Faculty readiness for AI-driven digital transformation in Omani higher education: examining the attitudes -usage gap

Background Artificial intelligence (AI) is fundamentally transforming higher education by enhancing pedagogical efficiency and administrative productivity. However, empirical evidence regarding faculty readiness and adoption patterns remains scarce within the Middle Eastern context. Objective This study investigated the levels of AI familiarity, usage patterns, and attitudes among faculty at the University of Buraimi, Oman, and examined the correlations between these variables to inform institutional policy. Method Utilizing a quantitative, cross-sectional design, a validated online questionnaire was distributed to 92 faculty members ( n = 92) across four academic colleges. The instrument assessed AI familiarity, usage, and attitudes on a 7-point Likert scale (Cronbach's alpha = .857). Data were analyzed using descriptive statistics and Pearson correlation coefficients. Results Participants exhibited moderate levels of AI familiarity (M = 24.84, SD = 4.92) and usage (M = 22.47, SD = 5.80), while maintaining notably positive attitudes toward AI integration (M = 50.12, SD = 8.34). Significant positive correlations were identified between AI familiarity and usage ( r = .573, p < .001), familiarity and attitude ( r = .427, p < .001), and usage and attitude ( r = .473, p < .001). These findings indicate a significant “willingness-usage gap”, where positive attitudes precede technical proficiency. Conclusion The results suggest that faculty familiarity and practical experience are primary determinants of technology acceptance. To align with the digital transformation goals of Oman Vision 2040, higher education institutions should prioritize role-specific AI literacy programs and robust institutional support frameworks to bridge the gap between psychological readiness and practical application. These findings highlight a contextualized “willingness–usage gap”, where positive psychological readiness precedes technical proficiency, offering institution-level strategic insight.

Authors

Institutions

Publication Details

Journal
Frontiers in Education
Published
2026-04-22
DOI
https://doi.org/10.3389/feduc.2026.1774840
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Faculty readiness for AI-driven digital transformation in Omani higher education: examining the attitudes -usage gap

Thilagavathi Krishnasamy, Jansirani Natarajan, Vidya Seshan, Janitha Plackal Ayyappan et al.
Frontiers in Education
Artificial Intelligence in Healthcare and Education
article

Faculty readiness for AI-driven digital transformation in Omani higher education: examining the attitudes -usage gap

Thilagavathi Krishnasamy, Jansirani Natarajan, Vidya Seshan, Janitha Plackal Ayyappan, Kirti Sharma
article en

Abstract

Background Artificial intelligence (AI) is fundamentally transforming higher education by enhancing pedagogical efficiency and administrative productivity. However, empirical evidence regarding faculty readiness and adoption patterns remains scarce within the Middle Eastern context. Objective This study investigated the levels of AI familiarity, usage patterns, and attitudes among faculty at the University of Buraimi, Oman, and examined the correlations between these variables to inform institutional policy. Method Utilizing a quantitative, cross-sectional design, a validated online questionnaire was distributed to 92 faculty members ( n = 92) across four academic colleges. The instrument assessed AI familiarity, usage, and attitudes on a 7-point Likert scale (Cronbach's alpha = .857). Data were analyzed using descriptive statistics and Pearson correlation coefficients. Results Participants exhibited moderate levels of AI familiarity (M = 24.84, SD = 4.92) and usage (M = 22.47, SD = 5.80), while maintaining notably positive attitudes toward AI integration (M = 50.12, SD = 8.34). Significant positive correlations were identified between AI familiarity and usage ( r = .573, p < .001), familiarity and attitude ( r = .427, p < .001), and usage and attitude ( r = .473, p < .001). These findings indicate a significant “willingness-usage gap”, where positive attitudes precede technical proficiency. Conclusion The results suggest that faculty familiarity and practical experience are primary determinants of technology acceptance. To align with the digital transformation goals of Oman Vision 2040, higher education institutions should prioritize role-specific AI literacy programs and robust institutional support frameworks to bridge the gap between psychological readiness and practical application. These findings highlight a contextualized “willingness–usage gap”, where positive psychological readiness precedes technical proficiency, offering institution-level strategic insight.

Frontiers in EducationVol. 11
Australian College of Nursing (AU), University of Sharjah (AE), University of Buraimi (OM)
Openalex Percentile: Top 19%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.