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Educators face increasing demands to raise student achievement, to improve classroom instruction, and to demonstrate accountability in an environment of high stakes testing. However, meeting these demands is challenging in the face of numerous risk factors that jeopardize the academic success of elementary and secondary students. To that end, the identification of risk factors is an important first step in addressing these demands. This study took a longitudinal approach to the analysis, comparing the incidence of at-risk students in Ohio between the 2000-2001 and 2010-2011 school years utilizing a research-based typology of risk factors to ensure consistency over time. The article begins with a brief literature review on the definition and identification of student risk factors. In the second section, research methods and data sources are described while the third presents results of the statistical analysis. The article closes with a summary of findings and conclusions. (Contains 9 tables and 26 endnotes.)

There is considerable research on the difficulties students have in conceptualising individual concepts of probability and statistics (see for example, Bryant & Nunes, 2012; Jones, 2005). The unit of work developed for the action research project described in this article is specifically designed to address some of these in order to help students create visual and intuitive understandings of the issues of sampling, randomness and populations. The interweaving of concepts, combined with the technical skills, is intended to challenge teachers, students and researchers. Creating meaningful and deep learning experiences for students requires considerable teacher knowledge and skill, being able to weave together concepts with context and metacognitive thinking. In particular, it takes skill in helping students to draw out from diverse activities the central and connecting themes. At the end of the program the lead teacher said she had previously never thought of designing a unit around a key idea such as randomness or inference. Being able to use such big conceptual ideas as a theme for a unit provided a very valuable and interesting experience, certainly deepening her own experience of the nuances within the ideas and how to build more connective conceptual experiences for the students. For students who go on to study formal statistics, the hope is that the experiences with informal inference in memorable contexts such as the dolphin problem will provide a foundation for appreciating and understanding the formal statistics associated with t-tests and p-values. For those who do not go on to study formal statistics, it is hoped that they have gained an appreciation of randomness and its usefulness in decision-making, moving beyond seeing random only as haphazard.

The traditional important role of maps used for educational purposes has gained further potential with recent advances in GIS technology. But beyond specific courses in cartography this potential seems little realized in geography teaching. This article investigates the extent to which any learning benefits may be derived from the use of such technologies. A controlled experiment was conducted to examine whether information recall is improved when cartographic information on population distribution is presented in 2D versus 3D form. The results show statistically significant differences in learning benefits between the two formats, largely in favor of 2D representation. These findings suggest that learning benefits can be derived from paying greater attention to map format in educational settings. (Contains 2 tables and 1 figure.)

Background: Literacy-rich environments (LREs) reflect characteristics such as abundance of materials, daily literacy routine, and layout conducive for reading and writing. Shifting from previous conceptualizations, LREs are not confined to schools but are ubiquitous in formal and informal educational settings; they include libraries, museums, bookstores, and community-based organizations. An ecological approach is important for understanding how literacy is embedded in social life and everyday practice, particularly in relation to literacy learning and development. It recognizes the multitude of practices in various communities and accounts for institutional and social structures that shape everyday practice. Purpose/Objective/Research Question/Focus of Study: The purpose of the study is to examine LREs as part of a broader ecology of literacy and to identify the factors that may influence proximity and accessibility to LREs. An ecological approach paired with geographic information systems (GIS) can yield various types of data visualization about spatial context. St. Louis metropolitan area serves as a viable example in the study. Research Design: The authors employed a mixed methods approach and collected data from several sources. Purposeful sampling was used to identify a number of educational and cultural institutions. GIS tools were central to the creation of maps. Using spatial analysis and data visualization, the authors paid attention to the emerging relationships between spatial patterns and represented demographics, evident on the maps as distance and clustering. Findings/Results: Findings indicate that an uneven geography of opportunity among underserved student populations is further compounded by a fragmented ecology of literacy. The spatial arrangements of LREs suggest an uneven distribution of resources, particularly educational and cultural institutions that shape everyday life. Findings suggest that factors such as race, median household income, and transportation routes influence proximity and accessibility to LREs. Conclusions/Recommendations: This investigation of LREs extends current conversations about literacy and various ecologies of literacy. GIS tools provided a means to examine the geospatial relationships between LREs, schools, and neighborhoods in a particular metropolitan area. Focusing on St. Louis was key not only because of the researchers' growing knowledge of the place but also because there are good reasons to believe that St. Louis, with its uneven and fragmented geography, may exemplify similar phenomena taking place in other metropolitan areas.

