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PurposeThe primary purpose of this study is to examine how fan attendance at team special events and player appearances impact fan consumption (as measured by merchandise sales). Insights obtained could shed light on opportunities for professional soccer teams to expand revenues through enhanced fan consumption of goods and services.Design/methodology/approachA sample of 499 season ticket holders were used to assess fan consumption by measuring merchandise sales. Ordinary least squares (OLS) regressions were run for merchandise sales as the dependent variable of fan consumption. The control variables were age, gender (male = 1, 0 otherwise), and whether an individual has children.FindingsThe key independent variables of attending special events and fan–player bonding were both found to have a statistically significant impact on merchandise sales. Results show that each additional special event attended generates up to $33.71 in merchandise sales for the club. Similarly, each fan–player bonding experience attended also has a direct impact, increasing merchandise consumption by $23.00.Social implicationsThe results of this study provide insights that can help fan consumption grow within the professional United States soccer industry and better allow team managers to make decisions about the possible benefits of holding more special events and fan–player bonding experiences. The findings also confirm the impact personal relationships with fans can have on the bottom line of sport franchises.Originality/valueThough this study adds to the body of literature by expanding previous work on fan consumption, there are limited studies on the social aspects of consumption which are examined and analyzed within this study, particularly of note is the study of merchandise sales as proxy for fan consumption.

Objective Throughout the COVID-19 pandemic, there have been concerns about the mental health of health care workers (HCW). Although numerous studies have investigated the level of distress among HCW, few studies have explored programs to improve their mental well-being. In this paper, we describe the implementation and evaluation of a program to support the mental health of HCW at University Health Network (UHN), Canada's largest healthcare network. Methods Using a quality improvement approach, we conducted a needs assessment and then created and evaluated a modified stepped-care model to address HCW mental health during the pandemic. This included: online resources focused on psychoeducation and self-management, access to online support and psychotherapeutic groups, and self-referral for individual care from a psychologist or psychiatrist. We used ongoing mixed-methods evaluation, combining quantitative and qualitative analysis, to improve program quality. Results The program is ongoing, running continuously throughout the pandemic. We present data up to November 30, 2021. There were over 12,000 hits to the UHN's COVID mental health intranet web page, which included self-management resources and information on group support. One hundred and sixty-six people self-referred for individual psychological or psychiatric care. The mean wait time from referral to initial appointment was 5.4 days, with an average of seven appointments for each service user. The majority had moderate to severe symptoms of depression and anxiety at referral, with over 20% expressing thoughts of self-harm or suicide. Post-care user feedback, collected through self-report surveys and semistructured interviews, indicated that the program is effective and valued. Conclusions Development of a high-quality internal mental health support for HCW program is feasible, effective, and highly valued. By using early and frequent feedback from multiple perspectives and stakeholders to address demand and implement changes responsively, the program was adjusted to meet HCW mental health needs as the pandemic evolved.

Background Delirium is an acute neurocognitive disorder that affects up to half of older hospitalized medical patients and can lead to dementia, longer hospital stays, increased health costs, and death. Although delirium can be prevented and treated, it is difficult to identify and predict. Objective This study aimed to improve machine learning models that retrospectively identify the presence of delirium during hospital stays (eg, to measure the effectiveness of delirium prevention interventions) by using the natural language processing (NLP) technique of sentiment analysis (in this case a feature that identifies sentiment toward, or away from, a delirium diagnosis). Methods Using data from the General Medicine Inpatient Initiative, a Canadian hospital data and analytics network, a detailed manual review of medical records was conducted from nearly 4000 admissions at 6 Toronto area hospitals. Furthermore, 25.74% (994/3862) of the eligible hospital admissions were labeled as having delirium. Using the data set collected from this study, we developed machine learning models with, and without, the benefit of NLP methods applied to diagnostic imaging reports, and we asked the question “can NLP improve machine learning identification of delirium?” Results Among the eligible 3862 hospital admissions, 994 (25.74%) admissions were labeled as having delirium. Identification and calibration of the models were satisfactory. The accuracy and area under the receiver operating characteristic curve of the main model with NLP in the independent testing data set were 0.807 and 0.930, respectively. The accuracy and area under the receiver operating characteristic curve of the main model without NLP in the independent testing data set were 0.811 and 0.869, respectively. Model performance was also found to be stable over the 5-year period used in the experiment, with identification for a likely future holdout test set being no worse than identification for retrospective holdout test sets. Conclusions Our machine learning model that included NLP (ie, sentiment analysis in medical image description text mining) produced valid identification of delirium with the sentiment analysis, providing significant additional benefit over the model without NLP.

