COGNITIVE AND LINGUISTIC FACTORS OF READING ARABIC: THE ROLE OF MORPHOLOGICAL AWARENESS IN READING

Scientific reading research has produced substantial evidence linking specific reading components to a range of constructs including phonological awareness (PA), morphological awareness, orthographic processing (OP), rapid automatized naming, working memory and vocabulary. There is a paucity of research on Arabic, although 420 million people around the world (Gordon, 2005) speak Arabic. As a Semitic language, Arabic differs in many ways from Indo-European languages. Over the past three decades, literacy research has begun to elucidate the importance of morphological awareness (MA) in reading. Morphology is a salient aspect of Arabic word structure. This study was designed to (a) examine the dimensions underlying MA in Arabic; (b) determine how well MA predicts reading; (c) investigate the role of the standard predictors in different reading outcomes; and (d) investigate the construct of reading in Arabic. This study was undertaken in two phases. In Phase I, 10 MA measures and two reading measures were developed, and tested in a sample of 102 Grade 3 Arabic-speaking children. Factor analysis of the 10 MA tasks yielded one predominant factor supporting the construct validity of MA in Arabic. Hierarchical regression analyses, controlling for age and gender, indicated that the MA factor solution accounted for 41– 43% of the variance in reading. In Phase II, the widely studied predictor measures were developed for PA and OP in addition to one additional measure of MA (root awareness), and three reading measures In Phase II, all measures were administered to another sample of 201 Grade 3 Arabic-speaking children. The construct of reading in Arabic was examined using factor analysis. The joint and unique effects of all standard predictors were examined using different sets of hierarchical regression analyses. Results of Phase II showed that: (a) all five reading measures loaded on one factor; (b) MA consistently accounted for unique variance in reading, particularly in comprehension, above and beyond the standard predictors; and (c) the standard predictors had differential contributions. These findings underscore the contribution of MA to all components of Arabic reading. The need for more emphasis on including morphology in Arabic reading instruction and assessment is discussed.

A Framework for Citizen-Centred Social Statistics and Analysis (Working Paper 48)

Economic policy-making has long been more integrated than social policy-making in part because the statistics and much of the analysis that supports economic policy are based on a common conceptual framework – the system of national accounts. People interested in economic analysis and economic policy share a common language of communication, one that includes both concepts and numbers. This paper examines early attempts to develop a system of social statistics that would mirror the system of national accounts, particular the work on the development of social accounts that took place mainly in the 60s and 70s. It explores the reasons why these early initiatives failed but argues that the preconditions now exist to develop a new conceptual framework to support integrated social statistics – and hence a more coherent, effective social policy. Optimism is warranted for two reasons. First, we can make use of the radical transformation that has taken place in information technology both in processing data and in providing wide access to the knowledge that can flow from the data. Second, the conditions exist to begin to shift away from the straight jacket of government-centric social statistics, with its implicit assumption that governments must be the primary actors in finding solutions to social problems. By supporting the decision-making of all the players (particularly individual citizens) who affect social trends and outcomes, we can start to move beyond the sterile, ideological discussions that have dominated much social discourse in the past and begin to build social systems and structures that evolve, almost automatically, based on empirical evidence of ‘what works best for whom’. The paper describes a Canadian approach to developing a framework, or common language, to support the evolution of an integrated, citizen-centric system of social statistics and social analysis. This language supports the traditional social policy that we have today; nothing is lost. However, it also supports a quite different social policy world, one where individual citizens and families (not governments) are seen as the central players – a more empirically-driven world that we have referred to as the ‘enabling society’.