Document Type

Article

Source of Publication

Journal of Intelligent Decision Making and Information Science

Publication Date

8-1-2026

Abstract

This study aimed to develop a predictive longitudinal model of the psychological and technical factors influencing the use of artificial intelligence tools among non-native Arabic learners (international students) in three Arab countries: Egypt, the Kingdom of Saudi Arabia, and Jordan. The study adopted an extended Technology Acceptance Model (TAM) incorporating two psychological variables: trust in artificial intelligence and artificial intelligence anxiety. A quantitative longitudinal design with two time waves (T1 and T2) over a full academic semester was employed using Hierarchical Multiple Regression Analysis and PROCESS Macro for mediation. The sample consisted of 812 international students from public universities in the three countries. Six validated instruments were administered at T1 (Perceived Usefulness, Perceived Ease of Use, Trust in AI, AI Anxiety, Attitude toward Use) and T2 (Actual Use, including a behavioral frequency item). The results indicated that T1 perceived usefulness (β = 0.37), perceived ease of use (β = 0.26), and trust in AI (β = 0.28) significantly and positively predicted T1 attitudes, while T1 AI anxiety (β =-0.20) demonstrated a significant negative predictive effect. T1 attitude significantly predicted T2 actual use (β = 0.50). Bootstrapped mediation analysis (PROCESS) confirmed the significant indirect effects of trust and anxiety on T2 actual use through T1 attitudes. Little's MCAR test indicated that missing data were completely random, and no significant attrition bias was found. Hierarchical regression with dummy variables revealed significant cross-country differences. The study recommends enhancing early trust, reducing initial anxiety, and developing Arabic curricula to systematically integrate AI tools.

ISSN

3079-0875

Publisher

Auricle Technologies, Pvt., Ltd.

Volume

3

Issue

6s

First Page

760

Last Page

780

Disciplines

Computer Sciences | Linguistics

Keywords

Arabic Language Learning, Artificial Intelligence, Bootstrapping, Comparative Study, International Students, Longitudinal Design, Multiple Regression Analysis, PROCESS Macro, Technological Anxiety, Technology Acceptance Model, Trust

Scopus ID

105047492451

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Hybrid: This publication is openly available in a subscription-based journal/series

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