Every two years in the United States, districts in each state elect representatives to the U.S. House of Representatives. The district boundaries are not permanent; rather, they are redrawn every ten years in a process known as redistricting. Mathematics is useful in understanding this important and often contentious process. Redistricting is a rich context for teaching and learning mathematics, one that illuminates both American democracy and important mathematical ideas. This article offers suggestions for classroom implementation as well as resources for further exploration. (Contains 4 figures, 1 table and 8 online resources.)

A jack knife is a pocket knife that is put to many tasks, because it's ready to hand. Often there could be a better tool for the job, such as a screwdriver, a scraper, or a can-opener, but these are not usually pocket items. In statistical terms, the expression implies making do with what's available. Another simile, of an extreme situation, is the bootstrap: extricating oneself from a predicament by the only means available. Bootstraps are more empirical than other statistical processes. Given a suitable sample, many population features can be derived from the sample alone. The process takes repeated random samples from the original data. The bootstrap method is flexible and robust, well suited for analysis of data whose population distribution is uncertain, as is often the case in biological studies. For example, assumptions about distribution can be avoided when comparing quanta at synapses. There may be occasions when the bootstrap can fail: for example it is not good with extreme distributions, or to estimate statistics--like the maximum--that depend on very small features of the data. Modern computers make the tedious procedure of repeated sampling straightforward. However, standard textbooks and the standard statistics packages have failed to acknowledge the value of the bootstrap approach. (Contains 4 figures.)

This study serves as a teaching aid for teachers of introductory statistics. The aim of this study was limited to determining various sample sizes when estimating population proportion. Tables on sample sizes were generated using a C[superscript ++] program, which depends on population size, degree of precision or error level, and confidence level. Nineteen different population sizes, five degrees of precision, and three levels of confidence were utilized. The study found that the larger the population size, the higher the degree of precision, and the higher the probability/confidence level, the larger the sample size must be. Two values for the sample estimate of the population proportion were used in this study. Practical applications of randomly pulling appropriate number of samples from huge data sets were also discussed. (Contains 6 tables.)

Multidimensional computer adaptive testing (MCAT) can provide higher precision and reliability or reduce test length when compared with unidimensional CAT or with the paper-and-pencil test. This study compared five item selection procedures in the MCAT framework for both domain scores and overall scores through simulation by varying the structure of item pools, the population distribution of the simulees, the number of items selected, and the content area. The existing procedures such as Volume (Segall in "Psychometrika" 61:331-354, 1996), Kullback-Leibler information (Veldkamp & van der Linden in "Psychometrika" 67:575-588, 2002), Minimize the error variance of the linear combination (van der Linden in "J. Educ. Behav. Stat." 24:398-412, 1999), and Minimum Angle (Reckase in "Multidimensional item response theory," Springer, New York, 2009) are compared to a new procedure, Minimize the error variance of the composite score with the optimized weight, proposed for the first time in this study. The intent is to find an item selection procedure that yields higher precisions for both the domain and composite abilities and a higher percentage of selected items from the item pool. The comparison is performed by examining the absolute bias, "correlation," "test reliability," "time used," and "item usage." Three sets of item pools are used with the item parameters estimated from real live CAT data. Results show that Volume and Minimum Angle performed similarly, balancing information for all content areas, while the other three procedures performed similarly, with a high precision for both domain and overall scores when selecting items with the required number of items for each domain. The new item selection procedure has the highest percentage of "item usage." Moreover, for the overall score, it produces similar or even better results compared to those from the method that selects items favoring the general dimension using the general model (Segall in "Psychometrika: 66:79-, 2001); the general dimension method has low precision for the domain scores. In addition to the simulation study, the mathematical theories for certain procedures are derived. The theories are confirmed by the simulation applications.

