Understanding user trust in artificial intelligence‐based educational systems
Evidence from China
Bibliographic Data
| ID | 21297503 |
|---|---|
| Authors | Fen Qin (0000-0001-5417-4442), Kai Li (0000-0001-6234-6806, Nankai University, corresponding author), Jianyuan Yan |
| Year | 2020 |
| Volume | 51 |
| Issue | 5 |
| Pages | 1693-1710 |
| Publication date | 2020-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Technology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1013 • E-ISSN: 1467-8535 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjet.12994 |
| OpenAlex | W3046786385 |
| Language | EN |
| Citations received | 49 |
| References cited | 35 |
Artificial Intelligence (AI) has penetrated the field of education. Trust has long been regarded as a driver for the acceptance of technology. Netnography and interviews were used to investigate trust in AI‐based educational systems from the perspective of users. We identified the factors influencing trust in AI‐based educational systems and categorized them as being related to technology, context and individual. Technology‐related factors encompass functionality, helpfulness, interpretability, dependability and interaction interface. Context‐related factors encompass benevolence of educational organizations, data management, teachers’ competencies, official norms and knowledge characteristics. Individual‐related factors encompass perception of the nature of learning, propensity to interact with teachers, perception of AI and autonomy orientation. The results from this paper will contribute to the literature on trust in technology and AI ethics in education
Autonomy · Context (archaeology) · Educational technology · Epistemology · Field (mathematics) · Helpfulness · Interpretability · Knowledge management · Operationalization · Pedagogy · Perception · Political science · Artificial Intelligence · Artificial Intelligence in Healthcare and Education · Computer Science · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology · Social Psychology
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| Unique citing works | 49 |
|---|---|
| Citations per year | 12,25 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 47 |