Introduction: Schizophrenia is associated with stroke incidence and case-fatality but the causes of this are not well-understood. We evaluated the association between comorbid schizophrenia and the quality of secondary prevention care after ischemic stroke. Methods: We used linked health administrative data to identify adults discharged alive from acute care hospitals in Ontario, Canada between 2004 and 2017 following an incident ischemic stroke and identified those with a history of schizophrenia using a validated algorithm. Outcomes were screening, treatment among those with the risk factor, control of vascular risk factors, and receipt of outpatient physician services. We used modified Poisson regression to model the relative risk of each indicator outcome among persons with and without schizophrenia who were alive one year after discharge, adjusting for age, sex, income, comorbidity and rural residence. Results: Among 85,046 persons with ischemic stroke, 886 (1.04%) had a diagnosis of schizophrenia. Those with schizophrenia were younger (median age 64 vs 72), more likely to be female (50.1% vs 44.6%), live in the lowest neighbourhood income quintile (41.1% vs 23.0%) and have diabetes (42.8% vs 32.3%). Of those alive 1 year after stroke, those with schizophrenia were less likely to be screened for hyperlipidemia (adjusted relative risk (aRR) 0.89; 95% confidence interval (CI) 0.84 to 0.94) or diabetes (aRR 0.93; 95% CI 0.89 to 0.97), be prescribed antihypertensive agents (aRR 0.96; 95% CI 0.93 to 0.99), or achieve target lipid levels (LDL < 2 mml/L) (aRR 0.87; 95% CI 0.78 to 0.96). There were no differences in prescription of antilipemic (aRR 0.96; 95% CI 0.91 to 1.01) or antiglycemic (aRR 0.95; 95% CI 0.87 to 1.03) agents or in achievement of target HbA1c ≤ 7% (aRR 0.89; 95% CI 0.78 to 1.02). Outpatient stroke specialist care in the 3 months after discharge was less likely among those with schizophrenia (aRR 0.72; 95% CI 0.65 to 0.78) as were visits to primary care physicians (aRR 0.93; 95% CI 0.91 to 0.96). Conclusions: People with schizophrenia and stroke are less likely to receive secondary preventive care across many indicators measured. This information may be useful for targeted interventions to improve post-stroke care in those with schizophrenia.

In this narrative review, we describe what is known about non-pharmacological and pharmacological treatments for insomnia in medical inpatients, with a focus on melatonin. Hospital-acquired insomnia is common, resulting in shortened total sleep time and more nighttime awakenings. Sleep disturbance has been shown to increase systemic inflammation, pain, and the likelihood of developing delirium in hospital. Treatment for insomnia includes both non-pharmacological and pharmacological interventions, the latter of which requires careful consideration of risks and benefits given the known adverse effects. Though benzodiazepines and non-benzodiazepine benzodiazepine receptor agonists are commonly prescribed (i.e., sedative-hypnotics), they are relatively contraindicated for patients over the age of 65 due to the risk of increased falls, cognitive decline, and potential for withdrawal symptoms after long-term use. Exogenous melatonin has a comparatively low likelihood of adverse effects and drug–drug interactions and is at least as effective as other sedative-hypnotics. Though more research is needed on both its effectiveness and relative safety for inpatients, small doses of melatonin before bedtime may be an appropriate choice for inpatients when insomnia persists despite non-pharmacological interventions.

