Sep 2026· Arab World English Journal· 0 citations· 33 references
Ethics and Social Impacts of AI
TL;DR
Qualitative findings corroborated a persistent awareness–practice gap, student over-reliance on AI, and inadequate institutional scaffolding, and recommends urgent development of context-specific, human-centered AI governance frameworks that bridge individual ethical awareness and institutional policy action.
Abstract
This study investigates English as a Foreign Language (EFL) teachers’ perceptions of ethical artificial intelligence (AI) use in teaching, learning, and assessment within an Omani higher education context. Despite rapid AI adoption in education, institutional governance frameworks remain critically underdeveloped, particularly in EFL contexts — creating an urgent need for empirical, locally grounded research. Using a convergent mixed-methods design, quantitative data were collected from 52 EFL faculty members through a structured 52-item Likert-scale questionnaire, complemented by focus group discussions with nine purposively selected teachers drawn from the same participant pool. Analysis across five constructs revealed high levels of AI literacy and ethical awareness (M = 4.09), ethical responsibility and academic integrity (M = 4.19), and positive pedagogical engagement (M = 4.11). The most critical finding was a significant institutional policy deficit reflected in the lowest construct mean (M = 3.25), with the majority of participants reporting an absence of clear guidelines, consequences, or detection tools. Future orientation and framework acceptance recorded the highest mean (M = 4.30), with 98.1% of participants endorsing formal adoption of an Ethical AI Responsibility (E.A.R.) framework. Qualitative findings corroborated a persistent awareness–practice gap, student over-reliance on AI, and inadequate institutional scaffolding. The study recommends urgent development of context-specific, human-centered AI governance frameworks that bridge individual ethical awareness and institutional policy action, with particular relevance to Omani and comparable EFL higher education contexts.
A Self-Perceived Ethical Knowledge Scale for Chinese preservice preschool teachers based on the eight ethics-related dimensions of TPCEK is adapted and validated, providing a context-specific instrument for assessing self-perceived ethical knowledge among preservice preschool teachers in AI-enhanced teacher education.
This study sought to investigate the perceptions of EFL teachers in Saudi Arabia regarding the benefits, challenges, ethical implications, and institutional support necessary to adopt AI-integrated English learning platforms. Using a quantitative, descriptive survey design, a structured online questionnaire was develop...
H. Al-Johani· Theory and Practice in Langu...· 0 citations
Generative artificial intelligence tools such as ChatGPT are increasingly reshaping teaching, learning, and assessment practices in higher education. This study examines the use of ChatGPT in academic assessments among pre-service teachers in four Federal Colleges of Education in Southwest Nigeria. Adopting a qualitati...
Adekunle Emmanuel Makanjuola, Blessing Mary Aninkan, Titilayo Omobolanle Onajide et al.· Shodh Sari-An International...· 0 citations
The emergence and development of generative AI tools have benefited higher education but have also created several ethical tensions in the educational system. This tension is higher in online teaching environments, where students often rely on AI tools. Previous studies have addressed ethical issues, yet how these issu...
Bao-Yi Wang, Farman Ullah Khan· Frontiers in Psychology· 0 citations
The findings of this paper call for AI literacy and capacity-building workshops, clear guidelines for the ethical use of AI, and mentorship, collaboration, and community engagement to advance AI adoption among students.
F. Ravhuhali· Journal of Education and Lea...· 0 citations
This study addresses the underexplored intersection of artificial intelligence (AI) tools and intercultural communicative competence (ICC) in Kazakhstan’s trilingual EFL context. The main focus is on comparing the frequency of traditional and AI-mediated ICC practices among EFL teachers and examining their qualitative...
K. Assan, S. Kunanbayeva, I. Derijan· Pedagogical Bulletin of Kaza...· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.