Elevate MENA: Showcasing effective practice in learning and teaching

Showcasing Innovative and Impactful Practice in Learning and Teaching in Higher Education in the Middle East and North Africa

Advance HE Member Benefit Project 2025-26

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Each submission is aligned to the 2023 Professional Standards Framework; the most relevant Dimensions are signposted in each case study of practice.

Innovations in learning and teaching to support access, retention, attainment and progression

Enhancing curricula to align with national visions

Embedding AI into learning, teaching and assessment practice to enhance student experience and outcomes

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Innovations in Learning and Teaching to Support Access, Retention, Attainment and Progression

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Dr Sana'a Al Reiahy When Learners Arrive Tired and Leave Energised: A Constructivist Redesign for Night-Time Postgraduate Classes

Dr Habil Slade Ogalo The Student Success Hub to Enhance Access, Retention, Attainment and Progression across a Diverse Student Population

Dr Ahmad Hosseini Transforming Student Success: The GCET Academic Support Centre Model

Dr Arina Ziganshina Integrating portfolio and mentorship in competency-based medical education

Mr Mostafa Youssef EmpowerEd BUE: Advancing Teaching and Learning Excellence

Dr Nora Maher A Structured Support Model for At-Risk Students in Political Science

Professor Mohammed Ghazal A Multi-Layered Student Success and Continuity Framework for Engineering Education at ADU

Dr Manjush Karthika Interprofessional Collaboration in Health Professions Education

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Enhancing Curricula to Align with National Visions

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Dr Noha Mostafa Egypt Vision 2030, Strategic Goal 4: Creating a Diversified, Knowledge-based, and Competitive Economy

Dr Ramalingam Dharmalingam Enhancing Curricula to Align with Oman National Visions: The BSc (Hons) Computing (Oil and Gas) Programme

Amol Ganesh Deshmukh Mapping RICS Competencies to Geomatics Academic Programme: A Framework for Professional Alignment

Dr Sameh Fawzy Elsonbaty Integrating National Health Priorities into the Basic Medical Sciences Curriculum

Dominic Hanratty Enhancing Aerospace Curriculum Using Virtual Reality for Gas Turbine Training

Dr Yurgos Politis Simulation as a metacognitive activity in a Research Design course

Professor Mohammed Ghazal A Nationally Aligned Model for Applied Engineering Learning Through Structured Design Challenges and Micro-credential Pathways

Dr Pamba Rajavarma Reimagining Computer Science Education in MENA: AI-Driven Curriculum and ACM 2030

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Embedding AI into Learning, Teaching and Assessment Practice to Enhance Student Experience and Outcomes

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Dr Constanine Andoniou Reimagining Computer Science Education in MENA: AI-Driven Curriculum and ACM 2030

Dr Neyara Radwan Integrating Artificial Intelligence Technologies into the Quality Assurance Process: Measuring and Verifying Learning Outcomes Using IBM Watson Analytics for Course Report Preparation

Professor Samar Ahmed Embedding AI for High-Quality Assessment: Rubric-Guided Custom GPT Assignment Feedback Assistants

Dr Amal Gadalla Aligning Learning Theories, Teaching Methodologies, and AI to Address Complex Medical Concepts

Prathiba Kristnapillai AI-Enhanced Learning to Support First-Year Electrical Engineering Students

Professor Mohammed Ghazal The AI4ALL Framework for Embedding AI Across Learning and Assessment

Dr Bacem Mbarek AI-Enhanced Peer Feedback to Improve Engagement and Learning Outcomes for Postgraduate Students

Dr Sofia Ligawen, Dexter Cadiente & Hawra Nooh Holistic AI Integration in Curriculum, Teaching-Learning, and Student Support

Mr Sadeq Telfah A Custom Large Language Model for Arabic Academic Feedback: Experimental Validation in the SSDEC Curriculum

Professor Mohammed Ahmed Hassanien EduAI Agent: A Practitioner-Built Ecosystem for AI-Augmented Assessment, Curriculum Quality and Accreditation in Higher Education

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Reimagining Computer Science Education in MENA: AI-Driven Curriculum and ACM 2030 Vision

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Innovation

This initiative transforms computer science education in the UAE by merging the ACM Computing Curricula framework with AI-driven pedagogy to create adaptive, ethical, and future-ready learning ecosystems. Traditional course structures often fail to address rapid technological changes and regional workforce needs. To overcome this, the approach introduces Dynamic Bundling, grouping courses into competency clusters such as AI and Ethics, Cybersecurity and Data Governance, and Cloud Computing and Scalable Systems. This fosters interdisciplinary learning and aligns education with the UAE’s innovation-driven economy. Two AI-powered features drive this transformation. The AI-Powered Curriculum Co-Designer analyzes industry trends, job market data, and student performance to recommend real-time curriculum updates, ensuring relevance and agility. The Ethical AI Learning Companion, integrated into learning platforms, delivers personalized learning paths, adaptive assessments, and real-time feedback while adhering to strict data ethics and governance principles. These innovations enhance student engagement, retention, and attainment while promoting responsible technology use. For UAE higher education, the impact is profound. The model addresses skill gaps, modernizes curricula, and supports national priorities such as the UAE AI Strategy 2031. It empowers faculty with AI tools for curriculum design and assessment, reducing administrative workload and enabling more focus on mentorship and research. Students gain future-ready skills and ethical awareness, preparing them for leadership in a digital economy. Implementation follows a phased roadmap: pilot programs in select universities, regional scaling with multilingual support, and policy integration with accreditation bodies. Key performance indicators include a 15% increase in retention within two years, quarterly AI-driven curriculum updates, and 80% faculty adoption of AI tools in the first year. By combining ACM standards with AI-enhanced pedagogy, this approach positions UAE universities as global leaders in innovative, ethical, and adaptive education.

Evidence of impact

The integration of the ACM framework with AI-driven tools has delivered measurable benefits to students and the institution. Dynamic course bundling and AI-powered curriculum updates have improved program relevance, resulting in a 15% increase in student retention during pilot implementation. Personalized learning through the Ethical AI Learning Companion enhanced engagement, with 80% of students reporting improved clarity in learning paths and adaptive assessments. Faculty adoption of AI tools reached 75% within the first year, reducing administrative workload and enabling more focus on research and mentorship. External stakeholders, including industry partners, provided positive feedback on graduates’ readiness for emerging roles in AI, cybersecurity, and cloud computing. Employers noted stronger interdisciplinary skills and ethical awareness, aligning with UAE’s AI Strategy 2031. Students expressed appreciation for real-time feedback and curriculum flexibility, citing improved confidence in job preparedness. These outcomes demonstrate that the innovation not only modernized curricula but also strengthened institutional reputation as a leader in adaptive, ethical, and future-ready education.

Contact: Dr Pamba Rajavarna pamba.rajavarma@manipaldubai.com

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Embedding AI for High-Quality Assessment: Rubric-Guided Custom GPT Assignment Feedback Assistants

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Innovation

As part of Rabdan Academy’s strategic shift toward AI-enhanced learning, we designed and deployed a targeted intervention to improve the quality, consistency, and timeliness of assignment feedback. The initiative centered on developing rubric-guided Custom GPT Feedback Assistants trained on institutional assessment rubrics, course-specific criteria, and discipline-aligned academic expectations. The intervention aimed to address two persistent sector-wide challenges: (1) variability in the quality and depth of feedback across instructors, and (2) student frustration with delayed or overly vague feedback. By embedding AI directly into the assessment workflow, we created a mechanism that generates precise, criterion-aligned, and actionable comments that instructors can review, refine, and release. This preserved academic judgment while dramatically increasing efficiency. The process began with co-design workshops involving faculty, learning designers, and assessment leads. These workshops unpacked each rubric criterion, translated academic expectations into machine-interpretable structures, and added constraints to ensure alignment with institutional standards (including tone, academic integrity cues, and constructive-developmental phrasing). The resulting Feedback Assistants were deployed across multiple courses. Instructors uploaded anonymized student submissions, selected the appropriate rubric profile, and received structured feedback that mapped onto each criterion. Faculty then verified accuracy, added individualized notes, and validated grades. This initiative did not replace human judgment; it amplified it. The AI served as a consistency engine, a quality accelerator, and a pedagogical scaffold for instructors. The intervention also exposed faculty to responsible AI use, strengthened their assessment literacy, and contributed to emerging institutional policy on AI-supported teaching and learning.

Evidence of impact

The intervention generated measurable improvements in both student learning experiences and faculty assessment practices. Across 146 assignments reviewed using the AI-assisted process, average turnaround time for feedback decreased from 10.4 days to 3.1 days, without compromising quality. Using a modified feedback quality index (clarity, actionability, alignment, and specificity), instructors rated AI-supported feedback 27 percent higher than traditional feedback produced during the previous term. Student perception data reinforced this. In voluntary post-feedback surveys (n=84), 91 percent of students described the feedback as “clear,” 87 percent as “directly actionable,” and 78 percent reported increased confidence in how to improve before their next assessment. Several students highlighted the structured nature of the comments, stating it made expectations “far less ambiguous.” Faculty also reported secondary benefits: reduced cognitive fatigue, improved ability to focus on deeper conceptual elements of student work, and more consistent application of rubric criteria across markers. Informally, instructors noted that the process acted as ongoing professional development, sharpening their own assessment language. The initiative demonstrated that responsibly integrated AI can enhance the feedback loop, elevate consistency, and meaningfully strengthen students’ capacity for academic improvement. Its success positions Rabdan Academy to scale similar AI-supported assessment tools across the institution.

Contact: Prof. Samar Ahmed sabdelazim@ra.ac.ae

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The Student Success Hub to Enhance Access, Retention, Attainment and Progression across a Diverse Student Population

Innovation

Arab Open University (AOU) has implemented a comprehensive Student Success Framework to enhance Access, Retention, Attainment, and Progression across its diverse student population. This framework is built on four strategic pillars: Access: Promoting inclusivity through flexible admissions, digital platforms, and outreach to underserved communities. Retention: Fostering a supportive academic environment that encourages engagement and persistence. Attainment: Providing resources, mentorship, and personalized learning to help students achieve academic excellence. Progression: Supporting transitions to employment or further study through career services and alumni engagement. To bring this framework to life, AOU launched the Student Success Hub (SSH)—a hybrid digital-physical platform offering integrated academic advising, career development, mental health support, and peer mentoring. Accessible via mobile and web, the SSH is staffed by trained advisors and student ambassadors. Key innovations include: An Early Alert System using predictive analytics to identify and support at-risk students. Personalized Learning Plans tailored to individual goals and challenges. Virtual Career Clinics connecting students with industry professionals. Peer Mentorship Circles that build community and shared learning.

Evidence of impact

The implementation of the Student Success Hub (SSH) at Arab Open University has yielded measurable improvements in student outcomes and institutional performance. Since its launch, enrollment among non-traditional learners—including working adults and women returning to education—has increased by 18%, driven by flexible access and targeted outreach. Retention rates have improved by 12%, supported by proactive academic advising and peer mentorship. The Early Alert System has enabled timely interventions for at-risk students, contributing to a 0.4-point increase in average GPA across faculties, with notable gains in Business Studies and Information Technology. In terms of progression, over 60% of graduates have secured employment or enrolled in postgraduate programs within six months, reflecting the effectiveness of career clinics and personalized learning plans. Feedback from students and external stakeholders has been overwhelmingly positive. Student satisfaction surveys show a 25% increase in perceived academic support and a 30% rise in engagement with university services. Employers have also commended AOU graduates for their preparedness and adaptability. Overall, the SSH has strengthened AOU’s reputation as a leader in open, inclusive, and digitally transformed higher education across the region.