Challenging the popular narrative of the long-run decline of the extended family, contemporary studies of intergenerational relations insist that the ties between adult children and their parents are increasing in importance. Although research documents a decline in multigenerational households, there is little empirical evidence on changes over time in other dimensions of intergenerational solidarity. Drawing on 1986 and 2001 data from the International Social Survey Programme, the authors analyzed trends in maternal contact in 7 Western countries: (a) Australia, (b) Austria, (c) Germany (West), (d) Great Britain, (e) Hungary, (f) Italy, and (g) the United States (N = 7,578). They found no evidence that adult children's contact with mothers became less frequent. In particular, contacts that do not require face-to-face interaction increased, consistent with the diffusion of cell phones and Internet use over the period. Although theorizing points to demographic developments as driving trends in intergenerational cohesion, changes in population composition played only a minor role.

The present article examines the effect of population distribution on L1 (Italian) and L2 (German) acquisition in the multilingual context of South Tyrol, Italy. Population distribution is regarded as a central variable to assess the impact of two factors included in willingness to communicate (WTC) theory: (1) Fear of assimilation to the L2 community and (2) Intergroup Climate. The study examines whether the opportunity to communicate in the L1 or the L2 in the immediate living environment has an effect on L1 and L2 acquisition at a single point in time as well as over time. Data were from two different projects: Mivas and Invalsi. The Mivas project examined written competence in the Italian L1 and the German L2 on measures of Fluency, Grammatical Complexity and Lexical Complexity. The final exams of 8th grade multilingual students enrolled in Italian language schools were examined for the year 1979/80 (Italian L1 n=33, German L2 n=37) and 2005/6 (Italian L1 n=41, German L2 n=43). Students' competence in the Italian L1 was also assessed through the results of national standardised testing (Invalsi) carried out in 2009/10 with 2nd grade students (n=1007) in the region. Overall results showed no evidence that living in an environment with a high concentration of L2 speakers is associated to L1 loss either at a single point in time or over time. Also, repeated and frequent exposure to the L2 spoken in the community were found to have a positive effect on L2 acquisition only whenever speakers of the L1 in the immediate living environment were scarce. Opportunity to communicate then seems to have an effect on L2 acquisition but no effect on L1 acquisition. (Contains 1 note and 8 tables.)

Due to a greater number of students enrolling in higher educational institutions, an increase in demand for housing on college campuses exists putting a strain on infrastructure. In order to accommodate the students, some universities are tripling students in residential settings by putting three students in a room originally designed for two. This research investigated whether there are negative effects on students from tripling. Results revealed no differences on depression, anxiety, and stress scales between students who were tripled and those who were assigned double rooms (n = 141). (Contains 1 table and 1 figure.)

The primary objectives of this research were to explore achievement pattern differences and the influence of family factors on the achievement patterns of Afro-Caribbean and African American students within the United States (U.S.). The study utilized two research designs; a causal-comparative and a correlational design. A student family background questionnaire was distributed to a sample of 87 high school students who were either Afro-Caribbean or African American. Additionally, students' chemistry quarterly test scores were obtained and results showed that Afro-Caribbean students outperformed African Americans. The difference was statistically significant (t = 2.43, p less than 0.05). Results also suggested that there were a few significant differences in the Afro-Caribbean and African American students' family background factors. (Contains 4 tables.)

In this article, we present a Bayes factor solution for inference in multiple regression. Bayes factors are principled measures of the relative evidence from data for various models or positions, including models that embed null hypotheses. In this regard, they may be used to state positive evidence for a lack of an effect, which is not possible in conventional significance testing. One obstacle to the adoption of Bayes factor in psychological science is a lack of guidance and software. Recently, Liang, Paulo, Molina, Clyde, and Berger (2008) developed computationally attractive default Bayes factors for multiple regression designs. We provide a web applet for convenient computation and guidance and context for use of these priors. We discuss the interpretation and advantages of the advocated Bayes factor evidence measures. (Contains 5 figures, 1 table and 11 footnotes.)

The federal government promised that it would limit waiver grants to states for the No Child Left Behind Act of 2001 (NCLB). It largely kept that promise, but states did gain significant flexibility through amendments to accountability plans. OLS model estimates showed that larger, more affluent, and more Republican states submitted more amendment requests and the federal Department of Education approved the amendments of states that received more federal funding, had a more developed standardized testing system in place prior to NCLB, and voted Republican. These findings suggested new avenues of exploration for scholars of executive federalism. (Contains 8 notes and 3 tables.)