Personalized learning technologies such as automated reading tutors have been proposed as a way to help struggling readers acquire needed skills while simultaneously encouraging engaged, sustained reading of entire books. This article investigates a key step in the development of such technologies: translating an entire novel into a sequence of nonoverlapping reading passages, so that valid feedback about students’ performances can be generated at the end of each tutoring session. A critical reliability issue that may be introduced at this step is identified, an approach for addressing that issue is proposed, and an evaluation conducted with respect to three popular middle-grade novels is presented. The findings suggest that our new approach provides more reliable evidence about students’ abilities and thus may be more appropriate for use when building automated reading tutors.

Automated text complexity measurement tools (also called readability metrics) have been proposed as a way to help teachers, textbook publishers, and assessment developers select texts that are closely aligned with the new, more demanding text complexity expectations specified in the Common Core State Standards. This article examines a critical element of the validity arguments presented in support of proposed metrics: the claim that criterion text complexity scores developed from students’ responses to reading comprehension test items are reflective of the difficulties actually experienced by students while reading. Evidence that fails to support this assertion is examined, and implications relative to the goal of obtaining valid, unbiased evidence about the measurement properties of proposed readability metrics are discussed.

A model-based approach for matching language learners to texts of appropriate difficulty is described. Results are communicated to test takers via a targeted reading range expressed on the reporting scale of an automated text complexity measurement tool (ATCMT). Test takers can use this feedback to select reading materials that are well matched to their abilities, that is, materials that are expected to be challenging, yet not so challenging as to cause frustration or reduce motivation. An application to the problem of helping students prepare to take the TOEFL iBT® test is presented.

The TextEvaluator® text analysis tool is a fully automated text complexity evaluation tool designed to help teachers and other educators select texts that are consistent with the text complexity guidelines specified in the Common Core State Standards (CCSS). This paper provides an overview of the TextEvaluator measurement approach and summarizes evidence related to three key claims in the TextEvaluator validity argument: (a) TextEvaluator has succeeded in expanding construct coverage beyond the two dimensions of text variation that are traditionally assessed by readability metrics; (b) the TextEvaluator strategy of estimating distinct prediction models for informational, literary, and mixed texts has succeeded in generating text complexity predictions that exhibit little, if any, genre bias; and (c) TextEvaluator scores are highly correlated with text complexity judgments provided by human experts, including judgments generated via the inheritance method and judgments generated via the exemplar method. Implications with respect to the goal of helping teachers and other educators select texts that are closely aligned with the accelerated text complexity exposure trajectory outlined in the CCSS are discussed.

This paper empirically examines the relationship between services trade liberalization and economic growth. Services trade currently comprises approximately 20 percent of total world trade, with more than half of the world’s labor force employed in service sectors. The possibility that reducing barriers can enhance global production is increasingly receiving attention. The impact of liberalization on growth is empirically assessed by including services trade restrictiveness as the key variable of interest in cross-sectional estimations of a global production function. Income dummies were interacted with levels of services trade restrictiveness to discern variations of influence across countries at different income levels. Services trade restrictiveness is captured using a World Bank index for a pooled cross-section of countries. Robustness of results are evaluated using a similar services trade restrictiveness index recently constructed by the OECD for member countries. The results suggest that services trade liberalization has a positive impact on a country’s per capita GDP. This benefit of service liberalization is larger in countries with greater services export values. In addition, service liberalization in low income countries has a greater impact on per capita income levels than does service liberalization in high income countries. While positive and statistically significant, the scale of the effect appears small. The robustness of the results were tested using an alternate measure of services trade restrictiveness for OECD countries. These robustness results validated the benchmark results and also suggested, for high income countries, the liberalization of services trade may have a non-linear influence on per capita income growth. These findings underscore the importance of including service trade liberalization as a part of trade policy discussions and development agendas, as liberalization of services restrictions may stimulate growth in per capita income and highlights that removing the barriers to services trade can positively impact income levels, especially in low-income countries. Currently, policies surrounding services trade liberalization largely occur at the bilateral agreement level. However, as knowledge grows about the possible benefits of services trade liberalization, movement towards multilateral recommendations may be optimal.