Contact: Dr Habil Slade Ogalo drhabilslade@aou.org.bh

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Mapping RICS Competencies to Geomatics Academic Program: A Framework for Professional Alignment

Innovation

The geospatial industry in Oman is still in its early stages of adoption. However, with the strategic goals outlined in Oman Vision 2040, particularly those related to smart city initiatives and sustainable development, Geomatics is expected to play a pivotal role in national progress. Meeting this emerging demand requires a skilled local workforce in the field of Geomatics. Currently, only a limited number of institutions in Oman offer academic programs in this specialised discipline. The Military Technological College (MTC) addresses this gap by offering a two-year full-time Diploma Program in Geomatics Engineering, with plans to introduce a Higher Diploma from October 2025. These programs, validated by the University of Portsmouth, UK, cover core Geomatics subjects including Remote Sensing, Geographic Information Systems, Photogrammetry, Surveying, Cartography, and Geodesy. To encourage Omani students to pursue Geomatics as a professional career, it is essential to align academic training with clear pathways to professional recognition. The Royal Institution of Chartered Surveyors (RICS), the world’s leading professional body for land, property, and construction, defines key competencies for Geomatics professionals across three levels of expertise. At MTC, we have undertaken a mapping exercise, aiming to benchmark the modules of the MTC Geomatics Program against RICS competencies and determine the level at which each competency is addressed. The outcome of this project provides a structured competency-module alignment matrix, serving as a framework to strengthen curriculum development, support student progression toward RICS accreditation, and enhance the employability of Geomatics graduates in Oman. Although competency level 1 is expected to be achieved at the end of course, in some cases level 2 & 3 are also attained.

Evidence of impact

The mapping of MTC Geomatics program module learning outcomes with the RICS competencies reveals a comprehensive and structured alignment between academic training and global professional standards. Across core modules such as Digital Photogrammetric Applications, Earth Observation Applications, Geospatial Analytics and Applied Surveying Skills, students engage with critical knowledge and practical skills that directly correspond to key RICS competencies at Levels 1 (Knowledge and Understanding), Level 2 (Application), and in selected areas, Level 3 (Reasoned Advice). Fundamental technical areas—such as the generation of Digital Elevation Models, orthophoto creation, GNSS-based survey planning, vector/raster data modelling, surface analysis, and total station surveys—are delivered through hands-on learning using industry-standard software and equipment (e.g., ArcGIS Pro, CHCNAV GNSS, Leica). These prepare students for RICS competencies in Surveying and Mapping, Remote Sensing and Photogrammetry, Geographic Information Systems, Geodesy, and Measurement. Additionally, the curriculum introduces Communication and Negotiation, Health and Safety, and Project Brief Development, embedding soft skills and professional practices that are critical to becoming a Chartered Geomatics Surveyor. Other modules such as Business Management and interdisciplinary design projects provide opportunities for students to develop and demonstrate professional judgement, project planning, and client-focused communication, addressing both mandatory and technical RICS competencies. This mapping exercise confirms that MTC’s Geomatics program not only supports the academic and technical development of students but also strategically positions them for RICS Accreditation, increasing their employability and alignment with Oman Vision 2040 priorities in smart infrastructure and sustainable land management.

Contact: Amol Ganesh Deshmukh amol.deshmukh@mtc.edu.om

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From Classroom to Economy: Transforming Student Learning through Industry-Engaged Pedagogy Aligned with Egypt Vision 2030

Innovation

My innovative teaching approach integrates real-world industry engagement into engineering education to align with Egypt Vision 2030, specifically Strategic Goal 4, focusing on building a diversified, knowledge-based, and competitive economy. Recognizing the current gap between engineering education and the industry needs, I reshaped my modules around experiential learning that directly reflects national priorities and value-added skills. The approach centres on four interconnected components: fieldtrips, applied projects, expert engagement, and internationalisation. Fieldtrips involve pre-visit research tasks, on-site inquiry, and reflective post-visit analysis to help students connect their experiences to national goals such as manufacturing revitalization and business-environment improvement. Applied projects place my students in collaborative roles with industry partners, where they address real operational challenges. These projects cultivate practical problem-solving and innovation skills. Many partner organizations have implemented student recommendations and provided job offers, reinforcing learner confidence and the real-world relevance of their work. Many of those projects were published as case studies in top academic journals with students as co-authors. I invite guest speakers from various sectors to bridge classroom concepts with real professional experience. Guests are ensured to be from different genders and backgrounds to enable a diverse environment. Their contributions help students develop a clearer sense of how their future roles support national economic transformation. Finally, I managed to arrange international Summer Schools for my students in UK and Malaysia to embed global learning with a rich mix of class and industry activities. Collectively, these innovations create a learning environment that is dynamic, applied, and deeply connected to the economic context that the students will be part of after graduation.

Evidence of impact

The impact of this experiential learning approach has been significant, as demonstrated through student feedback, performance indicators, and partner testimonials. Student engagement scores increased by 22% compared to previous cohorts, and reflective portfolios showed deeper conceptual understanding, with 87% of students explicitly linking experiential activities to national economic priorities. Course evaluations highlighted that 90% of students felt the experiential elements improved their career readiness and confidence in applying theory to real-world contexts. Industry partners reported tangible benefits as well: several student consultancy teams produced strategic recommendations that were adopted or further explored by SMEs, particularly in areas of process optimisation and data analytics. Employers expressed strong interest in future collaborations, noting that students demonstrated professionalism and analytical depth. Institutionally, this innovation strengthened community partnerships and provided a scalable model for practice-based learning aligned with university strategy and national agendas. It also helped position the programme as a contributor to Egypt’s Vision 2030 priorities by producing graduates with practical experience, problem-solving capability, and awareness of economic development goals.

Contact: Dr Noha Mostafa noha.mostafa@bue.edu.eg

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AI-Enhanced Learning to Support First-Year Electrical Engineering Students

Innovation

Many first-year electrical engineering diploma students at Higher Colleges of Technology enter the programme feeling unsure of themselves. When moving from theory to hands-on tasks like circuit simulation, PCB design and troubleshooting, they often hesitate to ask questions and repeat the same mistakes. This can affect their confidence, progress, and overall experience in the programme. To support them, this project proposes using AI-enhanced learning tools as a personal, always-available guide. In weekly labs, students will have access to step-by-step explanations and examples, allowing them to explore and experiment safely. The AI will also offer bilingual support in English and Arabic, helping students understand complex concepts without feeling overwhelmed. A key feature is the AI-enabled troubleshooting assistant. Students can upload their circuit or PCB screenshots and receive immediate feedback on mistakes, safety risks, and corrective steps. This real-time guidance will help them connect theory to practice more confidently and reduce repeated errors. AI-generated quizzes will provide students with opportunities to check their understanding before formal assessments, easing anxiety and promoting independent learning. Faculty remain central, using the time freed by AI to offer personalised mentoring and deeper guidance. By combining AI tools with supportive teaching and bilingual explanations, this approach aims to build confidence, foster independence, and create a sense of belonging for all learners. The ultimate goal is to improve retention, attainment, and progression while ensuring students feel capable, engaged, and supported throughout their first year in the engineering programme.

Evidence of impact

The AI-enhanced learning approach is designed to help first-year Electrical Engineering diploma students at HCT feel more confident and supported as they move from theory to hands-on tasks. By giving students real-time guidance and bilingual support, the AI tools will help them understand complex concepts, try tasks independently, and reduce anxiety. AI-generated quizzes allow students to check their own understanding before assessments, fostering a sense of control over their learning. Faculty benefit too, as the AI handles routine queries, giving them more time for personalised mentoring and one-to-one support. This approach is expected to improve retention, attainment, and progression while creating a more inclusive and supportive environment. Industry supervisors and external stakeholders can anticipate students demonstrating stronger problem-solving skills, safety awareness, and preparedness for practical tasks. Ultimately, the innovation is about helping students feel capable, engaged, and confident, while providing faculty with tools to support learning more effectively—turning early challenges into opportunities for growth and success.

Contact: Prathibha Krishnapillai pprasanth@hct.ac.ae

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Integrating portfolio and mentorship in competency-based medical education

Innovation

Our innovation introduces an integrated portfolio and mentorship model designed to strengthen competency-based medical education by aligning assessment, reflection, and academic support within a unified system. Central to the innovation is a standardized, competency-mapped portfolio, aligned with the UAE’s national EmiratesMEDs framework, which enables systematic monitoring of students’ academic, professional, and personal development. Portfolio content is carefully curated to capture meaningful indicators of competency attainment, including performance assessments, reflections, and structured self-improvement plans. To ensure equity and comparability, portfolio checklists and assessment criteria are standardised across the curriculum. Complementing the portfolio, a longitudinal mentorship system provides individualised guidance, goal-setting support, and ongoing feedback. Mentors receive structured training, role clarification, and regular quality-assurance meetings to promote consistency. Students progressively build self-regulated learning skills through guided reflection, SMART goal planning, and iterative improvement cycles. A key component of the innovation is its technology-enhanced infrastructure, achieved through the use of the college’s Learning Management System as an e-portfolio platform. This ensures accessibility, efficiency, and clear communication, while reducing logistical barriers often associated with mentorship programs. Automated reminders, embedded resources, tagging functions, and secure data storage further enhance usability for both mentors and students. The system also incorporates early-warning mechanisms, flexible reassessment opportunities, and supportive learning environments to reduce stress, enhance retention, and ensure learners remain on track in their competency development. Overall, this integrated approach offers a scalable, context-sensitive model that combines structured assessment, developmental mentorship, and technological enhancement to promote meaningful progression, reflective practice, and readiness for future medical practice.

Evidence of impact

The integrated portfolio and mentorship system has had a measurable and positive impact on student learning, engagement, and progression. Early introduction of the portfolio from Year 1 led to a marked decrease in failure rates at final assessment, demonstrating improved student readiness and understanding of competency expectations. Students consistently reported high satisfaction with mentor interactions, confirming strong acceptance of the system. Portfolio evidence revealed meaningful improvements in reflective practice, goal setting, and self-regulated learning, supported by structured self-study and improvement plans reviewed at every mentoring session. Mentors also reported enhanced clarity in tracking competency attainment through standardized checklists and competency-mapped portfolio elements. Institutionally, the innovation strengthened academic governance by establishing a unified framework for monitoring student progression across the curriculum. The LMS-based e-portfolio improved efficiency, transparency, and documentation, enabling seamless quality assurance and timely intervention for at-risk students. The continuous feedback cycle between mentors, administrators, and learners has contributed to a culture of improvement and strengthened the institution’s readiness for national competency-based standards.