There has been a significant increase in the use of secondary data sets. Many such data sets purport to be nationally representative. Secondary data sets include research commissioned by the National Center for Education Statistics, the Centers for Disease Control, and other public entities. Research increasingly utilizes these secondary data in their studies as these data sets are easily accessed by researchers. While these data sets are rich with opportunity, researchers must be aware of certain perils not only in the statistical analysis, but also in the proper use of data sets. While these data sets employ several techniques such as stratification and oversampling in order to maximize the representativeness of the data, certain sub-populations still have a tendency to be underrepresented. This study examines the subpopulation of children with autism spectrum disorders (ASDs) and whether they are underrepresented in various secondary data bases. In addition, this study reviews some published studies about children with ASDs which have used secondary data sets in which children with ASDs may be underrepresented. (Contains 1 table.)

Statisticians use words deliberately and specifically, but not necessarily in the way they are used colloquially. For example, in general parlance "statistics" can mean numerical information, usually data. In contrast, one large statistics textbook defines the term "statistic" to denote "a characteristic of a "sample", such as the average score", and the word "parameter" to denote "a characteristic of a "population"." However, for statisticians, statistics means more than just numerical information or a characteristic of a sample. Statistics is also a discipline. It is relevant to all areas of scientific enquiry, and spans study design, data collection, developing methods of analysis and analysing data, interpreting results, and making predictions. Other words that statisticians use carefully, and very particularly, form the cornerstones of statistical reasoning, words such as probability, significance, likelihood. Why does this matter? Well, it may well explain why non-statisticians struggle with the ideas and concepts used by statisticians. The reader is confused by the terminology, not the least because the statistician uses familiar words in different ways, a jargon similar to other professional vocabularies. This necessary precision of language becomes evident when considering one of the statistical methods--"the t test"--commonly used by biological scientists today. There are different ways to look at data. Some provide useful alternatives for scientists. For example, non-parametric tests could be considered. Another possibility may be permutation tests. A natural extension to significance testing is estimation and, in particular, the use of confidence intervals, where a correspondence with significance testing can be made. In this article, the authors describe how Student used statistics to measure the quality of the product at the brewery where he worked. (Contains 3 figures.)

This article presents lists of the top ten schools with most students, largest enrollment, and other categories for 2011 in the U.S. The school districts with most student for 2010-2011 are New York City with 1,043,886 followed by Los Angeles with 667,251, Chicago with 403,770 and down to the 10th spot Orange County (Fla.) with 175,986. The higher-education institutions with the largest enrollment for fall 2010 include the University of Phoenix-online with 307,965, Kaplan University with 77,966, Arizona State University with 70,440 and with Lone Star (Texas) College System with 54,412 on the tenth place. Topping the list of states with most students in public elementary and secondary schools are California with more than 6 million, Texas with more than 4 million and New York with over 2 million students.

An ecological study of age-standardized suicide rates in Belgian communities (1996-2005) was conducted using spatial regression techniques. Community characteristics were significantly related to suicide rates. There was mixed support for the social integration perspective: single person households were associated with higher suicide rates, while religious participation was unrelated and both immigration and the presence of non-European inhabitants had a negative impact. Deprivation had a positive relation with suicide. Population density had a negative influence on suicide rates. Areas with older populations had higher suicide risks than expected. A spatial contagion effect of neighboring communities was present for men. In the conclusion, hypotheses are presented on why an aging population could be associated with higher suicide rates in the community.

According to the Centers for Disease Control and Prevention (CDC), 25 percent of people living with HIV in the United States in 2006 were age 50 and older. HIV prevention for people over 50 is an important health concern, especially as the U.S. population grows older. Scholarly research has identified the need for HIV/AIDS interventions in the population of people over age 50, but few interventions have been established. The ecological perspective, which integrates intrapersonal, interpersonal, organizational, community, and policy factors, was used to review the current interventions and propose possible new HIV/AIDS prevention efforts for older adults. Intrapersonal interventions are often based on the health belief model. The precaution adoption process model was explored as an alternative intrapersonal theory for modeling prevention efforts. Community interventions using diffusion of innovations theory are fully explored, and new interventions are proposed as an option for preventing HIV/AIDS in older adults. An agenda for future research and interventions is proposed. Social workers will be at the forefront of the effort to prevent HIV/AIDS in older adults. They must accept this responsibility, propose interventions, and evaluate their effectiveness.

