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          <dc:title>Unlocking the Potential of AI-Enhanced Mixed Reality: Enhancing Technical English Proficiency for Engineering Students in the Gulf Region</dc:title>
          <dc:creator>Shafiq ur Rehman (21430457)</dc:creator>
          <dc:creator>Rabia Khatoon (9970090)</dc:creator>
          <dc:creator>Intakhab Alam Khan (24518810)</dc:creator>
          <dc:subject>Education</dc:subject>
          <dc:subject>Education systems</dc:subject>
          <dc:subject>Information and computing sciences</dc:subject>
          <dc:subject>Human-centred computing</dc:subject>
          <dc:subject>Artificial intelligence</dc:subject>
          <dc:subject>Engineering</dc:subject>
          <dc:subject>English for specific purposes</dc:subject>
          <dc:subject>English proficiency</dc:subject>
          <dc:subject>Gulf countries</dc:subject>
          <dc:subject>Human-computer interaction</dc:subject>
          <dc:subject>Immersive learning environments</dc:subject>
          <dc:subject>Mixed reality</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This study examines the influence of artificial intelligence (AI) augmented mixed reality (MR) technologies on the enhancement of technical English proficiency among engineering students in the Gulf countries. The main aim of the research is to explore how the gap between foreign language learning and domain-specific technical knowledge can be reduced by integrating the immersive and adaptive MR environments with AI. The mixed method design was used to evaluate the effectiveness of AI-enhanced MR technologies in a 12-week course. The sample size consists of 300 students from the Gulf region. The treatment group used AI-enhanced MR technologies, which simulated real-life engineering scenarios to facilitate content-based English learning. The quantitative data from the pre-and post-tests revealed higher proficiency with the mean score of 72.5 to 80.3 that shows a medium-to-large statistically significant improvement. The qualitative data indicated enhanced engagement, confidence, and understanding of technical vocabulary. The study’s results suggest that AI-driven MR applications provide an practical pedagogical approach for advancing English for Specific Purposes (ESP), particularly within a Science, Technology, Engineering, and Mathematics (STEM) setting. Technical issues, usability problems, and misalignment with culture were highlighted as challenges. Improving the technical support and cultural appropriateness of the content would address these challenges. The study’s significance is shown through its contribution to practical pedagogical strategies by combining AI and MR for ESP instruction in the engineering context. It also reflects that these technologies can be effective in other fields.&lt;/p&gt;&lt;h2 dir="ltr"&gt;Other Information&lt;/h2&gt;&lt;p dir="ltr"&gt;Published in: Arab World English Journal&lt;br&gt;License: &lt;a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" target="_blank" rel="noreferrer noopener"&gt;h&lt;/a&gt;&lt;a href="https://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank" rel="noreferrer noopener"&gt;ttps://creativecommons.org/licenses/by-nc-nd/4.0/&lt;/a&gt;&lt;br&gt;See article on publisher's website: &lt;a href="https://dx.doi.org/10.24093/awej/vol16no4.10" target="_blank"&gt;https://dx.doi.org/10.24093/awej/vol16no4.10&lt;/a&gt;&lt;/p&gt;</dc:description>
          <dc:date>2025-12-10T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
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          <dc:identifier>10.24093/awej/vol16no4.10</dc:identifier>
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          <dc:rights>CC BY-NC-ND 4.0</dc:rights>
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