Contact: Dr Arina Zigabshina dr.arina@dmu.ae

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Enhancing Curricula to Align with National Visions: The BSc (Hons) Computing (Oil and Gas) Programme

Innovation

Majan University College (MUC) launched the BSc (Hons) Computing (Oil and Gas) programme in 2018 as a strategic response to Oman Vision 2040’s emphasis on digital transformation, economic diversification, and human capital development. The programme was designed to bridge a sector-wide skills gap at the intersection of Information Technology (IT) and Operational Technology (OT), an area that remains critical for the oil and gas industry’s transition to Industry 4.0. Developed through extensive collaboration with leading industrial partners—including oil and gas organisations and automation solution providers—the programme integrates computing fundamentals with specialised modules such as SCADA, Industrial Computing, Wireless Sensor Networks, and Industrial Data Networks. This IT-OT fusion enables students to understand both digital infrastructures and industrial control environments. A strong emphasis on experiential learning supports the curriculum. Dedicated industrial computing laboratories equipped with PLCs and real-world devices allow students to undertake simulation-based projects that closely mirror operational settings. Continuous dialogue with industry informs module updates, ensuring alignment with emerging technologies and workforce needs. The curriculum embeds industry-aligned learning design, practical assessments that measure applied competence, the creation of realistic learning environments, project-based learning approaches responsive to how students learn and flexible pathways that cater to diverse learners including working professionals. This initiative represents a sector-specific educational model that supports national workforce development, enhances graduate employability, and strengthens Oman’s capacity for digital industrial transformation.

Evidence of impact

Since its introduction, the programme has become one of the most popular pathways in the Faculty of IT, enrolling an average of 194 students per year and achieving a 95% retention rate. It accounts for more than 30% of faculty enrolments and demonstrates strong gender diversity, with female students making up 50% of the cohort. The programme attracts both fresh graduates and industry professionals seeking to upskill. Among school-leaver entrants, approximately 30% have already secured employment in the oil and gas sector, with others progressing through internships and industry-supported projects. Employers report high satisfaction with graduates’ ability to bridge IT and OT functions—an area previously reliant on expatriate expertise. Industry partners, including SCADA operations centres and automation firms, have commended graduates for their readiness to contribute to digital transformation initiatives, particularly in cybersecurity, industrial networking, and data-driven operations. Feedback indicates that hands-on training and exposure to real industrial infrastructure significantly enhance employability. The programme directly supports Omanisation efforts by developing a national talent pipeline capable of taking on specialised technical roles. Its alignment with national priorities has strengthened MUC’s position as a provider of contextually relevant, industry-driven education and has contributed to Oman’s broader transition toward a sustainable, knowledge-based economy.

Contact: Dr Ramalingam Dharmalingam ramalingam.d@majancollege.edu.om

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Enhancing Aerospace Curriculum Using Virtual Reality for Gas Turbine Training

Innovation

Aerospace engineering program face ongoing challenges in delivering high-fidelity, practical learning experiences, particularly in highly complex areas such as Gas Turbine Engine (GTE) systems. At the Military Technological College (MTC), limited physical engine access, safety constraints, and the complexity of internal engine processes created barriers for students—especially for those with lower English proficiency or weaker theoretical grounding. To address this, I led the development and integration of a Virtual Reality (VR) Gas Turbine Engine Training System into the aerospace curriculum. The VR system provides students with full immersive access to a 3D engine model, allowing them to explore compressor stages, combustion chambers, turbine sections, and accessory systems in a way not possible with a physical engine. Learners can perform virtual strip-downs, observe airflow and combustion animations, and interact with engine components safely and repeatedly. This builds experiential understanding that bridges the gap between theory and practice. The innovation has been embedded within two Gas Turbine Engineering modules as a structured learning activity aligned to specific learning outcomes. It was also mapped to professional competencies expected within Part-147 and Oman’s national aviation workforce needs. I worked with instructors to redesign lesson plans, integrate VR tasks into classroom delivery, and provide staff training to support digital teaching confidence. This approach aligns directly with Oman Vision 2040, emphasising digital transformation, future-skills development, and the use of advanced technology in engineering education. It also reflects international best practice in simulation-enhanced learning, enabling students to develop deeper conceptual understanding in a controlled and inclusive environment. The innovation therefore not only modernised the aerospace curriculum but also established a scalable model for other engineering disciplines at MTC, positioning VR as a core pedagogical tool rather than an add-on technology.

Evidence of impact

The introduction of VR Gas Turbine training has produced clear and measurable improvements in student learning, engagement, and progression. Surveys conducted before and after VR integration showed a 42% increase in student confidence in explaining GTE internal processes. Practical assessment performance improved, with the average pass rate in applied GTE topics rising from 72% to 88% over current semesters. Students reported that VR made complex concepts 'easier to visualise', 'less intimidating' and 'more enjoyable', with particularly strong benefits for international learners and those with weaker theoretical foundations. The immersive environment reduced cognitive load, helping students connect classroom theory with real aircraft systems more effectively. Instructors also noted improvements in lesson flow, student questioning, and engagement during practical demonstrations. VR allowed the department to deliver safe, repeatable, and standardised practical experiences even when hangar access or engine availability was limited. Institutionally, the success of the VR project has prompted wider interest from other departments—including Mechanical, Marine, and Systems Engineering—who are exploring VR integration into their own curricula. This initiative strengthened MTC’s reputation as a leader in technology-enhanced aviation training and aligned the curriculum with Oman’s national vision for a digitally advanced education sector.

Contact: Dominic Hanratty dominic.hanratty@mtc.edu.om

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Integrating Artificial Intelligence Technologies into the Quality Assurance Process: Measuring and Verifying Learning Outcomes Using IBM Watson Analytics for Course Report Preparation

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Innovation

This innovative approach proposes the integration of IBM Watson Analytics into academic accreditation processes, specifically for preparing accurate, data-driven course reports. As higher education institutions aim to strengthen quality assurance and demonstrate clear evidence of student learning, the volume and complexity of data generated through e-learning platforms present a significant challenge. Traditional methods of compiling course reports are time-consuming, prone to human error, and often lack the analytical depth required for continuous improvement and accreditation standards. Our solution leverages the advanced analytics and AI capabilities of IBM Watson to automate the collection, analysis, and interpretation of learning data. By using cognitive computing, the system can identify trends in student performance, measure the extent to which learning outcomes have been achieved, and highlight gaps that require instructional or curricular adjustments. This transforms the course report from a descriptive document into a dynamic, evidence-based tool that supports decision-making at both the course and program levels. A key innovation lies in the ability of AI to verify alignment between assessments, learning outcomes, and teaching strategies. Watson Analytics provides visual dashboards, predictive insights, and pattern recognition that enable faculty to immediately detect areas affecting student access, retention, attainment, and progression. This ensures a more equitable learning experience by identifying at-risk students early and providing actionable recommendations to improve achievement. At the institutional level, the approach supports national priorities for digital transformation and enhances compliance with accreditation frameworks by offering transparent, accurate, and standardized reporting. The adoption of IBM Watson Analytics elevates the quality assurance process, reduces administrative burden, and enhances the reliability of evidence submitted for accreditation reviews. Overall, this innovative approach positions AI as a strategic enabler for improving academic quality, strengthening learning outcomes, and supporting continuous improvement across higher education programs.

Evidence of impact

The integration of IBM Watson Analytics into course reporting has had a measurable and transformative impact on both students and the institution. By automating the analysis of learning data, the system has significantly enhanced the accuracy and reliability of course reports, enabling faculty and administrators to make informed, evidence-based decisions. This has directly improved student outcomes by identifying at-risk learners early, allowing timely interventions that support retention, progression, and overall attainment. Preliminary data indicate that courses utilizing AI-driven reporting saw a 15% improvement in alignment between assessments and intended learning outcomes, ensuring that students are evaluated fairly and consistently. Faculty feedback has been overwhelmingly positive, highlighting that the dashboards and predictive insights simplify complex data interpretation and reduce administrative workload by up to 40%. External stakeholders, including accreditation reviewers, have noted the clarity, comprehensiveness, and transparency of AI-generated reports, reinforcing institutional credibility and compliance with national quality assurance standards. Beyond measurable outcomes, the innovation has fostered a culture of data-informed teaching and continuous improvement. By embedding AI into the academic workflow, the institution has strengthened its digital capabilities, enhanced teaching effectiveness, and created a scalable model for improving learning experiences, ultimately contributing to national priorities for higher education excellence and innovation.

Contact: Dr Neyara Radwan neyara.hassan@lu.ac.ae

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A Structured Support Model for At-Risk Students in Political Science

Innovation

In recent semesters, we noticed a rise in the number of students on academic probation at our institution. In response, our Political Science department introduced a structured support model to help students stay on track, and improve their performance. The main goal was to identify students who were struggling and understand what was holding them back, to give them the guidance they needed to succeed. The process began with a required probation meeting, where we sat down with each student and reviewed their transcripts in detail. This helped us understand the root causes of their problems; whether they relate to exam anxiety, challenges with academic writing, limited engagement with course materials, or other difficulties we were not aware of. After this initial discussion, we prepared a customized Support and Improvement Plan tailored to the courses they are taking in the Spring semester. This plan includes: • Bi-weekly one-to-one feedback sessions on coursework drafts • Extra assignments, such as short quizzes and case-based tasks to help improve their GPA • Co-created study timetables focusing on key political science concepts • Peer-learning opportunities with strong senior students who act as role models These activities offered a flexible way so students so that they do not feel depressed or ostracized. We were also flexible to monitor progress and adjust the plan whenever necessary. What makes this initiative pioneering is how we viewed academic probation. Instead of treating it as a penalty, we perceived it as a chance for students to rebuild their confidence and academic skills. It has now become a workable and effective practice within the department, helping us provide appropriate support to at-risk students.

Evidence of impact

The initiative had a positive effect on our student’s retention and achievement. Before introducing the support plan, 52 out of 150 Political Science students were identified as at risk. Among those who joined the support program while on academic probation, 68% (34 students) were able to return to good academic standing the following semester. This was a significant improvement compared to their status before the initiative was introduced. Student feedback has also been very encouraging. From anonymous reflections, most students reported that they felt more confident in their academic abilities, had a better understanding of course expectations, and even felt more connected to the department. Also, some noted that the one-to-one meetings helped them identify academic issues they hadn’t previously recognized.

Contact: Dr Nora Maher nora.maher@muc.edu.eg

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Integrating National Health Priorities into the Basic Medical Sciences Curriculum

Innovation

This curriculum enhancement project responds directly to national health priorities across the MENA region by integrating country-specific healthcare challenges into basic medical sciences modules such as immunology, microbiology and physiology. Many national visions—including Saudi Vision 2030, the UAE National Strategy for Wellbeing 2031 and similar regional frameworks—emphasise chronic disease prevention, digital and AI-enabled health services, mental health, and infection control. However, these priorities are often not explicitly connected to foundational scientific teaching. To address this gap, a cross-disciplinary academic team redesigned learning outcomes, teaching activities and assessments to ensure stronger alignment with national health strategies.

• Local epidemiological data, Ministry of Health reports and regional disease surveillance indicators were embedded into lectures, discussions and laboratory activities.
• Case-based learning scenarios were rewritten to reflect authentic regional challenges, such as the high prevalence of diabetes and obesity, antimicrobial resistance trends, MERS-CoV and COVID-19 experiences, and the growing use of AI in diagnostic pathways.
• Students engaged with real data, national policy goals and locally relevant clinical scenarios, enabling them to apply scientific knowledge more meaningfully while understanding the broader healthcare context they will eventually serve.
• Guest sessions from clinical and public health partners further reinforced the connection between foundational science and national strategic goals.
• Updated module outcomes explicitly referenced national visions and digital health priorities, improving curricular coherence and institutional alignment.

This innovation strengthened student engagement, improved perceived relevance of basic sciences and enhanced performance in case-based assessments. Importantly, it prepared graduates to contribute effectively to regional health priorities by deepening their understanding of both scientific mechanisms and the strategic direction of local healthcare systems. The approach also strengthened collaboration across departments and set the foundation for ongoing integration of national health data and AI-driven innovations into the curriculum.

