Understanding user trust in artificial intelligence‐based educational systems: Evidence from China

Qin, Fen; Li, Kai; Yan, Jianyuan

doi:10.1111/bjet.12994

Cited by 82 publications

(47 citation statements)

References 36 publications

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“…Users demand a personalized interface, giving them freedom to personalize their own device, deciding the way to show the feedback. Virtual profile of IPA would be shown also in the future, strengthening the perception of trustworthiness due to the great influence of the anthropomorphic look of the agent toward trust in human‐IPA (Qin et al, 2020; Rheu et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

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Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant

Huang

2021

Proceedings of the Association for Information Science and Tech

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Trust greatly contributes to human-AI collaboration, however, human's trust to IPA is hard to establish and lacks exploration. The purpose of this paper is to recognize the factors that affect the trustworthiness of IPA. 358 questionnaires were analyzed by PLS-SEM to construct the model, while thematic analysis was used to discover expectance of IPA. Chi-square tests and T-test were used to distinguish the difference between two user groups. Three factors that capability of system, personality of agent, and availability of interface have a significant impact on the trustworthiness of IPA. The capability of system is the most essential as the threshold with users' plenty of expectations. Most users pay less attention to the availability of interface and the personality of agent has a great impact on the trustworthiness of IPA. The factors found enrich the trusted AI research and inspire insights of design of IPA.

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Section: Discussionmentioning

confidence: 99%

“…Nowadays human‐center study has developed to explore trust building in human‐AI. Trust building in various systems was considered to gain insights into future AI product design (Hengstler et al, 2016; Qin et al, 2020). Difficulty, performance and results of tasks contributed to the perceived trust evaluation (Bitkina et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant

Huang

2021

Proceedings of the Association for Information Science and Tech

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“…El uso de la TD en el aula se ha ayudado de la inteligencia artificial como propuesta metodológica e innovación con el fin de proporcionar un aprendizaje personalizado y maximizar sus posibilidades. De este modo, imitando al ente humano, la inteligencia artificial ha permitido la creación de sistemas que aprenden del entorno y presentan conductas inteligentes y adaptables según las respuestas de los alumnos, a través de tutorías inteligentes, entornos de aprendizaje inteligente o robots educativos (Qin et al, 2020).…”

Section: Relación De Códigos Establecidos Junto Sus Frecuenciasunclassified

Estrategias para la Transformación Digital de un Centro Educativo: una revisión sistemática

Grau

Valls²,

Cantabrana³

2022

RiiTE

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The use of digital technology favors the development of the teaching and learning process of the student and the transfer of information to the entire educational community. This study aims to identify the actions and mechanisms that an educational institution must take into account in its digital transformation through the use of digital technology. This research is approached as a systematic review based on the PRISMA 2020 model, between January 2011 and February 2021. In the study, after applying the different inclusion criteria in 69 references, the analysis of 13 publications is carried out. Through the ATLAS.ti software. 9.1.3 (2089), a content study is carried out based on the established codes. The main result of this sistematic review indicates that an educational institution must know the degree of digital maturity of all its components (students, teachers and center) and the state of its infrastructure. This knowledge is necessary in the implementation of strategic plans to improve the use of digital technology, both at a methodological and instrumental level, and thus facilitate digital transformation at the level of infrastructure, digital competence of teachers and digital competence of students through didactic methodologies that facilitate it together with digital inclusion. El uso de la tecnología digital favorece el desarrollo del proceso de enseñanza-aprendizaje del alumno y la transferencia de información a toda la comunidad educativa. El presente estudio pretende identificar las acciones y los mecanismos que debe tener en cuenta una institución educativa en su transformación digital a través del uso de la tecnología digital. Esta investigación se aborda como una revisión sistemática basada en el modelo PRISMA 2020, entre enero de 2011 y febrero de 2021. En el estudio, después de aplicar los distintos criterios de inclusión en 69 referencias, se realiza el análisis de 13 publicaciones. A través del software ATLAS.ti. 9.1.3 (2089), se realiza un estudio de contenido a partir de los códigos establecidos. El principal resultado de esta revisión sistemática indica que una institución educativa debe conocer el grado de madurez digital de todos sus componentes (alumnos, docentes y centro) y el estado de su infraestructura. Este conocimiento resulta necesario en la implementación de planes estratégicos para mejorar el uso de la tecnología digital, tanto a nivel metodológico como instrumental, y así facilitar la transformación digital a nivel de infraestructuras, de competencia digital del profesorado y de competencia digital del alumnado a través de metodologías didácticas que la faciliten junto a la inclusión digital.

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“…As far as we know, some infrastructure designs on AI in education can be found [45][46][47][48], but no study case supports a TAI system. Some systems focus on security [49], explainability [50], privacy [51], ethics [52], fairness [53], human well-being [54], and trust [55]. Some of the previous works even analyze together different requirements related to a TAI system at once.…”

Section: Related Workmentioning

confidence: 99%

A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System

et al. 2021

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Learning analytics is quickly evolving. Old fashioned dashboards with descriptive information and trends about what happened in the past are slightly substituted by new dashboards with forecasting information and predicting relevant outcomes about learning. Artificial intelligence is aiding this revolution. The accessibility to computational resources has increased, and specific tools and packages for integrating artificial intelligence techniques leverage such new analytical tools. However, it is crucial to develop trustworthy systems, especially in education where skepticism about their application is due to the risk of teachers’ replacement. However, artificial intelligence systems should be seen as companions to empower teachers during the teaching and learning process. During the past years, the Universitat Oberta de Catalunya has advanced developing a data mart where all data about learners and campus utilization are stored for research purposes. The extensive collection of these educational data has been used to build a trustworthy early warning system whose infrastructure is introduced in this paper. The infrastructure supports such a trustworthy system built with artificial intelligence procedures to detect at-risk learners early on in order to help them to pass the course. To assess the system’s trustworthiness, we carried out an evaluation on the basis of the seven requirements of the European Assessment List for trustworthy artificial intelligence (ALTAI) guidelines that recognize an artificial intelligence system as a trustworthy one. Results show that it is feasible to build a trustworthy system wherein all seven ALTAI requirements are considered at once from the very beginning during the design phase.

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Understanding user trust in artificial intelligence‐based educational systems: Evidence from China

Cited by 82 publications

References 36 publications

Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant

Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant

Estrategias para la Transformación Digital de un Centro Educativo: una revisión sistemática

A Predictive Analytics Infrastructure to Support a Trustworthy Early Warning System

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