Since 1999, the Centers for Disease Control and Prevention have trained over 10,000 service providers from more than 5,000 agencies to implement evidence-based HIV prevention interventions through its Diffusion of Effective Behavioral Interventions DEBI) program. Based on in-depth, semistructured interviews with a convenience sample of 22 HIV prevention service providers from eight agencies in Wisconsin who participated in DEBI training, this article explores providers' motivations for attending DEBI training, perceptions of the utility and value of the DEBI program, and criticisms of the program. Providers indicated that they attended training as part of general skill-building efforts, as a way to improve services through the adoption of evidence-based interventions, and to better meet client needs. DEBI training participants were critical of the program's "top down" approach, perceived lack of fit between the DEBI and their target populations, and what they perceived as a lack of evidence that the interventions would work with their particular populations. These results suggest that in order for the DEBI program to be more widely accepted, the experiences and expertise of providers need to be more fully integrated into the processes of developing, disseminating, and adapting evidence-based HIV prevention interventions.

America's changing color line is perhaps best expressed in shifting patterns of neighborhood residential segregation--the geographic separation of races. This research evaluates black exceptionalism by using the universe of U.S. blocks from the 1990 and 2000 decennial censuses to provide a "single" geographically inclusive national estimate (Theil's H) of black residential segregation from whites and other groups, which can be additively decomposed into its "within" (e.g., neighborhood segregation within places) and "between" components (e.g., racial differences between places). The results show that America's blacks are living in blocks that are roughly two-thirds less racially diverse than the U.S. population overall. Nationally, neighborhood segregation processes account for half, or even less, of blacks' segregation from whites, Hispanics and Asians. Declining big-city micro-segregation has been muted by increasing or persistent macro-segregation. Moreover, with growing neighborhood segregation in the suburbs and fringe, America's central cities--the focus of most previous studies--now account for only a minority share of all neighborhood or micro-level segregation between blacks and whites. Evidence of black incorporation or spatial assimilation must account for other levels of geography that extend beyond the traditional focus on neighborhood segregation in big cities. (Contains 2 figures, 2 tables and 14 notes.)

In 2002, more American counties (985) experienced natural decrease than at any time in the nation's history. The incidence of natural decrease has diminished since then, but remains near record levels. It is most common in rural areas remote from metropolitan centers. Spatial concentrations exist in the Great Plains, Corn Belt, and East Texas, with scattered pockets in the Ozark-Ouachita Uplands, Upper Great Lakes, and Florida. A multivariate spatial-error regression model demonstrates that natural decrease is a consequence of the complex interaction between fertility, mortality, and migration over a protracted period and is symptomatic of fundamental changes in the demographic structure of an area. Age-structure changes resulting from protracted, age-specific migration are a primary cause of natural decrease. Temporal variations in fertility also have a significant impact, but counties experiencing natural decrease do not have fertility levels below the national average. (Contains 6 figures, 2 tables, and 9 footnotes.)

Calvin Lunsford Beale was born in Washington, DC, on June 6, 1923, and passed away at age 85 on September 2, 2008. He was a city boy born and bred, and while he "never wanted to live in a rural area" he became one of the most astute observers of rural America in the latter half of the twentieth century. Calvin spent the majority of his professional career in the U.S. Department of Agriculture's Economic Research Service, where he was senior demographer at the time of his death. Together with his longtime friend and colleague Glenn Fuguitt, Calvin was arguably the world's most prominent and influential social scientist studying rural population dynamics. Calvin is generally acknowledged for his substantive contributions to rural population analysis, but he also made lasting contributions in the area of research design. In this article, the authors talk about Calvin Beale's legacy for rural demography. They identify three areas where Calvin Beale's name is firmly affixed to social science understandings of rural people and communities in the United States: (1) migration and population redistribution; (2) subregional variations in rural demographic processes; and (3) racial and ethnic composition of rural populations. (Contains 2 footnotes.)

