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.

Minorities, Measured Cognitive Skills and the Earnings of Canadians (Working Paper 26)

This paper uses the Statistics Canada Survey of Literacy Skills in Daily Use (LSUDA) to investigate minority-“white”(i.e., non-minority) income differences and the role education and English/French literacy and numeracy skills play in those patterns. There are three principal sets of findings. First, among males, some visible minority groups have substantially lower levels of the measured language and number skills than whites and other more economically successful minorities, and in some cases these differences play a significant role in explaining the observed income patterns. The minority-white income gaps are, however, much smaller for women, and the literacy and numeracy variables do not have much of a role to play in explaining those differences. Second, for men, the minority-white income gaps are largely confined to immigrants, and there are no significant differences amongst the native-born once various factors which affect incomes (including education and the literacy and numeracy measures) are taken into account. For women, though, minority-white income differences only emerge for certain Canadian-born groups when they are differentiated from immigrants, for whom different gaps become apparent. Finally, the measured returns to literacy and numeracy differ significantly by ethnic group and sex. Various implications of the findings are discussed.

A HARD PUSH FOR SOFT SKILLS: AN EXAMINATION OF POLICY AND RESEARCH ON NON-COGNITIVE SKILLS IN CANADIAN K-12 SCHOOLING

Non-cognitive skills have caught the attention of current education policy writers in Canada. Within the last 10 years, almost every province has produced a document including the importance of supporting non-cognitive skills in K-12 students in the classroom. Although often called different names (such as learning skills, cross curricular competencies, and 20th Century Skills) and occasionally viewed through different lenses (such as emotional intelligence skills, character skills, and work habits), what unifies non-cognitive skills within the policy documents is the claim that students that are strong in these skills are more successful in academic achievement and are more successful in post-secondary endeavors. Though the interest from policy-makers and educators is clear, there are still many questions about non-cognitive skills that have yet to be answered. These include: What skills are the most important for teacher’s to support in the classroom? What are these skills’ exact contributions to student success? How can teachers best support these skills? Are there currently reliable and valid measures of these skills? These are very important questions worth answering if Canadian teachers are expected to support non-cognitive skills in their classrooms with an already burdened workload. As well, it can begin to untangle the plethora of research that exists within the non-cognitive realm. Without a critical look at the current literature, it is impossible to ensure that these policies are effective in Canadian classrooms, and to see an alignment between research and policy. Upon analysis of Canadian curriculum, five non-cognitive skills were found to be the most prevalent among many of the provinces: Self-Regulation, Collaboration, Initiative, Responsibility and Creativity. The available research literature was then examined to determine the utility of teaching these skills in the classroom (can students improve on these skills, do these skills impact other aspects of students’ lives, and are there methods to validly and reliably assess these skills). It was found that Self-Regulation and Initiative had the strongest basis for being implemented in the classroom. On the other hand, Creativity still requires a lot more justification in terms of its impact on students’ lives and ability to assess in the classroom.

Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.