Determinants of Chatbot Brand Trust in the Adoption of Generative Artificial Intelligence in Higher Education
Zapisane w:
| Wydane w: | Education Sciences vol. 15, no. 10 (2025), p. 1389-1413 |
|---|---|
| 1. autor: | |
| Kolejni autorzy: | , , , , |
| Wydane: |
MDPI AG
|
| Hasła przedmiotowe: | |
| Dostęp online: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Etykiety: |
Nie ma etykietki, Dołącz pierwszą etykiete!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3265872315 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2227-7102 | ||
| 022 | |a 2076-3344 | ||
| 024 | 7 | |a 10.3390/educsci15101389 |2 doi | |
| 035 | |a 3265872315 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231457 |2 nlm | ||
| 100 | 1 | |a Falebita, Oluwanife Segun |u Mathematics, Science and Technology Education Department, Faculty of Education, University of Zululand, KwaDlangezwa 3886, Richards Bay Private Bag X1001, South Africa; abahj@unizulu.ac.za (J.A.A.); asanrea@unizulu.ac.za (A.A.A.) | |
| 245 | 1 | |a Determinants of Chatbot Brand Trust in the Adoption of Generative Artificial Intelligence in Higher Education | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The use of generative artificial intelligence (GenAI) chatbots in brands is growing exponentially, and higher education institutions are not unaware of how such tools effectively shape the attitudes and behavioral intentions of students. These chatbots are able to synthesize an enormous amount of data input and can create contextually aware, human-like conversational content that is not limited to simple scripted responses. This study examines the factors that determine chatbot brand trust in the adoption of GenAI in higher education. By extending the Technology Acceptance Model (TAM) with the construct of brand trust, the study introduces a novel contribution to the literature, offering fresh insights into how trust in GenAI chatbots is developed within the academic context. Using the convenience sampling technique, a sample of 609 students from public universities in North Central and Southwestern Nigeria was selected. The collected data were analyzed via partial least squares structural equation modelling. The results indicated that attitudes toward chatbots determine behavioral intentions and GenAI chatbot brand trust. Surprisingly, behavioral intentions do not affect GenAI chatbot brand trust. Similarly, the perceived ease of use of chatbots does not determine behavioral intention or attitudes toward GenAI chatbot adoption but rather determines perceived usefulness. Additionally, the perceived usefulness of chatbots affects behavioral intention and attitudes toward GenAI chatbot adoption. Moreover, social influence affects behavioral intention, perceived ease of use, perceived usefulness and attitudes toward GenAI chatbot adoption. The implications of the findings for higher education institutions are that homegrown GenAI chatbots that align with the principles of the institution should be developed, creating an environment that promotes a positive attitude toward these technologies. Specifically, the study recommends that policymakers and university administrators establish clear institutional guidelines for the design, deployment, and ethical use of homegrown GenAI chatbots, ensuring alignment with educational goals and safeguarding student trust. | |
| 653 | |a Behavior | ||
| 653 | |a Higher education | ||
| 653 | |a Accuracy | ||
| 653 | |a Educational technology | ||
| 653 | |a University students | ||
| 653 | |a Distance learning | ||
| 653 | |a Generative artificial intelligence | ||
| 653 | |a Chatbots | ||
| 653 | |a Personalized learning | ||
| 653 | |a Decision making | ||
| 653 | |a Technology Acceptance Model | ||
| 653 | |a Attitudes | ||
| 653 | |a Structural equation modeling | ||
| 653 | |a Policy making | ||
| 653 | |a Brands | ||
| 653 | |a Literature Reviews | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Educational Change | ||
| 653 | |a Access to Information | ||
| 653 | |a Beliefs | ||
| 653 | |a Intention | ||
| 653 | |a Educational Objectives | ||
| 653 | |a Electronic Learning | ||
| 653 | |a Artificial Intelligence | ||
| 653 | |a Data Analysis | ||
| 653 | |a Social Influences | ||
| 653 | |a Outcomes of Education | ||
| 653 | |a Language Processing | ||
| 653 | |a Learner Engagement | ||
| 700 | 1 | |a Abah Joshua Abah |u Mathematics, Science and Technology Education Department, Faculty of Education, University of Zululand, KwaDlangezwa 3886, Richards Bay Private Bag X1001, South Africa; abahj@unizulu.ac.za (J.A.A.); asanrea@unizulu.ac.za (A.A.A.) | |
| 700 | 1 | |a Ayoola, Asanre Akorede |u Mathematics, Science and Technology Education Department, Faculty of Education, University of Zululand, KwaDlangezwa 3886, Richards Bay Private Bag X1001, South Africa; abahj@unizulu.ac.za (J.A.A.); asanrea@unizulu.ac.za (A.A.A.) | |
| 700 | 1 | |a Abiodun Taiwo Oluwadayo |u Department of Mathematics, Tai Solarin University of Education, Ijebu Ode P.M.B 2118, Nigeria; abiodunto@tasued.edu.ng | |
| 700 | 1 | |a Ayanwale, Musa Adekunle |u Department of Mathematics, Science and Technology Education, University of Johannesburg, Auckland Park, Johannesburg P.O. Box 524, South Africa; ayanwalea@uj.ac.za | |
| 700 | 1 | |a Ayanwoye, Olubunmi Kayode |u Science Education Department, Faculty of Education, Federal University Oye-Ekiti, Oye P.M.B. 373, Nigeria; olubunmi.ayanwoye@fuoye.edu.ng | |
| 773 | 0 | |t Education Sciences |g vol. 15, no. 10 (2025), p. 1389-1413 | |
| 786 | 0 | |d ProQuest |t Education Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3265872315/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3265872315/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3265872315/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |