Divergent Thinking and Convergent Thinking in the Mathematical Creative Thinking Process in terms of Student Brain Dominance

Divergent thinking and convergent thinking play a very important role in a person's creative thinking process to solve problems and these two types of thinking are related to hemispheric functions that will affect the way a person perceives information processing. This makes research important. The purpose of this study was to obtain a picture of divergent thinking and convergent thinking in the mathematical creative thinking process in terms of brain dominance. The research method used is qualitative with a descriptive exploratory approach. The instruments used were mathematical creative thinking questions, brain dominance tests, and unstructured interviews. The result of this research is that students who dominate the left brain in the creative thinking process are more dominant in convergent thinking, students who dominate the balanced brain in the creative thinking process are balanced in divergent thinking and convergent thinking, while student who dominate the right brain in the creative thinking process are more dominant in divergent thinking.

Testing for Stochastic Dominance up to a Common Relative Poverty Line

Although a wide array of stochastic dominance tests exist for poverty measurement and identification, they assume the income distributions have independent poverty lines or a common absolute (fixed) poverty line. We propose a stochastic dominance test for comparing income distributions up to a common relative poverty line (i.e., some fraction of the pooled median). A Monte Carlo study demonstrates its superior performance over existing methods in terms of power. The test is then applied to some Canadian household survey data for illustration.

Assessing Deprivation with an Ordinal Variable: Theory and Application to Sanitation Deprivation in Bangladesh

The challenges associated with poverty measurement using a cardinal variable have received much attention over the past four decades, but there is a dearth of literature on how to meaningfully assess poverty with an ordinal variable. This article proposes a class of simple, intuitive, and policy-relevant poverty measures for ordinal variables. The measures are sensitive to the depth of deprivations, unlike the headcount ratio. Moreover, under appropriate restrictions, the measures ensure that priority is given to the poorest among the poor when targeting, monitoring, and evaluating poverty alleviation programs. To assess the robustness of poverty comparisons to alternative choices of parameters, the article develops various stochastic dominance tests (some of which are novel contributions to the stochastic dominance literature). The empirical illustration documenting changes in sanitation deprivation in Bangladesh showcases the measures’ ability to identify instances in which overall sanitation deprivation improved while leaving the poorest behind.