Children of immigrant backgrounds--children who are immigrants themselves or were born to immigrant parents--are the largest segment of growth in the U.S. school population. In this exploratory interdisciplinary analysis, Filindra, Blanding, and Garcia Coll ask whether the context of policy and political receptivity, even when they are not directed at school reform or at immigrants, nonetheless affects the high school completion of children of immigrant backgrounds. The novelty of this work is its theoretical integration of insights from multiple disciplines and its emphasis on the larger context in analyzing the educational outcomes for children of immigrants. The authors' findings suggest that policy matters and that it matters in different ways. Specifically, they find a strong positive association between the immigrant inclusion in state welfare programs and high school graduation rates for the children of immigrants. At the same time, the study suggests that multiculturalism policies, targeting racial and ethnic minorities rather than immigrants specifically, may have the opposite effect. Finally, the authors suggest that politics also matters, as seen in the gap in graduation rates between the children of immigrants and the children of U.S.-born parents, which is narrower in Democrat-dominated states than it is in Republican-controlled states. (Contains 10 notes, 7 tables, and 2 figures.)

Echolocation is a specialized application of spatial hearing that uses reflected auditory information to localize objects and represent the external environment. Although it has been documented extensively in nonhuman species, such as bats and dolphins, its use by some persons who are blind as a navigation and object-identification aid has received far less attention. Compared with the echolocation performance of an expert who is blind, sighted novices rapidly learned size and position discrimination with surprising precision. In this paper, the authors used a novel task to characterize the population distribution of echolocation skills in sighted persons and report the highest-known human echolocation acuity in the expert who is blind. They showed that perceptual learning of echolocation can be rapid without feedback and that some sighted individuals can be trained in echolocation to a level of precision that approaches that of expert echolocators who are congenitally blind. (Contains 5 figures and 2 tables.)

Convexity-based measures of shape compactness provide an effective way to identify irregularities in congressional district boundaries. A low convexity coefficient may suggest that a district has been gerrymandered, or it may simply reflect irregularities in the corresponding state boundary. Furthermore, the distribution of population within a district can either amplify or lessen the effects of boundary irregularities. As such, it is essential to take both population data and state boundaries into account when using convexity coefficients to detect gerrymandering. Our boundary-adjusted convexity coefficient provides an efficient way to do so, and it yields results similar to the shortest--path approach taken by Chambers and Miller.

Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might result from a process of iterated learning in simple diffusion chains of adults. An iterated artificial language learning methodology was used, in which participants were organised into diffusion chains: the first individual in each chain was exposed to an artificial language which exhibited unpredictability in plural marking, and subsequent learners were exposed to the language produced by the previous learner in their chain. Diffusion chains, but not isolate learners, were found to cumulatively increase predictability of plural marking by lexicalising the choice of plural marker. This suggests that such gradual, cumulative population-level processes offer a possible explanation for regularity in language. (Contains 2 figures.)

The authors use longitudinal data from one large school district to investigate the distribution of principals across schools. They find that schools serving many low-income, non-White, and low-achieving students have principals who have less experience and less education and who attended less selective colleges. This distribution of principals is partially driven by the initial match of first-time principals to schools, and it is exacerbated by systematic attrition and transfer away from these schools. The authors supplement these data with surveys of principals and find that their stated preferences for school characteristics mirror observed distribution and transfer patterns: Principals prefer to work in easier-to-serve schools with favorable working conditions, which tend to be schools with fewer poor, minority, and low-achieving students. (Contains 13 notes, 9 tables, and 1 figure.)

In the first of two experiments, we demonstrate the spread of a novel form of tool use across 20 "cultural generations" of child-to-child transmission. An experimentally seeded technique spread with 100% fidelity along twice as many "generations" as has been investigated in recent exploratory "diffusion" experiments of this type. This contrasted with only a single child discovering the technique spontaneously in a comparable group tested individually without any model. This study accordingly documents children's social learning of tool use on a new, population-level scale that characterizes real-world cultural phenomena. In a second experiment, underlying social learning processes were investigated with a focus on the contrast between imitation (defined as copying actions) and emulation (defined as learning from the results of actions only). In two different "ghost" conditions, children were presented with the task used in the first experiment but now operated without sight of an agent performing the task, thereby presenting only the information used in emulation. Children in ghost conditions were less successful than those who had watched a model in action and showed variable matching to what they had seen. These findings suggest the importance of observational learning of complex tool use through imitation rather than only through emulation. Results of the two experiments are compared with those of similar experiments conducted previously with chimpanzees and are discussed in relation to the wider perspective of human culture and the influence of task complexity on social learning. (Contains 1 table and 2 figures.)

