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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.
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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 ›
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