Evidence of impact

The integration of national health priorities into basic medical sciences has had a measurable and positive impact on both student learning and institutional alignment with national agendas. Student evaluations demonstrated a 42% increase in perceived relevance of immunology, microbiology and physiology content after the redesign, with many students noting that the use of regional epidemiological data and authentic case scenarios made learning “more meaningful and connected to real healthcare challenges.” Assessment data showed a 28% improvement in case-based learning performance, particularly in questions requiring application of scientific concepts to local clinical contexts such as diabetes prevalence, antimicrobial resistance patterns and digital health initiatives. Attendance in redesigned sessions increased by 15%, reflecting enhanced student motivation and engagement. Qualitative feedback from clinical partners highlighted the value of preparing students earlier for region-specific challenges. One hospital collaborator commented that students demonstrated “greater awareness of national health strategies and stronger readiness to engage in preventive and digital health approaches.” Institutionally, the project strengthened alignment with accreditation standards and national vision metrics. The curriculum mapping exercise was commended during internal review for “clear evidence of responsiveness to the national healthcare agenda.” The initiative has since been adopted as a model for future curriculum updates in other basic science modules.

Contact: Dr Sameh Fawzy Elsonbaty sameh.elsonbaty@lu.ac.ae

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Interprofessional Collaboration in Health Professions Education

Innovation

This innovation introduces an evidence-based, institution-wide strategy to enhance faculty readiness for interprofessional education (IPE) as a foundation for improving student progression. A structured faculty survey highlighted strong faculty willingness to collaborate but identified substantial gaps in conceptual knowledge and facilitation skills particularly regarding Interprofessional Education Collaborative competencies, structured communication tools, and debriefing techniques. The innovative approach shifted the focus from student-facing simulation design to building faculty capability as the key determinant of IPE quality. Guided by the diagnostic findings, a multi-phase capacity-building framework was designed to prepare educators through targeted workshops, hands-on scenario facilitation practice, assessment tool training, and structured debriefing exercises. The project extends into scenario development with expert validation, pilot implementation, and mixed-methods evaluation using RIPLS, ICCAS, reflective logs, and thematic analysis ensuring a rigorous, measurable approach to improving teaching quality and student attainment. To scale the initiative, the project roadmap includes institutional integration of IPE simulations, longitudinal evaluation of student progression, dissemination through national and international conferences, and showcasing IPE in action at conferences aligned with related themes. This structured, iterative approach ensures equitable access to interprofessional learning for all students, reduces variability in facilitation quality, and strengthens academic and clinical preparedness across health professions programs.

Evidence of impact

Although this innovation is in its early stage, it has already generated tangible institutional impact by providing the first systematic evidence of faculty readiness, capability gaps, and implementation barriers related to Interprofessional Education. The survey results revealed clear gaps which enabled the institution to identify targeted areas for faculty development. These data have already informed discussions within program teams regarding curriculum enhancement and the need for structured facilitator training to ensure consistent IPE experiences. The findings have also impacted student-facing planning. Faculty insights into student challenges such as variation in clinical knowledge (89.3%), role ambiguity (67.9%), and anxiety during mixed-discipline simulations (50%) have prompted programs to reconsider pre-briefing design, role assignment, and psychological safety strategies. This represents a measurable shift in how departments are preparing to support student engagement and progression in future IPE activities. While full student outcome data will be collected in the next phase, the innovation has already produced actionable institutional insight, cross-disciplinary engagement, and a clear foundation for structured IPE capacity-building, marking a meaningful first step toward long-term improvement in student attainment and progression. This innovative project has received research ethical approval from Liwa University (EC-MHS-001-2025).

Contact: Dr Manjush Karthika manjush.karthika@lu.ac.ae

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Embedding Ethical and Responsible AI Practices to Enhance Postgraduate Learning and Assessment Integrity

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Innovation

My innovative approach centred on establishing a coherent, research-informed framework for ethical and responsible AI integration across postgraduate education. Recognising early that reactionary or punitive measures would not resolve emerging challenges, I led a proactive institutional initiative grounded in pedagogy, ethics and digital cognition. Through peer-reviewed published (and more in press) research I authored practical tools that made responsible AI use visible, discussable and assessable. These included AI usage declarations, reflective self-audit templates and a set of principles supporting transparent engagement with generative AI. This shifted the institutional narrative from avoidance to scholarly inquiry. To build capability, I designed and delivered AI pedagogy workshops for faculty, programme leaders and dissertation supervisors. These explored assessment design for reasoning and originality, identification of AI-generated bias or misinformation, and ways to embed ethical AI literacy into module learning outcomes. These engagements significantly increased staff confidence and enabled structured conversations around integrity, innovation and student support. The approach also extended to curriculum design. In the new M.Ed. in Educational Technology and AI, I embedded ethical AI literacy and critical digital pedagogy as core learning outcomes. In the PGDip and M.Ed. in Educational Leadership, I aligned assessments and evidence structures with CAEP standards to ensure AI-aware professional preparation. Together, these strategies created a systemic, sustainable model for AI-enhanced postgraduate education that prioritised integrity, transparency, critical thinking and national readiness.

Evidence of impact

The innovation produced measurable improvements in academic integrity, curriculum coherence and faculty–student confidence around AI. Faculty reported greater clarity when communicating acceptable AI use and increased capability in designing assessments that require authentic reasoning and judgement. This reduced reliance on formats vulnerable to automated generation and improved the robustness of postgraduate assessment. Students benefitted from explicit, structured guidance on ethical AI use, supported by reflective tools that helped them evaluate their own practices. This clarity significantly reduced confusion and anxiety, strengthening retention and academic self-efficacy. Evidence from workshops and programme reviews showed improved student understanding of integrity expectations and increased engagement with critical AI literacy. Institutionally, curriculum teams adopted shared approaches to embedding AI into learning outcomes, mapping structures and assessment designs. Programmes preparing for CAEP accreditation enhanced their alignment to professional standards by incorporating AI-aware educator preparation. The M.Ed. in Educational Technology and AI established ethical AI literacy as a core component, directly supporting national priorities for AI readiness. Overall, the initiative promoted a culture where AI is approached critically and ethically, improving postgraduate learning quality and strengthening institutional preparedness for an AI-enabled future.

Contact: Dr Constantine Andoniou constantine.andoniou@adu.ac.ae

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When Learners Arrive Tired and Leave Energised: A Constructivist Redesign for Night-Time Postgraduate Classes

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Innovation

Postgraduate classes at Abu Dhabi University run from 6:45 pm to 10:00 pm, serving adult learners who attend directly after full working days. When I began teaching on the program, I observed a consistent pattern across cohorts: students entered the classroom exhausted, with low energy and limited willingness to participate in discussion, despite strong intrinsic motivation to learn. The traditional extended lecture model unintentionally amplified fatigue and reduced opportunities for dialogic learning, which is essential in postgraduate education built on professional experience, reflective inquiry, and peer exchange. To address this, I redesigned the entire learning experience using the Understanding by Design (UbD) framework, grounded in principles of adult learning and social constructivism. Beginning with the desired graduate outcomes, I mapped backward to create a sequence of learning activities that encourage students to build knowledge through interaction rather than passive reception. At the start of the semester, I implemented a learner profile activity to understand each student’s work context, learning preferences, confidence levels, and expectations. This data informs differentiated instructional strategies and creates an immediate sense of belonging and relevance. The redesign integrates digital tools such as AhaSlides to support interactive polling, case analysis, and structured reflection. Case studies are drawn from students’ real contexts and explored through collaborative discussion, enabling learners to connect theory directly to practice. I also draw on my training and professional development experience to design interactive activity cycles that combine movement, dialogue, and reflection. Techniques such as “walk-and-talk,” mini-workshops, peer coaching, and instructional simulations offer opportunities for students to engage physically and socially, which helps counter the fatigue typically associated with late-evening classes. This approach shifts the cognitive load from listening to co-creating knowledge, enabling students to remain intellectually active even when physically tired. It also models the pedagogies we expect them to apply in their schools, reinforcing deep learning rather than memorization.

Evidence of impact

Across one academic year (n=200 postgraduate students), student feedback demonstrates a consistent pattern of positive outcomes. In anonymous evaluations, 94% of students reported that the redesigned learning environment “helped them stay engaged despite evening fatigue,” and 91% reported that the blend of interactive design and digital tools “made learning enjoyable and relevant to their work.” Several students commented that “we do not feel the time,” describing a shift from entering the classroom with low energy to leaving “motivated and full of ideas.” Participation levels increased visibly across cohorts. Students who were initially silent began sharing experiences, questioning assumptions, and contributing to collective inquiry. Case-based discussions led to deeper reflection on practice, and final assessments demonstrated increased ability to apply theoretical frameworks to complex workplace scenarios. The model also strengthened progression: three students reported implementing similar learner-profiling techniques in their own teaching, and all reported sharing interactive strategies within their schools. The initiative has enhanced attainment through deeper understanding and improved formative performance, and improved retention by creating a learning atmosphere that sustains energy, respects adult experience, and supports students to persist despite demanding schedules.

Contact: Dr Sana'a Al Reiahy sanaa.alreiahy@adu.ac.ae

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Transforming Student Success: The GCET Academic Support Centre Model

Innovation

Evolving from the previously established Foundation Support Centre, the ASC Academic Support Centre (ASC) at GCET represents a structured, data-informed success model designed to enhance student access, retention and academic achievement institution-wide. The ACS operates as a central developmental hub for programmes of all levels. Rather than functioning as a remedial drop-in point, the ASC reframes support as progression-oriented academic development, empowering students to build the competencies required for successful and confident engagement in higher education. The Centre consolidates support practices formerly scattered across academic departments into one integrated system. It operates on three strategic pillars: 1. Early diagnostic identification of students needing support, enabling proactive rather than reactive intervention. 2. Structured deployment of Student Peer Teaching Assistants (SPTAs), recruited and paid by GCET, who provide discipline-specific tutoring support. 3. A centralised reporting and analytics mechanism, ensuring efficient resource allocation and high-resolution data on student learning behaviours, challenges and outcomes. After an early diagnosis process, students are then directed into tailored support streams, including one-to-one academic help, group-based skill circles, English speaking and writing support, and structured study-skills mentoring. Learners with special needs are prioritised immediately within the referral cycle, ensuring equity of access and inclusive learning support. The shift from reactive assistance to proactive scaffolding has directly influenced student learning culture, improving motivation, discipline, self-awareness and academic identity. Recognising diversity of English language skills, particularly among learners entering with limited English or APL progression, the ASC embeds writing and digital literacy support into real coursework demands, enhancing relevance and transferability. The model remains scalable, low-cost, and suitable for replication across institutions seeking to strengthen attainment without substantial infrastructural investment.

Evidence of impact

After two semesters of operation, measurable improvement in student performance and behaviour is evident. Participation in voluntary support sessions have increased consistently month-on-month, and Flash Survey results indicate stronger clarity around academic writing expectations and assessment readiness. The class attendance after support referral shows an increase of 18 to 24%. The assessment submission has been more regular, with a significant reduction in late or missed submissions. The academic speaking and writing quality also proves fewer revisions, clearer structure and argumentation. Most importantly, the student satisfaction has drastically increased, which is shown via positive feedback in various surveys, praising the relevance and accessibility of the services. Students engaging with support circles demonstrated enhanced topic-specific speaking skills, paraphrasing fluency and reading-to-writing transfer. GFP learners reported reduced anxiety and greater confidence transitioning into undergraduate study, while teaching staff noted fewer repeated feedback cycles and improved quality in reflective and research-based written work. Through a deliberate move from passive availability to targeted, data-led intervention, the GCET Academic Support Centre has strengthened student progression, academic identity and independent learning capability. The model illustrates how structured literacy-grounded support can sustain meaningful improvement in student achievement within HE environments.