This study examines the density of lottery outlets within ethnically concentrated neighborhoods in Middlesex County, New Jersey, using geospatial statistical analyses. No prior studies have empirically examined the relationship between lottery outlet density and population demographics. Results indicate that lottery outlets were not randomly dispersed across the county but rather were significantly clustered in some census tracts. Using geospatial statistical analysis, percent poverty was found to be negatively related to the density of lottery outlets, while percent commercial use was highly positively related. Percent Hispanic was strongly significant in all the models predicting lottery outlet density and had the highest explanatory power other than percent commercial. Other independent variables, including median household income and race (African American and White) were not found to be significant predictors of lottery outlet density. Implications for policy and research are discussed. (Contains 3 tables and 3 figures.)

Growing accountability pressures, accompanied by a lack of readily accessible measures of institutional performance, have led to an increasing focus on graduation rates. Although previous research has illuminated myriad factors influencing students' likelihood of educational success, it has not paid adequate attention to how state contexts may shape student outcomes. I build on the small but growing body of research exploring the role of state characteristics in facilitating student success in higher education. Controlling for a range of state and individual attributes, I examine how one aspect of the state context--the distribution of enrollments in 2 vs. 4-year public institutions--is related to bachelor's degree attainment of students attending public 4-year colleges and universities. The results suggest that the larger the proportion of students attending community colleges in a state, the higher the probability of bachelor's degree attainment at public 4-year institutions. This appears to be a product of student sorting: the presence of community colleges facilitates sorting of students into higher education in a way that is associated with higher degree completion at public 4-year institutions. These findings have important implications for research on student outcomes and policies aimed at evaluating the performance of public 4-year institutions.

Objective: Major depressive disorder (MDD) occurs frequently in adolescents, but the neurobiology of depression in youth is poorly understood. Structural neuroimaging studies in both adult and pediatric populations have implicated frontolimbic neural networks in the pathophysiology of MDD. Diffusion tensor imaging (DTI), which measures white matter (WM) microstructure, is a promising tool for examining neural connections and how they may be abnormal in MDD. Method: We used two separate approaches to analyze DTI data in adolescents with MDD (n = 14) compared with healthy volunteers (n = 14). Results: The first, hypothesis-driven approach was to use probabilistic tractography to delineate tracts arising from the subgenual anterior cingulate cortex (ACC). Adolescents with MDD demonstrated lower fractional anisotropy (FA) in the WM tract connecting subgenual ACC to amygdala in the right hemisphere. The second, exploratory approach was to conduct a voxelwise comparison of FA. This analysis revealed 10 clusters where adolescents with MDD had significantly lower (uncorrected) FA than the healthy group within WM tracts including right and left uncinate and supragenual cingulum. Conclusions: These preliminary data support the hypothesis that altered WM microstructure in frontolimbic neural pathways may contribute to the pathophysiology of MDD in adolescents. (Contains 3 figures and 3 tables.)

Over the past few decades, a handful of states have chosen to provide state financing of special education programs through a method referred to as "Census-Based" funding--an approach which involves allocated block-grant funding on an assumed basis of uniform distribution of children with disabilities across school districts. The approach has been argued to eliminate financial incentives for classification of marginal--low severity, higher incidence--disabilities. We explain herein that despite some evidence linking headcount-based financing schemes to increased classification rates (a) no evidence exists whether the incentivized rates are more or less indicative of true prevalence of disabilities, and (b) where attempts have been made to discern whether certain populations of children with disabilities are in fact uniformly distributed, researchers have found that they are not. We use U.S. Census data on families of children with disabilities to evaluate the geographic and demographic distribution of those families in Pennsylvania and New Jersey, finding high degrees of geographic clustering, relationships between census disability rates, census poverty rates, geographic locations and school district classification rates. In short, we find families of children with disabilities to be non-randomly and non-uniformly distributed across geographic spaces in Pennsylvania and New Jersey. We conclude by evaluating the equity consequences of assuming falsely that these children are distributed uniformly. (Contains 8 footnotes, 3 tables, and 16 figures.)

The book "If the World Were a Village," by David J. Smith, is the context for analysing and creating graphs of the world's demographic information. Students examine numerical information regarding the more than six billion world inhabitants by imagining the world's population as 100 people.