This paper considers whether the sources of linguistic complexity presented within texts targeted at 1st-grade readers have increased, decreased, or held steady over the 52-year period from 1962 to 2013. A collection of more than 450 texts is examined. All texts were selected from Grade 1 textbooks published by Scott Foresman during the targeted time period. Analyses are implemented using the TextEvaluator® tool, a comprehensive text complexity evaluation tool designed to help teachers, textbook publishers, and test developers identify and quantify text-based sources of comprehension difficulty within informational, literary, and mixed texts. Results suggest that 1st-grade textbooks published over the past half century have included an increasing proportion of informational passages, and this shift has been accompanied by the following specific changes: (a) an increase in the proportion of words that tend to appear less frequently in printed text, (b) an increase in the proportion of words that are more characteristic of academic text as opposed to fiction or conversation, (c) lower levels of referential cohesion, (d) lower levels of narrativity, and (e) fewer instances of an interactive/conversational style. These findings suggest that, in contrast to the claim of a “general, steady decline” in textbook complexity, text-based sources of comprehension difficulty within Grade 1 texts have either risen or held steady throughout the past half century.

The TextEvaluator® text analysis tool is a fully automated text complexity evaluation tool designed to help teachers, curriculum specialists, textbook publishers, and test developers select texts that are consistent with the text complexity guidelines specified in the Common Core State Standards. This paper documents the procedure used to align the TextEvaluator reporting scale with the Common Core text complexity scale and provides score ranges for use when placing texts into grade bands. Three evaluations of the proposed score ranges are reported: one implemented with respect to the set of 168 exemplar texts provided in Appendix B of the Common Core State Standards, one implemented with respect to a set of 10 career texts, and one implemented with respect to a set of 59 texts selected from textbooks assigned in first-year, credit-bearing college courses. Results suggest that the proposed ranges can help users determine an appropriate grade band placement for any text that has been evaluated by TextEvaluator, including informational, literary, and mixed texts.

The TOEFL® family of assessments includes the TOEFL® Primary™, TOEFL Junior®, and TOEFL iBT® tests. The linguistic complexity of stimulus passages in the reading sections of the TOEFL family of assessments is expected to differ across the test levels. This study evaluates the linguistic complexity of each passage in a corpus of TOEFL stimulus passages. The analysis was conducted using the TextEvaluator®, a comprehensive text analysis system developed at Educational Testing Service (ETS). For each TOEFL reading passage, TextEvaluator provides an overall complexity score and 8 component scores that measure text complexity in specific domains. The results suggest that the overall complexity scores of the reading passages selected for use at different test levels are significantly different. According to the analysis of the component scores, the TOEFL Primary, TOEFL Junior, and TOEFL iBT passages are similar with respect to some aspects of text variation and distinct with respect to others. Score ranges based on the distributions of the overall complexity scores and the distributions of the component scores of all the passages at each test level can be used as guidelines to develop or select new passages.

Using a panel of up to 116 countries from 1970 to 2010 we estimate the effects of foreign aid flows on a variety of measures of institutional quality. We find that aid flows are associated with the deterioration of both political and economic institutions. Regarding the latter, aid flows are associated with deterioration in a recipient's legal system and property rights, as well as its openness to international trade. Controlling for both political and economic institutions in growth regressions, the latter is robustly, positively associated with growth. After controlling for institutional quality, aid flows are not otherwise significantly related to growth.

