Exploring UAE Student Perspectives on Utilising AI Tools in Higher Education: A Quantitative Analysis

17 September 2025
Wafaa Elsawah; Muntaha Badawieh; Amer Alaya

Exploring UAE Student Perspectives on Utilising AI Tools in Higher Education: A Quantitative Analysis

Wafaa Elsawah1, Muntaha Badawieh2, Amer Alaya3

1 British University in Dubai; 0000-0002-9538-4697

2 British University in Dubai

3 University of Birmingham Dubai

This study investigates the factors influencing UAE higher education students' acceptance and usage of artificial intelligence (AI) tools. Drawing on the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB), the research explores how students perceive the ease of use, usefulness, subjective norms, and attitudes toward AI tools in their educational environment. A quantitative survey was conducted with 80 students from various UAE universities. The findings indicate that perceived usefulness and positive attitudes toward AI significantly predict students' behavioural intentions to adopt these technologies, while perceived ease of use and subjective norms play a less prominent role. These results suggest that UAE students prioritize the functional benefits of AI tools over ease of use or social pressures. This study offers valuable insights for policymakers, educators, and technology developers aiming to integrate AI in higher education, aligned with the UAE's strategic objectives for digital transformation. The findings underscore the importance of enhancing student engagement through targeted AI-driven educational tools and support systems.

Introduction and Background

The presentation focuses on how Artificial Intelligence (AI) is reshaping higher education globally and in the UAE. The UAE government has made AI a national priority through its AI Strategy 2031, aiming to position the country as a leader in AI adoption across sectors, including education. The higher education context in the UAE provides a unique environment for this study due to its diverse student population, advanced digital infrastructure, and strategic push towards a knowledge-based economy.

Despite the clear potential of AI, there remain gaps in understanding how students perceive and adopt these technologies. This study seeks to explore those factors to inform policy, teaching practices, and tool development.

Research Aim and Framework

The research aims to identify factors influencing UAE students’ adoption of AI tools in higher education, focusing on four key constructs:

  • Perceived Ease of Use (PEOU) – how easy students find AI tools to use.
  • Perceived Usefulness (PU) – the perceived academic value of AI tools.
  • Subjective Norms (SN) – the influence of peers and faculty.
  • Attitudes (ATT) – students’ personal feelings and evaluations toward AI.

The study integrates two widely used theoretical models:

  • Technology Acceptance Model (TAM), which highlights ease of use and usefulness as predictors of adoption.
  • Theory of Planned Behaviour (TPB), which adds attitudes, subjective norms, and behavioural intentions to explain user behaviour.

Hypotheses

Based on these frameworks, the study tests four hypotheses:

H1: Ease of use positively influences AI adoption.

H2: Usefulness positively influences AI adoption.

H3: Subjective norms positively influence AI adoption.

H4: Positive attitudes towards AI predict stronger adoption intentions.

Methodology

The research adopts a quantitative design, surveying over 80 higher education students across UAE universities. Data was collected through online questionnaires using a 5-point Likert scale to measure perceptions of ease of use, usefulness, subjective norms, attitudes, and behavioural intentions.

The data was analysed using Jamovi and WarpPLS software. These tools supported descriptive statistics, reliability and validity checks, and structural equation modelling to examine the relationships between the constructs.

Key Findings

The structural model explained 82% of the variance in students’ intention to adopt AI tools, a very strong explanatory power. The results are summarised below:

  • Perceived Usefulness was a significant predictor of AI adoption. Students who recognised clear academic benefits were more likely to use AI tools.
  • Attitudes were the strongest driver. Positive feelings and personal beliefs about AI had the greatest impact on behavioural intentions.
  • Ease of Use was not statistically significant, suggesting that UAE students may already be technologically proficient and prioritise functionality over simplicity.
  • Subjective Norms were also not significant, indicating that peer or faculty influence plays a limited role compared to individual attitudes and perceived benefits.

These findings challenge traditional assumptions about technology adoption. They suggest a shift in how UAE students evaluate educational technologies—placing more weight on usefulness and personal attitudes than on usability or social influence.

Practical Implications

The presentation highlights several implications:

  • For Institutions: Focus on adopting AI tools that offer clear, tangible benefits to students. This could mean integrating AI that improves personalised learning, automates administrative tasks, or enhances feedback mechanisms.
  • For Developers: Co-design tools with students and faculty to ensure alignment with real educational needs. Continuous feedback loops and pilot testing can increase adoption and satisfaction.
  • For Training: Implement programmes to foster positive attitudes towards AI. This involves demystifying the technology, showcasing successful use cases, and providing practical training to boost confidence.

Discussion

The study offers several insights:

  • The dominant role of perceived usefulness aligns with prior research showing that when students see clear academic value, their adoption rates increase. In the UAE context, this is strengthened by government strategies and advanced digital ecosystems.
  • The limited role of ease of use reflects a technologically mature student population that expects basic usability and focuses more on outcomes.
  • The weak influence of subjective norms may indicate cultural shifts in UAE higher education, with students becoming more individualistic and autonomous in their technology adoption decisions.
  • The central role of attitudes underscores the emotional and cognitive dimensions of technology adoption. Positive experiences and trust in AI can significantly boost willingness to use it.

Conclusion

The presentation concludes that perceived usefulness and attitudes are the key determinants of AI adoption among UAE higher education students. These insights have practical relevance for policymakers, educators, and developers aiming to integrate AI tools effectively into educational settings.

By understanding students’ perspectives, stakeholders can design strategies that leverage usefulness and foster positive attitudes, rather than focusing solely on usability or peer influence. This is particularly relevant in the UAE, where rapid digital transformation requires thoughtful alignment between technology, users, and educational goals.