The DOI matches its Crossref record, with a small difference in title or year; 55 of the 57 references it cites were found in a registry or an index, and 2 are not checked yet.
Teachers’ attitudes towards chatbots in education: a technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics
Open accessAbstract
The appearance of Artificial Intelligence implementations, such as text-based virtual assistants (chatbots) in education is relatively new. These implementations can be useful for helping teachers and students to solve both educational questions and routine tasks. This paper examines the factors that explain teachers’ acceptance of chatbots through the dimensions of the Technology Acceptance Model (perceived usefulness and perceived ease of use), its conversational design (use of social language and proactiveness), and the teachers’ age and digital skills. The data collection process included a pre-test and an online survey with four different types of chatbots. We analyse 225 responses of primary and secondary education teachers. The results show that the perceived easiness and perceived usefulness leads to greater acceptance of chatbots. As for the chatbots’ features, formal language by a chatbot leads to a higher intention of using them. These results can help in chatbot design and communication decisions, improving the acceptance of the educational community.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Introductory Econometrics: A Modern Approach
Wooldridge, J. M. (1999) · Cited by 14,354
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
Proceedings for the Annual Meeting of the Cognitive Science Society
Dziemianko, M., Clarke, A. D. F., & Keller, F. (2013) · Cited by 1,726
Task-Dependent Algorithm Aversion
Castelo, N., Bos, M. W., & Lehmann, D. R. (2019) · Springer eBooks · doi:10.1007/978-3-031-88067-4_21 · Cited by 1,723
Task-Dependent Algorithm Aversion
Castelo, N., Bos, M. W., & Lehmann, D. R. (2019) · Journal of Marketing Research · doi:10.1177/0022243719851788 · Cited by 1,500
European Framework for the Digital Competence of Educators: DigCompEdu
(2017) · RePEc: Research Papers in Economics · doi:10.2760/178382 · Cited by 1,276
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019) · Marketing Science · doi:10.1287/mksc.2019.1192 · Cited by 1,262 · cited 1×
“Luo et al. (2019) define chatbots as computer programs that simulate human conversations using natural languages through voice or text commands and serve as virtual assistants to users.”
Background
Research works printed but not linked: 6
- Baron N. S., 2003, The Stanford Handbook for Language Engineers, e dited by A. Farghali,, 59
- Bii P., 2013, Educational Research, 4, 218
- Gulz A., 2004, International Journal of Artificial Intelligence in Education, 14, 313
- Heller B., 2005, EdMedia+ Innovate Learning, 3913
- 10.2760/159770 · DOI
- Xiao J., 2003, Proccedings of Interact 2003, 383
Cited by
Sorted by citations
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326
“Similar results concerning teachers attitudes towards chatbots in education were reported in [34]: perceiving the AI chatbot as easy-to-use and useful leads to greater acceptance of the chatbot.”
ResultCelik, I. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107468 · Cited by 1,012
Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2151730 · Cited by 688
Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023) · Information Systems Frontiers · doi:10.1007/s10796-022-10291-4 · Cited by 685
Metadata
- Authors
- Chocarro, R., Cortiñas, M., & Marcos-Matás, G.
- Affiliations
- Universidad Pública de Navarra (UPNA) (ES)
- Departamento Gestión de Empresas, Universidad Pública de Navarra, Pamplona, Spain
- Corresponding author
- Cortiñas, Mónica
- Venue
- Educational Studies
- Publisher
- Informa UK Limited
- Published
- 2021-02-04
- Volume
- 49
- Issue
- 2
- Pages
- 295-313
- ISSN
- 0305-5698 (ISSN-L)
- 1465-3400
- OpenAlex
- W3126219458
- Cited by
- 343
- References
- 55
- Citations by year
- 2026: 49 · 2025: 93 · 2024: 115 · 2023: 56 · 2022: 23 · 2021: 7
- FWCI
- 17.76
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- Educational Studies (publishedVersion)
- Academica-e (Universidad Pública de Navarra) (submittedVersion, other-oa)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- chatbots, teacher attitudes, technology acceptance model, perceived usefulness, perceived ease of use, social language, conversational design, chatbot design, digital skills, age differences, basic education teachers, intention to use
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