I. INTRODUCTION For more than 20 years economic freedom has been on the rise throughout the world. The Fraser Institute scores individual countries in terms of their economic freedom on a scale of 0-10, with 10 indicating most free. The average Economic Freedom of the World (EFW) score rose from about 5.7 in 1990 to about 6.9 in 2010. This increase of 1.2 points followed 20 years of stagnation where the average score declined slightly from about 5.88 in 1970. Starting in 1990, however, the average country saw its government expenditures share shrink, its regulations of markets become less burdensome, and its barriers to international trade become smaller. (1) The time period since 1990 has also corresponded to increasing global interconnectivity associated with the proliferation of the Internet. Following the introduction of commercial Internet service providers (ISPs) in 1989, the rate of worldwide Internet use has grown exponentially. Starting from less than .05% of the world population in 1990, nearly 30% of people used the Internet in 2010, and nearly 35% in 2012. (2) In this paper, we ask if these corresponding trends--increasing Internet use and increasing economic freedom--are not merely coincidental. To wit: is Internet use an important impetus for institutional change? Numerous researchers have stressed the importance of institutional quality for economic growth and well-being. (3) As Rodrik, Subramanian, and Trebbi (2004) famously proclaimed: institutions rule. The concept of economic freedom embodies various dimensions of institutional quality that have been shown to positively correlate with growth in cross-country samples (e.g., Ayal and Karras 1998; Dawson 1998; Gwartney, Lawson, and Holcombe 1999; Heckelman and Stroup 2000; Young and Sheehan 2014). (4) Economic freedom has, furthermore, been shown to correlate positively with health outcomes (Stroup 2007), political freedoms (Lawson and Clark 2010), the extent of trust within a population (Berggren and Jordahl 2006), and measures of subjective well-being (Gehring 2013; Nikolaev 2014; Ovaska and Takashima 2010). (5) Understanding which factors lead to the expansion of economic freedom is of clear importance to students of economic development. We estimate the relationship between Internet use and changes in EFW scores in a panel of up to 114 countries for the years 1990 through 2010. The estimated relationship is generally positive, but it also appears to be conditional on a country's initial level of economic freedom. Starting from an EFW score of about 6 or lower, the marginal effect is positive and statistically significant. Countries with 2010 EFW scores around this threshold included China, Nigeria, and Pakistan. Alternatively, our preferred estimates imply that starting from a score of about 7.7 or higher the relationship turns negative, and that the negative marginal effect is statistically significant starting from EFW scores greater than 8.5. However, only two countries, Hong Kong and Singapore, had 2010 EFW scores greater than 8.5. Our research is motivated by several studies that empirically identify cross-country institutional spillovers and their effects. Bosker and Garretsen (2009) find that an important determinant of a country's economic growth is the institutional quality of its neighbors. Leeson and Dean (2009), Seldadyo, Elhorst, and de Haan (2010), and de Groot (2011) all report evidence suggesting that countries cluster according to their institutional qualities. Furthermore, Simmons and Elkins (2004) find that countries do not indiscriminately copy their neighbor's policy innovations; rather, they specifically adopt liberalizing innovations. In all of the above studies, a country's neighbors are defined in the conventional, geographic sense of the term. Our point of departure is to acknowledge that the Internet allows individuals to transcend geography. In discussing the importance of institutional quality for economic development, Hayek (1960, 30) stresses that "we should provide the maximum of opportunity for unknown individuals to learn of facts that we ourselves are yet unaware of and to make use of this knowledge in their actions. …

Many proposed cohesion metrics focus on the number and types of explicit cohesive ties detected within a text without also considering differences in the ease or difficulty of required referential and connective inferences. A new cohesion measure structured to address this limitation is proposed. Empirical analyses confirm that this new measure performs similarly to existing measures when applied to the simpler problem of detecting lower and higher cohesion versions of the same text, yet is significantly more effective than existing measures when applied to the more complex problem of distinguishing different texts rated by human experts as requiring lower or higher levels of reading comprehension skill. Implications of these findings relative to the goal of helping teachers and other educators select texts for use in instruction and assessment are discussed.

