Litcius/Paper detail

Artificial intelligence in Jordanian education: Assessing acceptance via perceived cybersecurity, novelty value, and perceived trust

Mazen Alzyoud, Najah Al-shanableh, Saleh Al-Omar, As’ad Mahmoud As’adAlnaser, Akram Mustafad, Ala’a M. Al-Momani, Sulieman Ibraheem Shelash Al-Hawary

2024International Journal of Data and Network Science89 citationsDOIOpen Access PDF

Abstract

The growing significance of Artificial Intelligence (AI) across different fields highlights the essential role of user acceptance, as the success of this technology largely depends on its adoption and practical use by individuals. This research aims to examine how perceived cybersecurity, novelty value, and perceived trust affect students' willingness to accept AI in educational settings. The study's theoretical basis is the AI Device Use Acceptance (AIDUA) model. Using structural equation modeling, the study tested hypothesized relationships using data from 526 students at Jordanian universities. The results showed that social influence is positively associated with performance expectancy, while perceived cybersecurity is positively related to both performance and effort expectancy. Novelty value is positively associated with performance expectancy but a negative one with effort expectancy. Additionally, effort and performance expectancy significantly influence perceived trust and the willingness to accept AI. Moreover, perceived trust has a notable positive effect on the willingness to accept AI in education. These findings provide valuable guidance for the creation and improvement of AI-driven educational systems in universities, contributing to the broader understanding of AI technology acceptance in the educational field.

Topics & Concepts

NoveltyExpectancy theoryUnified theory of acceptance and use of technologyStructural equation modelingPsychologyValue (mathematics)Technology acceptance modelAffect (linguistics)Social psychologySocial influenceField (mathematics)Applied psychologyKnowledge managementComputer scienceUsabilityHuman–computer interactionCommunicationPure mathematicsMachine learningMathematicsOrganizational and Employee PerformanceTechnology Adoption and User BehaviourImpact of AI and Big Data on Business and Society