The traditional way of equating the scores on a new test form X to those on an old form Y is equipercentile equating for a population of examinees. Because the population is likely to change between the two administrations, a popular approach is to equate for a "synthetic population." The authors of the articles in this issue of the journal try to avoid the arbitrariness in the definition of a synthetic population by equating X to Y for the population G1 that takes the new form. The author has been happy to notice the authors' attention to the topic of bias in linear equating. The equating literature has been dominated by an interest in the standard error of equating, but bias is the primary criterion for evaluating the success of an equating. After all, equating is an attempt to remove the bias in the score on the new test form as an estimate of the score on the old form due to scale differences between them. A focus only on the standard error of equating prevents one from noticing any remaining bias in the equated scores, or even possible new bias added to them in the equating process. In this article, the author discusses a little further the issue of bias in linear equating. (Contains 1 figure.)

This article presents the authors' rejoinder to commentaries on linear equating and the NEAT design. The authors appreciate the insightful work of the commentary writers. Each has made a number of interesting points, many of which the authors had not considered at all. Before responding to some of those points, the authors reiterate what they see as the main results of their work. First, they developed five distinct linear equating models within a common framework. Second, their results indicate that the choice of relationship between total test scores and anchor test scores can make a big difference in the equating relationships and in the degree of bias in these relationships. Third, they found that when the groups differ in performance, the Levine methods make the largest adjustments, the "Tucker" methods make the smallest adjustments, and the chained linear method makes adjustments that are between these two extremes. Fourth, in developing the model based on a chained linear relationship approach, they generated a derivation of the Levine true-score method that does not explicitly rely on assumptions about true-score relationships and, thereby, avoids the awkward necessity pointed out by Kolen and Brennan (2004, pp. 117-118). Fifth, their results and those of others suggest that the weights used to specify the synthetic population in the parameter substitution methods do not make much difference in how the resulting equating relationships function. Sixth, they suggested that in comparing different linear equating methods in terms of the overall location of the line, the mean intercept is far more informative than the traditional "Y" intercept. All of the commentaries broadened the discussion in ways that the authors had not considered. They put the authors' results into a larger framework of equating, and in doing so raised a number of issues that they probably should have addressed, or at least acknowledged. (Contains 1 figure.)

At approximately 9,500 years old, two sets of human remains from La Jolla, California (W-12), known as the University House Burials due to the physical location of their discovery on property owned by the University of California, San Diego, are some of the oldest in the United States. These burials are central to a repatriation controversy between the University of California, San Diego, and the Kumeyaay Cultural Repatriation Committee, which represents 12 federally recognized Kumeyaay/Diegueno tribal governments in San Diego County, California. The story of the La Jolla burials is a politically complicated one involving the Kumeyaay Indian Tribe's efforts to claim and repatriate the La Jolla remains, the University of California, San Diego's property issues and scientific interests, the local community's concerns, federal law, and the question of the population origins of the La Jolla remains. This final point has become central to determining who should ultimately have control over the final disposition of the burials, a point that has been, and will be, at the heart of many repatriation disputes. This article focuses on the science of determining the origins of all remains of great antiquity, including the La Jolla burials themselves. (Contains 64 notes.)

How can teachers encourage their geography students to make sense of big numbers? The key math skills geography students need to apply are ones they learned long ago in fifth grade: estimation and place value. However, in order to recognize the size of a city, or strength of a country's per capita income, or value of a birth rate, they need practice. Using the Population Reference Bureau's 2008 World Population Data Sheet, the author suggests that teachers encourage students to create comparison statements, using math vocabulary. They should model some examples to help students get started. Then they should encourage students to analyze statements. Later, teachers should encourage students to find their own comparison data within a specific region. Quickly, though, students enjoy finding their own interesting sets of data, and learn to express their comparisons with mathematical precision. (Contains 5 tables.)

This article describes an easy and cheap laboratory exercise for students to discover their own mitochondrial haplogroup. Students use buccal swabs to obtain mucosa cells as noninvasive tissue samples, extract DNA, and with a simple polymerase chain reaction-restriction fragment length polymorphism analysis they can obtain DNA fragments of different sizes that can be visualized in agarose gels. The analysis of these fragments can reveal the mitochondrial haplogroup of each student. The results of the exercise can be used to provide additional insights into the genetic variation of human populations. (Contains 3 figures and 3 tables.)