Adam Smith famously argued that increased competition in religion would result in more religious tolerance and that the benefits of competition in the marketplace would also be seen in religious instruction when many religious sects are tolerated. We use a cross-section of a maximum of 167 countries to explore whether increased religious competition results in less governmental regulation of religion and less governmental favoritism of religion. Our measure of religious regulation and favoritism comes from the Association of Religion Data Archives. Our empirical analysis also explores the influence of economic and political factors, including the size of the economy, openness of trade, legal origins, education, the amount of checks and balances on the government and the role of democracy.

We have developed the TextEvaluator system for providing text complexity and Common Core-aligned readability information. Detailed text complexity information is provided by eight component scores, presented in such a way as to aid in the user’s understanding of the overall readability metric, which is provided as a holistic score on a scale of 100 to 2000. The user may select a targeted US grade level and receive additional analysis relative to it. This and other capabilities are accessible via a feature-rich front-end, located at http://texteval-pilot.ets.org/TextEvaluator/.

One source of potential difficulty for struggling readers is the variability of texts across grade levels. This article explores the use of automatic natural language processing techniques to identify dimensions of variation within a corpus of school-appropriate texts. Specifically, we asked: Are there identifiable dimensions of lexical and discourse/genre variation among these texts, and what are major differences among 3rd- to 6th-grade texts? At the lexical level, we identified sets of nonspecific lexical terms that appear to be used across wide sets of texts, another that appears to be more "academic" in nature, and a large number of topic specific sets. Additional analyses detected several dimensions of variation that were fairly similar to the dimensions detected in previous studies (e.g., Biber, 1988; Reppen, 2001), as well as several new dimensions. In comparing 3rd and 6th grade level texts, we observed a shift in the distribution of texts on several dimensions.

Objectives: This study measured the response of deoxypyridinoline, a biomarker of bone resorption, during 11 weeks of Marine recruit training. Methods: Urine samples were obtained from 155 female and 58 male Marine recruits from the first morning void every 3 days during training. Training miles of weight-bearing exercise were recorded daily, and injury data were obtained from the medical clinic staff. Results: Deoxypyridinoline was significantly (p < 0.001) increased at week 2 and weeks 9 through 11 for women and at weeks 10 and 11 for men. The increase in bone resorption corresponded to an increase in miles of weight-bearing exercise performed throughout training. The incidence of stress fracture and reaction was 3.9% and 14.8%, respectively, for women and 1.7% and 3.4%, respectively, for men. Conclusions: Significant bone resorption took place at the end of Marine recruit training due to accumulation of weight-bearing exercise throughout training and the increase in marching toward the end.

This study evaluated the arm, trunk, and leg for fat mass, lean soft tissue mass, and bone mineral content (BMC) assessed via dual-energy X-ray absorptiometry in a group of age-matched (∼29 yr) men ( n = 57) and women ( n = 63) and determined their relationship to insulin-like growth factor I (IGF-I) and leptin. After analysis of covariance adjustment to control for differences in body mass between genders, the differences that persisted ( P ≤ 0.05) were for lean soft tissue mass of the arm (men: 7.1 kg vs. women: 6.4 kg) and fat mass of the leg (men: 5.3 kg vs. women: 6.8 kg). Men and women had similar ( P ≥ 0.05) values for fat mass of the arms and trunk and lean soft tissue mass of the legs and trunk. Serum IGF-I and insulin-like growth factor binding protein-3 correlated ( P≤ 0.05) with all measures of BMC ( r values ranged from 0.31 to 0.39) and some measures of lean soft tissue mass for women ( r = 0.30) but not men. Leptin correlated ( P≤ 0.05) similarly for measures of fat mass for both genders ( r values ranging from 0.74 to 0.85) and for lean soft tissue mass of the trunk ( r = 0.40) and total body ( r = 0.32) for men and for the arms in women ( r = 0.56). These data demonstrate that 1) the main phenotypic gender differences in body composition are that men have more of their muscle mass in their arms and women have more of their fat mass in their legs and 2) gender differences exist in the relationship between somatotrophic hormones and lean soft tissue mass.