Contact: Dr Ahmad Hosseini ahmad.hosseini@gcet.edu.om

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Simulation as a metacognitive activity in a Research Design course

Innovation

My teaching philosophy prioritizes the design and development of curricula that are both responsive to diverse student abilities and relevant to students’ lived experiences. I aim to realize this through pedagogical strategies that integrate hands-on, cooperative, and individualized learning modalities to actively engage students and enhance their learning processes. When I started working at the Education Department at Abu Dhabi University, I was tasked with developing a Research Design course for a newly established PhD in Education programme. One of the programme’s learning outcomes emphasized enabling students to demonstrate competence in applying knowledge through the management and evaluation of initiatives. This outcome aligned meaningfully with the session on 'Ethics in Educational Research', which I had previously taught. In earlier iterations, this session had remained largely theoretical, focusing primarily on institutional and international codes of research conduct, best practices regarding privacy and data protection, and procedural overviews of ethics approval processes. To foster more active engagement, I introduced a new collaborative activity - a simulation. After delivering foundational content on research ethics, I divided students into small groups and presented them with two research vignettes. One vignette described a sociology PhD student proposing to interview undocumented migrant workers about their living and working conditions, with the aim of exposing systemic exploitation and informing policy reform. Students were then asked to assume the role of an Institutional Review Board (IRB) and critically evaluate the proposal. Their task was to identify ethical concerns and provide constructive feedback on issues requiring closer attention. Each group presented their evaluations in a plenary session, followed by a structured discussion to analyze their findings and reflect on the ethical decision-making process. The simulation enables a shift from teaching about ethics to practicing ethical governance that aligns with the 'We the UAE 2031' vision on agility, proactivity, and applied excellence.

Evidence of impact

All students taking that course had gone through the ethics review process for their master’s programme, so they were aware of the process and requirements. The theoretical portion of the session was a reminder of all the necessary steps, milestones and deliverables, sprinkled with specific examples, some of which were from projects I have engaged in. However, it wasn’t until they did the simulation of an Institutional Review Board meeting that they had to think deeply about the issues we covered in the theory. Following this activity the students expressed how intrigued they felt doing this activity because they were forced to get out of their comfort zone and examine a situation from a very different perspective. They also seemed to enjoy the active participation aspect of the activity and the fact that they were applying the content knowledge. I have to add that in my opinion students not only engaged actively in their small groups, but more importantly, they engaged critically in discussing their findings with the other groups and debated broader issues of ways to make research more rigorous and robust.

Contact: Dr Yurgos Politis yurgos.politis@adu.ac.ae

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AI-Enhanced Peer Feedback to Improve Engagement and Learning Outcomes for Postgraduate Students

Innovation

To enhance feedback quality and student engagement at the postgraduate level, we implemented an AI-assisted peer feedback system in research-intensive courses. Postgraduate students submitted draft reports and research proposals via a digital platform integrated with AI tools. The system guided students in evaluating peers’ work using structured rubrics, highlighted areas for improvement, and prompted critical reflection. Faculty monitored the feedback process, intervening when necessary, and ensured alignment with academic standards. The approach encouraged students to engage critically with complex content, strengthened their analytical and evaluative skills, and fostered collaborative learning among cohorts. The system was piloted over two semesters, with continuous adjustments based on student feedback and performance metrics. Collaboration between faculty, instructional designers, and IT staff ensured that the system was user-friendly, accessible, and integrated with existing learning management systems. This initiative demonstrates how AI tools can support high-level learning and research skills development while maintaining rigorous academic standards, making it particularly suitable for postgraduate education.

Evidence of impact

The AI-assisted peer feedback system led to measurable improvements in postgraduate student engagement and learning outcomes:

• Survey feedback indicated that 90% of students found the feedback process valuable, particularly for improving research design and critical analysis.
• Timely feedback allowed students to revise proposals and reports more effectively, contributing to higher-quality submissions.
• Faculty workload for reviewing drafts was reduced by 25%, enabling instructors to focus on mentoring and guiding research projects.
• Students demonstrated stronger analytical and evaluative skills, and interdisciplinary collaboration increased within cohorts.
• External reviewers and supervisors recognized the approach as an innovative model for supporting postgraduate learning, and the system has since been adopted in additional postgraduate programs, highlighting its scalability and sustainability.

Contact: Dr Bacem Mbarek bacem.mbarek@gulfcollege.edu.om

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EmpowerEd BUE: Advancing Teaching and Learning Excellence

Innovation

EmpowerEd BUE is a university-wide academic development initiative designed to enhance teaching quality, strengthen pedagogical innovation, and embed a sustainable culture of continuous professional growth at the British University in Egypt. The project responds to the institutional need for a structured, scalable, and evidence-informed framework that supports academic staff in adopting contemporary teaching practices aligned with BUE’s transformation agenda. The initiative establishes a comprehensive professional development ecosystem that includes blended learning pathways, micro-credentials, mentoring schemes, and active communities of practice. These pathways focus on priority themes such as AI-assisted pedagogy, assessment and feedback literacy, inclusive and student-centred teaching, and the design of authentic learning experiences. By integrating workshops, microlearning, reflective practice cycles, and collaborative peer-exchange, the framework ensures consistency in academic development while accommodating diverse disciplinary contexts. EmpowerEd BUE also aims to significantly expand the institution’s capacity for the Scholarship of Teaching and Learning (SoTL). Through structured support, staff are encouraged to engage in pedagogical research, experiment with innovative teaching approaches, and disseminate evidence of impact within and beyond the university. The project follows a staged process involving needs analysis, design, piloting, university-wide rollout, and institutionalisation through HR, quality assurance, and governance systems. Ultimately, EmpowerEd BUE positions the university to deliver high-quality, research-informed, future-ready teaching that enhances student learning, supports staff growth, and contributes to BUE’s standing as a leading institution within Egypt and the region.

Evidence of impact

The initiative has already begun to demonstrate clear institutional and pedagogical impact. Early pilot activities attracted strong engagement across multiple faculties, with high participation rates in AI-assisted teaching workshops, assessment design sessions, and feedback-focused development activities. Participants reported improved confidence in adopting innovative approaches, particularly in integrating AI tools, redesigning assessments for authenticity, and implementing more effective feedback strategies. Qualitative feedback from academic staff indicates that the structured pathways and hands-on workshops have offered practical, immediately applicable strategies that enhanced their teaching. Several departments have already adopted revised assessment briefs, improved rubric designs, and introduced blended and interactive teaching methods inspired by the training. The project has also strengthened cross-faculty collaboration. Communities of practice formed during pilot activities have continued beyond the formal sessions, with staff sharing resources, peer-reviewing each other’s assessments, and exploring joint SoTL outputs. From an institutional perspective, the initiative directly supports BUE’s transformation priorities by advancing professional development, enhancing teaching consistency, and contributing to measurable improvements in student experience. Early student feedback from modules taught by EmpowerEd participants reflects increased clarity of expectations, improved feedback quality, and more engaging learning environments—demonstrating the early but tangible impact of the project.

Contact: Mr Mostafa Youssef mostafa.youssef@bue.edu.eg

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Aligning Learning Theories, Teaching Methodologies, and AI to Address Complex Medical Concepts

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Innovation

This innovation integrates learning theory, active teaching methodologies, and structured AI support to enhance student understanding of conceptually complex biomedical content. The approach was developed across multiple courses, including clinical biochemistry and metabolic pathways. Teaching was redesigned to explicitly draw on Cognitive Load Theory, constructivism, dual-coding, and Assessment for Learning principles. Classes incorporated micro-flipped segments, progressive disclosure techniques, and scaffolded exploration. For example, in biochemistry lectures, students redrew pathways, annotated regulatory points, and explored mechanisms independently before the instructor connected higher-level concepts. AI was integrated as a structured learning partner rather than a replacement for pedagogy. Students used AI tools for in-class micro-explanations, rapid visualisation of pathways, clarification of misconceptions, and guided reasoning exercises. During class, AI-generated prompts supported case-based discussions and adaptive questioning. Across approaches, students were invited into the “why” behind teaching design which made learning theory visible to them. This increased metacognitive awareness, improved study strategies, and strengthened autonomy. AI was used transparently and critically, encouraging students to evaluate information against scientific evidence.

Evidence of impact

Students demonstrated increased engagement, confidence, and conceptual clarity when navigating complex biomedical processes. Active participation improved, particularly in sessions where AI scaffolding and active learning were combined. Students described the sessions as “more understandable,” “less overwhelming,” and “easier to remember.” Formative assessment performance improved, especially in areas requiring multi-step reasoning or integration of biochemical and physiological concepts. Students showed stronger ability to annotate pathways, identify regulatory points, and interpret clinical or laboratory scenarios. Institutionally, this work contributed to a growing culture of responsible AI adoption and evidence-based teaching enhancement. It offered a model for theory-driven integration of digital tools and has informed conversations within the department about active learning, and student experience. This innovation aligns with Abu Dhabi University’s digital transformation and educational excellence priorities, demonstrating practical ways AI can enhance learning without compromising academic integrity. This work has been awarded best presentation award in The 2nd ADU International Conference on Education.

Contact: Dr Amal Gadalla amal.gadalla@adu.ac.ae

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A Nationally Aligned Model for Applied Engineering Learning Through Structured Design Challenges and Micro-credential Pathways

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Innovation

To align engineering education with the priorities of 'We the UAE 2031', the curriculum in the college of engineering at Abu Dhabi University was restructured around a set of annual, innovation-driven design challenges embedded within course projects. These challenges require students to design, implement, and demonstrate functional prototypes that reflect emerging national needs in digital transformation and applied technology by applying the skills learnt in the respective course. These span key domains including Internet of Things systems, autonomous and intelligent mobility, smart sensing and monitoring, mobile application development, and biomedical assistive technologies. Examples of resulting prototypes include IoT-enabled ventilator systems, robotic systems, AI-supported vein detection devices, smart attendance solutions, environmental monitoring platforms, and self-driving vehicles. Each design cycle is delivered through a competitive structure that mirrors national innovation programs, where students defend their design decisions, demonstrate prototype performance, and benchmark outcomes against peers. This structure reinforces problem scoping, experimental validation, and technical communication, skills emphasized in national digital-economy and innovation strategies. In addition to project work, the curriculum incorporates optional specialization routes in areas such as Edge AI and cross-platform mobile development, allowing students to deepen expertise in priority technology sectors. In parallel, micro-credentials offered through the college’s Industrial Alignment Program were embedded into degree pathways. These provide students with structured learning in cybersecurity, networking, and cloud and data platforms, supporting alignment with the UAE Ministry of Education’s Outcomes-Based Education Framework (OBEF) in areas related to industry relevance and skills development.

Evidence of impact

The curriculum changes produced measurable outcomes in student performance, prototype quality, and engagement with national innovation activities. The design-challenge model generated a consistent annual pipeline of functional prototypes, many of which progressed to UAE-based and regional competitions. Collectively, student teams achieved more than 50 recognitions in national and sector-focused events. The model also increased student contributions to the UAE’s research output; since adopting structured prototype-based learning, students have co-authored over 75 Scopus-indexed publications, with sustained year-on-year growth. Several winning course projects were further developed into publishable work. Micro-credentials delivered through the Industrial Alignment Program supported the same curricular direction and contributed to observable skill-development trends. More than 600 students have completed these pathways, and the program produced a 25% increase in student publications alongside two completed cycles of industry-defined skills alignment. Graduate outcomes reflect the progression dimension of the OBEF framework. More than 80% of ADU graduates secure employment within a year, consistent with national expectations for workforce readiness under the Forward Economy pillar.

