Considering the importance of knowledge and its role in achieving sustainable human development, the Arab Knowledge Index seeks to inform the decision-making process based on the systematic analysis of data, facts and information. Building on the three previously published Arab Knowledge Reports, the AKI adopts a scientific methodology up to the highest international standards, taking into account the specificities of the Arab region and its development dilemmas. It employs six composite sub-indices: Pre-University Education; Technical Vocational Education and Training (TVET); Higher Education; Economy; ICT; and R&D and Innovation, which all interact with each other.
The Arab Knowledge Index covers all 22 Arab countries and employs the most recent and reliable data for each of the variables and the countries. Construction of constituent indicators and the selection of feeding variables is based on a scientific process that has also been further verified and refined through consultations with leading experts from inside and outside the Arab region.
Download the Concepts and Methodology 2016 ( 14 pages, 397 KB) from the Arab Knowledge Index 2016
Download the Concepts and Methodology 2015 ( 18 pages, 342 KB) from the Arab Knowledge Index 2015
At the statistical level, data was collected from credible international datasets (UNESCO, World Bank, ILO, World Economic Forum) and treated as if clean and error-free, in addition to addressing any variables that might potentially incur bias on the values of the indicator, by using appropriate statistical methods. Total interpretive values of the sectoral indicators were standardised on a scale from 1 to 100. Arithmetic aggregation was used in determining the values of sub-indicators for the Arab Knowledge Index through applying a series of consecutive aggregations, starting at the variables' level and up to reaching the final Index level. Results indicated non-sensitivity of the indicators to the methods of standardisation and weight-assignment and aggregation.
Internal weights were set independently in each sectoral index, and similarly at the level of pillars, sub-pillars, components and sub-components, with some being assigned equal weights and others using methods of budget allocation and variable analysis. Assigned weights by either the budget allocation or variable analysis ended up in high coherency with each other, and also in line with the preliminary anticipations of the researchers in accordance with the conceptual and theoretical frameworks.