The Affordable Care Act directed Medicare to update its home health prospective payment system to reflect more recent data on costs and use of services-an exercise known as rebasing. As a result, the Centers for Medicare and Medicaid Services will reduce home health payments 3.5 percent per year in the period 2014-17. To determine the impact that these reductions could have on beneficiaries using home health care, we examined the Medicare reimbursement margins and the use of services in a national sample of 96,621 episodes of care provided by twenty-six not-for-profit home health agencies in 2011. We found that patients with clinically complex conditions and social vulnerability factors, such as living alone, had substantially higher service delivery costs than other home health patients. Thus, the socially vulnerable patients with complex conditions represent less profit-lower-to-negative Medicare margins-for home health agencies. This financial disincentive could reduce such patients' access to care as Medicare payments decline. Policy makers should consider the unique characteristics of these patients and ensure their continued access to Medicare's home health services when planning rebasing and future adjustments to the prospective payment system.

This paper presents a technique for applying the Rule Space model of cognitive diagnosis to assessment in a semantically-rich domain. Responses to 22 architecture test items, developed to assess a range of architectural knowledge, were analyzed using Rule Space. Verbal protocol analyses guided the construction of a model of examinee performance, consisting of processes for constructing an initial representation of an item (labeled understand), forming goals and performing actions based on those goals (solve), and determining whether goals have been attempted and satisfied (check). Item attributes, derived from these processes, formed the basis for diagnosis. Our technique extends Rule Space's applicability by defining attributes in terms of item characteristics and the causal relations between characteristics and the problem-solving model. Data were collected from 122 architects of various ability levels (students, architecture interns, and professional architects). Rule Space successfully classified approximately 65%, 90%, and 40% of examinees based, respectively, on attributes associated with the understand, solve, and check processes of the problem-solving model. The findings support the effectiveness of Rule Space in a complex domain and suggest directions for developing new architecture items by using attributes particularly effective at distinguishing among examinees of different ability levels.

A method for diagnostic assessment and proficiency scaling of test results is provided. The method uses as input a vector of item difficulty estimates for each of n items and a matrix of hypothesized skill classifications for each of said n items on each of skills. The method includes using a tree-based regression analysis based on the vector and matrix to model ways in which required skills interact with different item features to produce differences in item difficulty. This analysis identifies combinations of skills required to solve each item, and forms a plurality of clusters by grouping the items according to a predefined prediction rule based on skill classifications. A nonparametric smoothing technique is used to summarize student performance on the combinations of skills identified in the tree-based analysis. The smoothing technique results in cluster characteristic curves that provide a probability of responding correctly to items with specified skill requirements. The probability is expressed as a function of underlying test score.

We examine the empirical relationship between Internet subscriptions and foreign aid flows for 22 Development Assistance Committee (DAC) members for a 15 year time period employing the median voter model. We find that Internet use is positively related to the amount of foreign aid that donor nations give. This relationship is particularly robust for humanitarian aid. We hypothesize that Internet use is likely making aid giving more altruistic because Internet use increases the empathy people in donor nations feel for people in recipient nations. As Internet use increases in donor nations, the potential for emotional contagion to develop increases and the potential for the decisive voter to demand for an increase in humanitarian aid increases.

Using a panel of up to 116 countries from 1970-2010 we estimate the effects of foreign aid flows on a variety of measures of institutional quality. We find that aid flows are associated with the deterioration of both political and economic institutions. Regarding the latter, aid flows are associated with deterioration in a recipient’s legal system and property rights, as well as its openness to international trade. Controlling for both political and economic institutions in growth regressions, the latter is robustly, positively associated with growth. After controlling for institutional quality, aid flows are not otherwise significantly related to growth.