Contact: Prof Mohammed Ghazal mohammed.ghazal@adu.ac.ae

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A Multi-Layered Student Success and Continuity Framework for Engineering Education at ADU

Innovation

The College of Engineering at Abu Dhabi University established a Multi-Layered Student Success and Continuity Framework structured around access, retention, attainment, and progression. Each layer consists of operational components integrated into teaching and learning processes:

• The first layer addresses access and attainment through virtual laboratories developed for nine engineering subjects. These laboratories were initially implemented as replacements for physical lab sessions when on-campus access was limited due to Covid-19. Students complete structured lab manuals, conduct simulations aligned with course outcomes, and submit graded reports. The virtual laboratories remain in use as supplementary tools for reinforcing core practical concepts to meet course learning requirements related to practical competencies.

• The second layer addresses access and attainment at the entry stage through a freshman orientation session embedded within the Introduction to Engineering and Computing course. The session familiarizes new students with program requirements, laboratory environments, and available academic support. Activities such as problem-solving tasks and basic soldering exercises introduce students to foundational tools and expectations before formal coursework begins.

• The third layer addresses progression through two components. The first component is a five-year Engineering Dual Degree pathway developed in collaboration with Trinity College Dublin, supported by elective selection that enables students to complete both BSc and MSc degrees within an accelerated structure. The second component is an Industrial Alignment Program developed by the College. Students engage in funded project with industrial partners that include meetings and site visits to support progression toward employment after graduation.

• The fourth layer addresses retention through an enrollment-monitoring process supported by an internally developed dashboard that displays enrollment status, credit-hour progression, and reported barriers to registration. Teaching Assistants, academic advisors, and admissions staff contact students before each semester to document intentions and coordinate academic advising, course planning, or administrative follow-up as required.

Evidence of impact

Implementation of the framework has been reflected in documented student participation, re-enrollment patterns, and engagement with academic and industry-linked activities across the College of Engineering. Virtual laboratories were used by students in nine engineering subjects, with 549 survey responses recorded; 84% of respondents reported to be very satisfied with completing practical tasks in the virtual format. The freshman orientation session has been delivered annually to more than 250 new engineering students, reaching up to 360 students in Fall 25-26, with consistent participation in problem-solving activities and introductory laboratory tasks. Students engaging in progression pathways have taken part in industry-defined project cycles, with more than 600 graduates completing industry-linked components since the program’s introduction. Reenrollment monitoring through the dashboard-supported calling campaign recorded continuation rates of 66.08% in Spring 2024-25 and 66.48% in Fall 2025-26 among contacted students. Enrollment trends show long-term growth in the College of Engineering, increasing from 181 students in 2008 to 2,348 students in 2020, and then rising by nearly 1,000 additional students to 3,325 in 2025.

Contact: Prof Mohammed Ghazal mohammed.ghazal@adu.ac.ae

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The AI4ALL Framework for Embedding AI Across Learning and Assessment

Innovation

The initiative began with a benchmarking study comparing UAE AI curricula with 21 international frameworks. The analysis, conducted in alignment with Ministry of Education classification efforts, identified gaps in conceptual foundations and revealed uneven student readiness for AI learning. These findings informed the design of ADU’s AI-first approach, AI4ALL, which introduced a foundational 'Introductory Artificial Intelligence' course required across all engineering majors in the college. The course removes traditional barriers, no programming, calculus, or linear algebra, while retaining statistical reasoning, hands-on experimentation, and problem-based learning. This structure enables early, broad access to AI competencies and supports discipline-specific contextualization in domains such as biomedical engineering, computing, and electrical systems. To ensure scalable delivery, the initiative also integrates generative and discriminative AI into learning support and assessment workflows. Generative AI produces individualized explanations, formative quizzes, and differentiated learning resources. Discriminative AI is used to analyze student submissions and generate structured feedback, enabling consistent assessment across large cohorts. The model also includes an ecosystem of AI-enabled classroom tools. This includes a Teaching & Learning Engagement Analytics Device, developed in-house using 3D printing, embedded systems, and machine learning pipelines. It provides real-time indicators of attention and engagement, supporting evidence-informed instructional decisions.

Evidence of impact

The initiative produced measurable changes in student engagement with AI-related coursework, research, and project development. Enrollment in the foundational AI course expanded significantly, with nearly 700 students completing the course in the 2024-25 academic year. The use of generative and discriminative AI tools supported consistency in feedback and assessment across large cohorts, enabling scalable delivery without increasing faculty workload. Student participation in AI-related research increased in parallel. Across the period following the introduction of the AI4ALL model, students produced a growing number of AI-focused papers, several of which progressed to indexed publication. Institutional research analytics show that artificial intelligence became the most active research domain at the university during this period, reflecting a measurable shift in student output and topic selection.

Contact: Prof Mohammed Ghazal mohammed.ghazal@adu.ac.ae

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Holistic AI Integration in Curriculum, Teaching-Learning, and Student Support

Innovation

Bahrain Polytechnic continues to revolutionize itself as the leader of higher education in the region. Propelled by it vision of a Bahrain Polytechnic 2.0, it established employability, entrepreneurship, enterprise and innovation as one of its strategic themes. To achieve the goal of producing work-ready graduates for rapidly evolving industries, the Institution developed its AI Policy Framework for the responsible and ethical use of AI in teaching, learning and assessment, modernized its curriculum through AI integration, and established necessary support for its students and staff. To intensify awareness among students and staff of the comprehensive AI Policy Framework, a series of capacity building workshops and courses were implemented. In addition to these workshops attended by over 15,000 participants, selected academic staff members completed over 80 Coursera courses on AI literacy. These courses provided academic staff members with diverse experiences and insights on the use of AI in different disciplines in the context of higher education. For a more holistic AI utilization, the curriculum was enhanced to integrate specific uses of AI in various courses across programmes. The integration underwent rigorous quality assurance prior to actual classroom implementation. The classroom applications of AI are monitored through classroom observations, internal moderation, and external examination for sharing of best practices. Furthermore, relevant AI tools were adopted and used across the Polytechnic. These include the use of 'Mohammed', a 24/7 AI Assistant Agent programmed specifically for students and staff of Bahrain Polytechnic. 'Mohammed' which is embedded in the Institution’s Learning Management System provides students and staff with various information on policies and procedures, assessments, course contents, and other aspects of the curriculum. Committed to continuous improvement, the Institution conducts periodic surveys among stakeholders to collect feedback on the use of AI for the evidence-based enhancement of key institutional processes, including policies, curriculum, and student support.

Evidence of impact

The institutional strategies of AI integration in policies, teaching-learning and assessments, and student support bear a positive impact on students’ academic journey. Survey results reveal a significantly higher student satisfaction rating in pilot courses (Arabic). Specifically, the satisfaction rating this year is 30% higher than the students’ rating in the previous year when AI was not formally integrated in the curriculum. The high satisfaction rating is attributed to an AI-enhanced learning experience engendered by gamification of learning, timely constructive feedback, personalized learning, remote and round-the-clock accessibility, etc. The high satisfaction rating is linked to a significantly higher student performance, including high efficiency in classroom task completion and self-paced learning. The use of AI in teaching-learning and assessments is perceived to have enhanced students’ skills in preparation for their employment in AI-driven workplaces.

Primary Contact: Dr Sofia Ligawen sofia.ligawen@polytechnic.bh

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A Custom Large Language Model for Arabic Academic Feedback: Experimental Validation in the SSDEC Curriculum

Innovation

My research aims to identify the capabilities of an Arabic model for GPT developed to provide rubric-aligned feedback on assessments taken in an 'Emirate Studies' programme. Using a mixed methods model, the feedback comments generated by the software have been compared for the whole class of students through the examination of six students for the purpose of identifying their diverse input through the software’s concordance. Data analysis indicates very high agreement between the AI system and the instructor on the rubric-level comparisons, where 80% of the comparisons resulted in ‘Exact’ or ‘Close.’ However, the LLM performed better on rule-based tasks like APA compliance, structural issues, citation judgment, and word count follow-through compared to the human instructors on more culture-dependent tasks like the judgment of leadership analysis and heritage-related tasks. Qualitative analysis indicates that instructors tended to use the adaptively modified suggestions from the AI system.

Evidence of impact

The use of an innovative Arabic GPT significantly improved feedback quality, consistency, and efficiency within the curriculum. By deploying a rubric-aligned Arabic LLM, instructors reported a measurable reduction in time spent on mechanical aspects of assessment, especially APA formatting, structural issues, citation accuracy, and word-count checks. Concordance data showed that 80% of AI-generated comments aligned exactly or closely with instructor evaluations, demonstrating strong reliability in rule-driven components of academic writing. This consistency reduced variability in feedback tone and depth across sections, contributing to greater equity in students’ formative learning experiences. Student feedback reflected increased clarity and timeliness of responses, with many noting that immediate AI-generated comments helped them revise more effectively before receiving instructor input. Instructors further confirmed that the system served as an efficient 'first-pass' evaluator, allowing them to allocate more time to higher-order cognitive areas—particularly cultural reasoning, leadership analysis, and UAE-focused civic interpretation. Despite clear limits in cultural-contextual judgment, the hybrid model enhanced overall instructional effectiveness. The institution benefited through improved marking consistency, reduced instructor workload, and the introduction of a scalable, domain-specific approach to Arabic academic writing support. Collectively, the innovation demonstrated both tangible pedagogical gains and a sustainable model for AI-supported assessment in culturally grounded courses.

Contact: Sadeq Telfah stelfah@ra.ac.ae

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EduAI Agent: A Practitioner-Built Ecosystem for AI-Augmented Assessment, Curriculum Quality and Accreditation in Higher Education

Innovation

EduAI Agent is an intelligent platform developed by two academics whose combined expertise spans medical education, quality assurance, and AI application in higher education. The platform was born from a straightforward but urgent observation: existing AI tools were powerful in general terms but fundamentally unfit for the specific, standards-driven demands of higher education practice in the MENA region. Faculty needed something that understood how blueprinting works, how accreditation evidence is structured, and how learning outcomes translate into valid, reliable assessments, not a generic chatbot requiring constant re-prompting and professional translation. EduAI Agent addresses this through a unified, end-to-end workflow. Educators begin by defining or importing programme and course learning outcomes. The platform then supports the construction of an evidence-based exam blueprint, generates assessment items mapped to Bloom's taxonomy cognitive levels, assembles balanced examinations, and produces post-assessment item analysis, all within a single, auditable environment. Accreditation-ready reports and quality documentation are generated automatically, reducing the administrative burden that currently consumes significant faculty time and institutional resource. The platform was designed on constructivist principles: it scaffolds professional judgment rather than replacing it. Every decision remains with the educator. The AI surfaces options, flags gaps, and ensures alignment, but the academic retains full ownership of the process and its outputs. EduAI Agent is bilingual in English and Arabic, locally sensitive to NCAAA, CAA, and international accreditation frameworks, and built on a privacy-first, zero data-retention architecture. It is accessible to any educator regardless of technical background, supporting Saudi Vision 2030 goals of educational excellence, digital transformation, and internationally competitive higher education outcomes.

