Utilizing Multi-Criteria Decision-Making for Optimal Selection of a Digital Competency Framework for Higher Education

Digital competency frameworks play a pivotal role in shaping modern higher education (HE), particularly in rapidly evolving technological contexts. In Iraq, the integration of robust digital competency frameworks tailored to the specific needs of higher education institutions (HEI) is crucial. However, among numerous available frameworks, selecting the most suitable one poses a significant challenge due to differences in scope, cultural values, practices, available resources, and educational systems. Previous studies or literature in the field have generally overlooked the comparison of competency frameworks to identify the most appropriate one for a given context. This research aims to address this challenge by employing multi-criteria decision-making (MCDM) techniques, including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to systematically evaluate and choose the optimal digital competency framework for Iraq's HE among the worldwide frameworks. Evaluating these frameworks involves examining their alignment with institutional goals, adaptability to diverse educational contexts, scalability, and relevance to specific learning objectives. The research findings can inform policymakers, educational leaders, and stakeholders about adopting digital competency frameworks. This could enhance the academic experience, providing learners and educators with essential digital skills needed for the changing global context.