations with personality in a German and a Chinese sample. Discover Psychology, 2(1). https://doi.org/10.1007/s44202-022-00020-y · DOI · Paper page
  55. Slamet, J. (2024). Potential of ChatGPT as a digital language learning assistant: EFL teachers’ and students’ perceptions. Discover Artificial Intelligence, 4(1), 46. https://doi.org/10.1007/s44163-024-00143-2 · DOI · Paper page
  56. Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: Assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14, Article 1260843. https://doi.org/10.3389/fpsyg.2023.1260843 · DOI · Paper page
  57. Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, https://doi.org/10.1016/j.asw.2023.100752 · DOI
  58. Teng, M. F. (2024). ‘ChatGPT is the companion, not enemies’: EFL learners’. perceptions and experiences in using ChatGPT for feedback in writing. Computers and Education, 7, Article 100270. https://doi.org/10.1016/j.caeai.2024.100270 · DOI · Paper page
  59. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 · DOI · Paper page
  60. Vo, T. K. A., & Nguyen, H. (2024). Generative artificial intelligence and ChatGPT in language learning: EFL students’ perceptions of technology acceptance. Journal of University Teaching and Learning Practice, 21(6). https://doi.org/10.53761/fr1rkj58 · DOI
  61. Warschauer, M., & Xu, Y. (2024). Generative AI for language learning: Entering a new era. Language Learning and Technology, 28(2), 1–4. https://hdl.handle.net/10125/73569
  62. Weidener, L., & Fischer, M. (2023). Teaching AI ethics in medical education: A scoping review of current literature and practices. Perspectives on Medical Education, 12(1), 399–410. https://doi.org/10.5334/pme.954 · DOI · Paper page
  63. Marzuki, , Widiati, U., Rusdin, D., Darwin, , & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2). https://doi.org/10.1080/2331186X.2023.223646 · DOI
  64. Xiao, Y., & Zhi, Y. (2023). An exploratory study of EFL learners’ use of ChatGPT for language learning tasks: Experience and perceptions. Languages, 8(3), 212. https://doi.org/10.3390/languages8030212 · DOI · Paper page
  65. Xiong, H. (2024). Research on confusing responses based on ChatGPT. Applied and Computational Engineering, 57(1), 90–97. https://doi.org/10.54254/2755-2721/57/20241315 · DOI
  66. Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies, 28(11), 13943–13967. https://doi.org/10.1007/s10639-023-11742-4 · DOI · Paper page
  67. Yilmaz, H., Maxutov, S., Baitekov, A., & Balta, N. (2023). Student attitudes towards ChatGPT: A technology acceptance model survey. International Educational Review, 1(1), 57–83. https://doi.org/10.58693/ier.114 · DOI
  68. Yildiz, C. (2024). ChatGPT integration in EFL education: A path to improved speaking self-efficacy. Novitas-ROYAL (research on Youth and language), 18(2), 167–182.
  69. Zhang, B., Zhu, Y., Deng, J., Zheng, W., Liu, Y., Wang, C., & Zeng, R. (2023). ‘I am here to assist your tourism’: Predicting continuance intention to use AI-based chatbots for tourism. Does gender really matter? International Journal of Human-Computer Interaction, 39(9), 1887–1903. https://doi.org/10.1080/10447318.2022.2124345 · DOI
  70. Zhu, M., & Wang, C. (2025). A systematic review of artificial intelligence in language education: Current status and future implications. Language Learning and Technology, 29(1), 1–29. https://hdl.handle.net/10125/73606
  71. Zhou, Y., Wu, X., & Qu, K. (2024). The role of ChatGPT in English language learning: A hedonic motivation perspective on student adoption in Chinese universities. Language Teaching Research Quarterly, 43, 132–154. https://doi.org/10.32038/ltrq.2024.43.08 · DOI

Cited by

Sorted by citations

Related

Authors
Alghasab, M.
Corresponding author
Alghasab, Maha
ORCID
Alghasab, Maha
Venue
Educational Process International Journal
Publisher
Universitepark
Published
2025
Volume
18
Issue
1
ISSN
  • 2147-0901 (ISSN-L)
  • 2564-8020
DOI
10.22521/edupij.2025.18.507
OpenAlex
W7084912657
Cited by
0
References
0
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Educational Process International Journal (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
Keywords
ChatGPT, EFL learners, technology acceptance, perceived usefulness, perceived ease of use, behavioral intention, gender differences, attitudes toward AI, English language learning

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review