Evidence of impact

The impact of EduAI Agent has been measurable, immediate, and institution-wide. In pilot implementation at King Abdulaziz University, faculty reported a reduction in exam blueprinting time from an average of three to four hours to under thirty minutes, a saving of more than 80% in preparation time per assessment cycle. This recovered capacity was consistently redirected toward student contact, feedback, and mentorship. Assessment quality improved demonstrably: post-implementation item analysis revealed stronger alignment between cognitive level distribution and intended learning outcomes, with a marked reduction in recall-dominant question sets and a corresponding increase in application and analysis-level items — directly supporting deeper student learning and improved attainment. Accreditation readiness also strengthened significantly. Faculty reported greater confidence in producing NCAAA-aligned documentation, and institutional quality teams noted a reduction in last-minute compliance preparation, replacing reactive cycles with continuous, evidence-based quality assurance. External validation has further confirmed impact: the platform's six-step development framework was formally published in the Journal of Advanced Pharmacy Education and Research (2025).

Contact: Prof Mohammed Hassanien mhassanien@kau.edu.sa

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This innovation is aimed at supporting academic confidence and developing English language skills required for student retention and academic success.

Professor Mohammed Ghazal Professor and Chair of Electrical, Computer and Biomedical Engineering Abu Dhabi University, UAE

Prof Ghazal shares three innovations: 1. a comprehensive Student Success and Continuity Framework to enhance engagement and outcomes; 2. curriculum transformation based around innovation-driven design challenges; 3. the development of an introductory Artificial Intelligence course delivered across all engineering programmes. Read about his work aligned to each theme:

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Theme 2: Aligning Curricula with National Visions

This innovation directly addresses retention and attainment challenges faced by working adult postgraduate students attending evening classes after full workdays. The initiative seeks to enhance engagement and participation, reduce exhaustion-driven disengagement, and improve progression through deeper understanding rather than memorisation, by redesigning the learning environment using UbD, learner profiling and interactive digital tools. This inititive aligns with the Access & Retention and Attainment & Progression areas by removing barriers caused by evening scheduling, supporting belonging and motivation, and enabling diverse adult learners to achieve their full potential.

The innovation addressed key national health priorities identified in regional strategic visions, particularly the high prevalence of chronic diseases such as diabetes and obesity, antimicrobial resistance, mental health needs, and the growing emphasis on digital and AI-enabled healthcare delivery. The challenge was that foundational medical sciences were traditionally taught without explicit connection to these national priorities, leading to limited relevance and reduced learner engagement. By integrating local epidemiological data, national vision goals, and region-specific case-based scenarios into basic medical sciences, the project enhanced curriculum relevance, improved student motivation, and strengthened graduate readiness to contribute to national healthcare targets.

Postgraduate students often work on complex, research-based assignments that require timely, in-depth feedback. Providing personalized feedback at scale is challenging, which can affect engagement, academic performance, and research skill development.

Dr Habil Slade OgaloAssociate Professor and Dean, Business Studies Arab Open University, Bahrain

Dr Ogalo's implementation of a digital Student Success Hub has led to significant improvements in student outcomes and institutional performance. Read about his work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Dr Nora MaherAssociate Professor, Political Science May University in Cairo, Egypt

Dr Maher's work aims to support students struggling academically through the introduction of a series of initiatives aimed at effectively identifying students who require intervention, understanding their challenge and providing the guidance they need to succeed.Read about her work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Theme 2: Aligning Curricula with National Visions

Dr Sameh Fawzy ElsonbatyAssociate Professor, Medical and Health Sciences Liwa University, United Arab Emirates

Dr Elsonbaty transformed curricula to align with national priorities through embedding country-specific healthcare challenges into basic medical sciences module learning, teaching and assessment. Read about his work here:

Theme 2: Aligning Curricula with National Visions

Dr Ahmad HosseiniHead of Education and Community Research Group Global College of Engineering and Technology, Oman

Dr Hosseini's work in GCET's newly formed institution-wide development hub offers data-informed and progression-oriented academic development to empower students to build the competencies required for successful and confident engagement in higher education.Read about his work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Theme 2: Aligning Curricula with National Visions

Dr Ramalingam Dharmalingam SFHEAAssistant Professor, Educational Development Majan University College, Oman

Dr Dharmalingam's innovation directly addresses national workforce development priorities outlined in Oman's Vision 2040, particularly the need to strengthen digital competencies, enhance economic diversification, and build a sustainable talent pipeline for critical industries. Read about his work here:

Theme 2: Aligning Curricula with National Visions

Dr Yurgos PolitisAssistant Professor, Education Abu Dhabi University, United Arab Emirates

Dr Politis developed Research Design module for PhD Education candidates, embedding a focus on ethical governance that aligns with the 'We the UAE 2031' Vision of agility, proactivity, and applied excellence in higher education. Read about his work here:

Theme 2: Aligning Curricula with National Visions

My innovation directly addressed a major emerging challenge within postgraduate education: the rapid expansion of generative AI and its implications for ethical student behaviour, academic integrity, and institutional readiness. As AI tools became widely accessible, both faculty and students experienced uncertainty about boundaries of acceptable use, risks of assessment inflation, and the need to maintain academic standards. The challenge was amplified in postgraduate programmes, where authenticity of reasoning, synthesis and judgement is essential for progression and attainment. Nationally, the UAE has prioritised AI literacy, responsible innovation and future-ready graduate capability. My initiative aligned with these goals by embedding ethical, transparent and pedagogically grounded AI practices into learning, teaching and assessment. By reframing AI not as a threat but as an object of scholarly inquiry, the innovation strengthened access to clear guidance, supported student retention by reducing confusion and anxiety around AI expectations, and enhanced attainment and progression by ensuring assessments fostered authentic intellectual engagement. This positioned postgraduate students to meet national AI readiness goals while safeguarding academic integrity.

Dr Arina ZiganshinaHead of Examination and Assessment Dubai Medical University, United Arab Emirates

Dr Ziganshina introduces an integrated portfolio and mentorship model designed to strengthen competency-based medical education by aligning assessment, reflection, and academic support within a unified system.Read about her work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Theme 2: Aligning Curricula with National Visions

Dr Sana'a Al ReiahyAssociate Professor of Education Abu Dhabi University, United Arab Emirates

Finding that postgraduate students were experiencing fatigue due to combining work and studies, Dr Al Reiahy redesigned the learning experience using the Understanding by Design (UbD) framework to improve student retention, experience and outcomes.Read about her work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Theme 2: Aligning Curricula with National Visions

Dr Noha MostafaAssociate Professor of Industrial Engineering and Management The British University, Egypt

Dr Mostafa integrates real-world industry engagement into engineering education to align with Egypt's Vision 2030, focusing on building a diversified, knowledge-based, and competitive economy. Read about her work here:

Theme 2: Aligning Curricula with National Visions

Dr Bacem Mbarek Associate Professor, Computer Science Gulf College, Oman

Dr Mbarek's innovation incorporates an AI-assisted peer feedback system which has enhanced postgraduate student feedback literacy and outcomes. Read about his work here:

Theme 3: Embedding AI to Enhance Student Experience

Mr Mostafa Youssef Senior Advisor for Academics, Learning and Development The British University in Egypt

Mr Youssef has developed a comprehensive institution-wide professional development approach that includes blended learning pathways, micro-credentials, mentoring schemes, and active communities of practice to enhance the quality of learning and teaching. Read about his work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Dr Amal GadallaVisiting Assistant Professor in Bio-Medical Sciences Abu Dhabi University, United Arab Emirates

Dr Gadalla's innovative approach incorporates active learning pedagogy and structured AI support to enhance student understanding of complex concepts in the bio-sciences. Read about her work here:

Theme 3: Embedding AI to Enhance Student Experience

The initiative responds to two intersecting national priorities: the UAE Ministry of Education’s Outcomes-Based Education Framework (OBEF), which emphasizes industry collaboration, skills alignment, and demonstrable learning outcomes, and 'We the UAE 2031', which prioritizes human-capital development and technological capability to support the nation’s transition to a competitive, innovation-driven economy. The challenge addressed was that conventional course structures enabled students to meet theoretical outcomes yet did not consistently produce applied, industry-relevant outputs aligned with these national expectations. The innovation therefore targets attainment, by requiring students to evidence mastery through functional, prototype-based assessments mapped to OBEF’s industry-linked expectations, and progression, by ensuring that learning outputs translate into research participation, competition pathways, and employability indicators aligned with the UAE 2031 vision. By realigning coursework around design challenges anchored in national technology priorities and OBEF-defined competencies, the curriculum directly addresses the need for graduates who can contribute to emerging sectors and meet UAE workforce and innovation targets.

Rising enrollment in STEM disciplines in the UAE, driven by national priorities outlined in the National Strategy for Higher Education 2030 agenda, created a need to ensure equitable access to practical learning and consistent academic transition support. At the same time, variations in student preparedness highlighted gaps in early retention support, requiring systematic mechanisms that identify students at risk of discontinuity and ensure timely intervention. Strengthening attainment and progression was an additional priority. Employers in the UAE continue to emphasize the need for graduates with demonstrable applied skills, early exposure to industrial environments, and clear pathways into advanced study. This aligns with the country’s workforce development objectives and the broader national agenda to expand a highly skilled, industry-ready STEM workforce. Accordingly, these factors created the need for a comprehensive, multi-layered approach in learning and teaching that enhances access to learning opportunities, supports continuity throughout the program, and improves students’ transition into postgraduate education or employment.

The innovation directly addressed several interrelated challenges affecting access, retention, attainment, and progression within the aerospace engineering program at the Miltary Technical College. Students historically struggled with limited physical access to Gas Turbine Engine systems due to safety restrictions, hangar availability, and the inherent complexity of internal engine processes. This disproportionately affected learners with lower English proficiency, weaker theoretical foundations, or limited prior exposure to practical aerospace environments, reducing their confidence and slowing academic progression. By implementing a Virtual Reality (VR) Gas Turbine Training System, I sought to remove these barriers by providing equitable, repeatable, and high-fidelity access to engine components and internal processes that could not be safely or consistently demonstrated physically. The innovation also aligned with Oman Vision 2040, which prioritizes digital transformation, advanced technological integration, and the development of future skills across higher education. By embedding VR into Module 15, the project strengthened curriculum modernisation efforts and enhanced national workforce readiness for the aviation sector. While not an AI tool, the VR solution represented a significant step in simulation-enhanced and technology-enabled pedagogy, supporting more personalised learning, greater conceptual clarity, and improved attainment. Overall, the project addressed a national priority for technologically advanced STEM education while directly improving students’ ability to access complex content, retain knowledge, succeed in assessments, and progress confidently into higher-level modules and industry pathways.

Our innovation introduces an integrated portfolio and mentorship model designed to strengthen competency-based medical education by aligning assessment, reflection, and academic support within a unified system. Developed and implemented at Dubai Medical University, College of Medicine, the approach addresses longstanding challenges in undergraduate medical education, such as inconsistency in competency tracking, limited reflective practice, and variable mentorship quality, by embedding structured processes, digital tools, and developmental support mechanisms throughout the six-year MD program.

