Understanding User Trust in Artificial Intelligence-Based Educational Systems: Evidence from China

Autor/inn/en	Qin, Fen; Li, Kai; Yan, Jianyuan
Titel	Understanding User Trust in Artificial Intelligence-Based Educational Systems: Evidence from China
Quelle	In: British Journal of Educational Technology, 51 (2020) 5, S.1693-1710 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.12994
Schlagwörter	Trust (Psychology); Artificial Intelligence; Classification; Context Effect; Intelligent Tutoring Systems; Teacher Competencies; Knowledge Level; Learning Processes; Personal Autonomy; Teacher Student Relationship; Ethics; Foreign Countries; Technological Literacy; Usability; Individual Characteristics; Teaching Methods; Student Attitudes; China + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Classification system; Klassifikation; Klassifikationssystem; Intelligentes Tutorsystem; Lehrkunst; Wissensbasis; Learning process; Lernprozess; Individuelle Autonomie; Teacher student relationships; Lehrer-Schüler-Beziehung; Ethik; Ausland; Technisches Wissen; Personality characteristic; Personality traits; Persönlichkeitsmerkmal; Teaching method; Lehrmethode; Unterrichtsmethode; Schülerverhalten
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01