Abstract

Higher education systems worldwide are facing increasing pressure to change beyond traditional degree-based models in response to rapid technological advancement, artificial intelligence disruption, and shifting labour market demands. Although the United Arab Emirates has made significant investments in higher education and has a clear vision for a knowledge-based economy, a growing gap between graduate skills and employer needs continues to limit the system’s effectiveness. This thesis explores how the UAE higher education system can move beyond traditional degree models and develop more flexible, skills-based, and future-ready learning systems by 2035. The thesis focuses on how new learning models, such as micro-credentials and online education, can improve graduate outcomes. It also examines how ready the current system is for change, how global trends like artificial intelligence are shaping education, and how a clear future strategy can be developed for policymakers, universities, and employers. The thesis uses a structured foresight approach. First, horizon scanning is used to identify key trends and early signals of change across different areas, including technology, labour markets, and education systems. Then, STEEPV analysis organises these signals across six dimensions, Social, Technological, Economic, Environmental, Political, and Values is applied to organise these trends into key driving forces. Systems thinking and rich picture development, CATWOE analysis, are used to understand how different parts of the system are connected and to identify the main problem, which is the gap between what universities teach and what employers need. Scenario planning is then used to explore four possible futures based on two key uncertainties: the value of degrees in employment and the speed of change in the education system. A roadmap is developed to guide the transition from the current system to a future-ready model. Finally, a primary data validation survey administered to 99 UAE stakeholders across education, industry, and regulatory sectors was conducted to validate and enrich the analytical findings with real stakeholder perspectives. The findings show that the UAE already has strong regulatory frameworks supporting change including outcomes-based education and recognition of prior learning, but the main challenge is slow institutional implementation and a significant awareness gap among practitioners. Artificial intelligence plays a dual role disrupting traditional knowledge-based learning while enabling personalized and flexible education at scale. This was confirmed by 84.9% of survey respondents who agreed AI is fundamentally changing the skills graduates need, while only 48.5% believed universities are currently responding effectively. The scenario analysis highlights a key risk if degree value declines faster than alternatives are accepted, graduates face serious disadvantages. The recent launch of the UAE Skills Platform by the Ministry of Higher Education and Scientific Research and MOHRE in May 2026 an AI-powered national system connecting education to live labor market data directly validates the thesis findings and confirms the preferred future is already being built. The main contribution of this thesis is the Hybrid Degree Model. This model redesigns the traditional degree by making it shorter, more flexible, and focused on skills. It combines academic learning with industry-recognized micro-credentials, practical work experience, and AI-related skills. This approach keeps the cultural importance of the degree while making it more relevant to the labor market. Survey validation confirmed strong stakeholder support 71.8% agreed the model would be more valuable than the current degree and 81.8% supported its introduction in UAE universities. Overall, this thesis provides a practical and UAE-focused solution for the future of higher education. It offers clear guidance for policymakers, universities, and employers to support a smooth transition toward a more flexible and skill-based education system

Publication Date

7-19-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Ozcan Saritas

Comments

This thesis has been embargoed. The full-text will be available on or around 8/4/2027.

Campus

RIT Dubai

Download

Share

COinS