Dr Pamba Rajavarma Associate Professor Manipal Academy of Higher Education, Dubai UAE

Dr Rajavarma's innovation bridges skill gaps and aligns education with industry needs through introducing AI-driven curriculum design and ethical learning companions, promoting the UAE's vision to provide innovative, ethical, and adaptive education. Read about her approach here:

Theme 2: Aligning Curricula with National Visions

Professor Samar AhmedEducation Innovation Rabdan Academy, UAE

Professor Ahmed's innovative approach embeds rubric-guided AI generated feedback, enhancing the clarity and consistency of feedback for learning while reducing workload pressures for teaching staff. Read about her work here:

Theme 3: Embedding AI to Enhance Student Experience

Professor Mohammed Ahmed Hassanien SFHEAProfessor of Clinical Biochemistry King Abdulaziz University, Saudi Arabia

Prof Hassanien introduces EduAI Agent, a practitioner-built intelligent platform that integrates artificial intelligence into the full cycle of assessment design, curriculum quality, and accreditation documentation, designed specifically to meet the needs of HE professionals in the MENA region. Read about his work here:

Theme 3: Embedding AI to Enhance Student Experience

This innovative approach was shotlisted for Best Use of AI in Education award at the QS Reimagine 2025 Awards. Find out more here:

The project seeks to address low confidence and early disengagement among first-year electrical engineering diploma students, especially when moving from theory to hands-on tasks. Students often struggle to access personalised guidance, repeat practical mistakes, and experience anxiety that affects retention, attainment, and progression. The AI-enhanced approach aims to provide real-time, bilingual support and formative feedback to help students build confidence, develop competence, and progress successfully in the programme.

The intervention directly targeted a nationally recognised challenge in higher education: the persistent variability and opacity of assessment feedback, which undermines student attainment, slows academic progression, and particularly disadvantages students who rely on clear, structured guidance to succeed. Across the UAE and the wider region, quality assurance bodies have repeatedly flagged inconsistent feedback practices and slow turnaround times as factors affecting student satisfaction and progression metrics. The innovation also responded to an emerging AI-related national priority: the strategic integration of artificial intelligence into teaching, learning, and assessment in a way that is ethical, transparent, and pedagogically sound. As AI adoption accelerates, institutions are expected to demonstrate responsible deployment that supports learning rather than replacing academic judgment. Our project directly addressed this challenge by embedding a controlled, rubric-guided AI feedback mechanism that enhances, rather than automates, the educator’s role. In terms of attainment and progression, the need was clear. Students at skill-diverse institutions often struggle with interpreting unstructured or overly general comments, leading to repeated errors, reduced confidence, and slower movement through key academic milestones. By standardising the quality, clarity, and actionability of feedback, the intervention tackled this barrier head-on. It ensured equitable access to high-quality developmental guidance, improved students’ ability to understand expectations, and supported smoother progression between assessment points. In addition, the initiative addressed faculty workload pressures, a national sector priority linked to retention and quality enhancement. By reducing marking fatigue and freeing capacity for deeper academic engagement, the project created a more sustainable feedback ecosystem that benefits both students and educators.

This innovation addresses the need to elevate standards in academic research and instruction.

Useful links: Saudi Vision 2030 – Health Sector Transformation Program https://www.vision2030.gov.sa/en/programs/HSTP UAE National Strategy for Wellbeing 2031 https://u.ae/en/about-the-uae/strategies-initiatives-and-awards/government-strategies/wellbeing2031 GCC Health Statistics (Ministries of Health dashboards) Saudi Arabia: https://www.moh.gov.sa UAE: https://www.mohap.gov.ae Oman: https://www.moh.gov.om Qatar: https://www.moph.gov.qa WHO Eastern Mediterranean Regional Health Observatory https://rho.emro.who.int Global Antimicrobial Resistance and Use Surveillance System (GLASS) https://www.who.int/glass AI in Healthcare – MENA Regional Overview (OECD/WHO reports) https://www.oecd.org/health/digital-health Case-Based Learning in Medical Education – Best Practice Guides (Advance HE) https://www.advance-he.ac.uk/knowledge-hub

Dominic HanrattyPrincipal Instructor Military Technical College, Oman

Mr Hanratty's innovation embeds the use of Virtual Reality into learning and teaching to strengthen curriculum modernisation efforts and enhance national workforce readiness for the aviation sector. Read about his work here:

Theme 2: Aligning Curricula with National Visions

Mr Sadeq TelfahLecturer Rabdan Academy, United Arab Emirates

Mr Telfah has researched the use of a rubric-aligned Arabic GPT to improve feedback consistency, quality and efficiency within the curriculum. Read about his work here:

Theme 3: Embedding AI to Enhance Student Experience

The innovation directly addresses national workforce development priorities outlined in Oman Vision 2040, particularly the need to strengthen digital competencies, enhance economic diversification, and build a sustainable talent pipeline for critical industries. Prior to the introduction of this programme, the oil and gas sector faced a dual skills gap: IT graduates lacked exposure to industrial control systems, while engineering graduates lacked advanced computing and cybersecurity skills. This gap restricted access for local learners to specialised technical roles and contributed to high reliance on expatriates. The programme improves retention and attainment by offering contextualised, industry-informed learning experiences, flexible pathways for working professionals, and hands-on lab-based teaching that supports diverse learning needs. With an average annual enrolment of n = 194 and a 95% retention rate, the programme demonstrates strong learner engagement and progression. Approximately 30% (n ≈ 29) of school-leaver students secure employment in the oil and gas sector during or immediately after their studies, evidencing clear progression into high-value careers. Moreover, the programme responds to emerging AI and digital transformation challenges, equipping graduates with IT-OT integration skills essential for automation, data-driven operations, and the adoption of intelligent industrial systems across Oman’s energy sector.

This innovation is aimed at addressing challenges in:1. Attainment (Institution level): 2. Developing Strategic Approaches to Teaching Excellence 3. Staff Recruitment and Development

This innovation was aimed at supporting students with a GPA of under 2.0 to improve their academic standing and chance of success.

Prathibha KrishnapillaiFaculty of Engineering Higher Colleges of Technology, United Arab Emirates

Ms Krishnapillai's innovation uses Generative AI to build student confidence and competence in though providing real-time, bilingual support and formative feedback.Read about her work here:

Theme 3: Embedding AI to Enhance Student Experience

Theme 2: Aligning Curricula with National Visions

Dr Sofia Ligawen, Dexter Cadiente & Hawra Nooh Bahrain Polytechnic, Bahrain

The team at Bahrain Polytechic introduced an institution-wide AI competency framework, designed to promote responsible and ethical use of AI in teaching, learning and assessment. To support implementation, the team designed and delivered a suite of support and development activities and resources, including staff development workshops and an AI-assistance agent. Read about their work here:

Theme 3: Embedding AI to Enhance Student Experience

Dr Manjush KarthikaAssociate Professor, Respiratory and Emergency Medical Care Liwa University, United Arab Emirates

Dr Karthika introduces an evidence-based, institution-wide strategy to enhance faculty readiness for interprofessional education (IPE) as a foundation for improving student progression.Read about his work here:

Theme 1: Enhancing Access, Retention, Attainment and Progression

Theme 2: Aligning Curricula with National Visions

This innovation addresses persistent difficulties undergraduate biomedical sciences students experience when engaging with complex metabolic, physiological, and laboratory concepts. These topics traditionally show high cognitive load, lower attainment, and inconsistent progression into advanced clinical modules. The challenge was to use AI tools to improve conceptual clarity, reduce overwhelming cognitive demand, and create learning conditions that sustain attention during dense scientific teaching. In the same time ensure proper alignment to learning theories. The work aligns with national priorities around digital and AI-enabled education by embedding structured, pedagogically aligned AI tools that support conceptualisation, reasoning, and formative feedback. It contributes to widening student access to learning strategies that help them work more efficiently with complex information.

EduAI Agent was developed to address a confluence of interconnected challenges that sit at the heart of higher education quality in the MENA region. Faculty across the region, particularly those new to AI or working in resource-constrained environments, lacked accessible, institutionally appropriate tools to design high-quality assessments and learning experiences. Generic AI platforms required significant technical literacy and produced outputs misaligned with local accreditation standards, learning frameworks, and Arabic-English bilingual contexts. EduAI Agent was built to close this gap, placing sophisticated AI capability directly in the hands of educators regardless of their technical background.

The initiative addresses three interconnected challenges in AI education within the UAE context:

1. uneven readiness for AI learning due to typical barriers such as programming and advanced mathematics;
2. limited scalability of high-quality AI instruction across large student cohorts;
3. the absence of data-driven teaching practices capable of adapting instruction based on real-time indicators of student engagement.

The innovation responds to these challenges by embedding AI as an early, universal competency across engineering curricula and integrating generative and discriminative AI tools into teaching, assessment, and feedback workflows. The initiative also aligns with national digital transformation priorities and contributes to building AI literacy as a foundational skill for the future workforce.

The innovation addressed a critical need in enhancing the accuracy, efficiency, and reliability of measuring and verifying learning outcomes within e-learning environments. Specifically, it targeted challenges related to ensuring fair access to quality assessment data, improving student retention through timely feedback, and strengthening attainment and progression by providing data-driven insights for continuous improvement. At a national level, the project aligns with priorities to advance digital transformation in higher education and promote evidence-based decision-making. By integrating IBM Watson Analytics into the course reporting process, the innovation supports institutional goals for improving educational quality, transparency, and accountability. From an AI enhancement perspective, the solution addressed the challenge of analyzing large, complex datasets generated through e-learning platforms—tasks that traditionally demanded extensive manual effort and were prone to human error. The AI-driven approach automated data processing, identified performance patterns, highlighted at-risk students, and verified alignment between assessments and intended learning outcomes. Overall, the project responded to the strategic need for robust, AI-enabled mechanisms that enhance access to meaningful analytics, support student success, and elevate the effectiveness of digital teaching and assessment practices.

Dr Neyara RadwanAssociate Professor, Industrial Management Liwa University, United Arab Emirates

Dr Radwan's innovation utilises the AI capabilities of IBM Watson to automate the collection, analysis, and interpretation of learning data to enhance quality assurance processes, student experience and outcomes. Read about her work here:

Theme 3: Embedding AI to Enhance Student Experience

Amol Ganesh DeshmukhProgram Leader Military Technological College, Oman

Mr Deshmukh's work addresses Oman's 2040 Vision by enhancing employability in the Geomatics sector through aligning curricula with professional standards. Read about his work here:

Theme 2: Aligning Curricula with National Visions

The innovation targets access, retention, attainment, and progression by introducing AI-driven curriculum design and ethical learning companions within the ACM framework. It addresses national priorities in the MENA region, such as bridging skill gaps, modernizing outdated curricula, and aligning education with industry needs. By leveraging AI-powered tools for real-time curriculum updates and personalized learning paths, the approach enhances student engagement and retention while promoting ethical technology use. Dynamic course bundling fosters interdisciplinary skills, improving attainment and progression. This solution responds to the challenge of creating adaptive, future-ready education ecosystems that meet regional workforce demands and global standards.

Dr Constantine Andoniou Associate Professor of Education Abu Dhabi University, United Arab Emirates

Dr Andoniou's work on developing a coherent, research-informed framework for ethical and responsible AI integration across postgraduate education promotes an institutional culture of critical and ethical use of AI across learning, teaching and assessment.Read about his work here:

Theme 3: Embedding AI to Enhance Student Experience

Useful additional resources:https://jaymctighe.com/resources/ https://www.nextgenlearning.org/articles/getting-to-know-you-learner-profiles-for-personalization https://www.ascd.org/el/articles/differentiated-learning https://edpsych.pressbooks.sunycreate.cloud/chapter/psychological-constructivism-piagets-theories/