Charter schools are publicly supported schools to which parents can opt to send their children. The goal of the charter school movement is to offer parents a choice of schools within the public school sector. In general, charter schools are freed from many of the regulations under which traditional public schools operate – with the hope that the increased flexibility will result in superior student achievement.

The multiple-matrix item sampling designs that provide information about population characteristics most efficiently administer too few responses to students to estimate their proficiencies individually. Marginal estimation procedures, which estimate population characteristics directly from item responses, must be employed to realize the benefits of such a sampling design. Numerical approximations of the appropriate marginal estimation procedures for a broad variety of analyses can be obtained by constructing, from the results of a comprehensive extensive marginal solution, files of plausible values of student proficiencies. This article develops the concepts behind plausible values in a simplified setting, sketches their use in the National Assessment of Educational Progress (NAEP), and illustrates the approach with data from the Scholastic Aptitude Test (SA T).

A procedure for determining the effect of testlet nonequivalence on the operating characteristics of a testlet-based computerized mastery test (CMT) is introduced. The procedure involves estimating the CMT decision rule twice—once with testlets treated as equivalent and once with testlets treated as nonequivalent. In the equivalent testlet mode, the likelihood functions (LFS) estimated for specific number-correct (NC) scores are assumed to be con stant across testlets and a single set of cutscores is estimated for all testlets. In the nonequivalent testlet mode, the LFS estimated for specific NC scores are allowed to vary from one testlet to another and a different set of cutscores is estimated for each permutation of testlet presentation order. Small differences between the estimated operating characteristics of the equivalent testlet decision rule and the nonequivalent testlet decision rule indicate that the assumption of equivalent testlets was war ranted. This procedure is demonstrated with data from the Architect Registration Examination.

A theoretical framework for mastery testing based on item response theory and Bayesian deci sion theory is described. The idea of sequential testing is developed, with the goal of providing shorter tests for individuals who have clearly mastered (or clearly not mastered) a given subject and longer tests for those individuals for whom the mastery decision is not as clear-cut. In a simulat ed application of the approach to a professional certification examination, it is shown that average test lengths can be reduced by half without sacrifi cing classification accuracy. Index terms

The Survey of Young Adult Literacy conducted in 1985 by the National Assessment of Educational Progress included sixty-three items that elicited skills in acquiring and using information from written documents. These items were analyzed in two distinct ways: (1) with an item response theory (IRT) model, which characterized items' difficulties and respondents' proficiencies as revealed simply by tendencies toward correct response, and (2) a qualitative cognitive model, which characterized items in terms of the processing tasks they required. This paper demonstrates how a generalization of Fischer and Scheiblechner's Linear Logistic Test Model can be used to integrate information from the cognitive analysis into the IRT analysis. Subject Terms: Bayesian estimation; cognitive processing models; Item Response Theory; Linear Logistic Test Model; literacy assessment; National Assessment of Educational Progress

This study measured the response of deoxypyridinoline, a biomarker of bone resorption, during 11 weeks of Marine recruit training.Urine samples were obtained from 155 female and 58 male Marine recruits from the first morning void every 3 days during training. Training miles of weight-bearing exercise were recorded daily, and injury data were obtained from the medical clinic staff.Deoxypyridinoline was significantly (p0.001) increased at week 2 and weeks 9 through 11 for women and at weeks 10 and 11 for men. The increase in bone resorption corresponded to an increase in miles of weight-bearing exercise performed throughout training. The incidence of stress fracture and reaction was 3.9% and 14.8%, respectively, for women and 1.7% and 3.4%, respectively, for men.Significant bone resorption took place at the end of Marine recruit training due to accumulation of weight-bearing exercise throughout training and the increase in marching toward the end.

Since the late 1980s faculty and staff at the Medical College of Wisconsin (MCW) have actively sought to align their school's academic culture and promotional process with its mission of educational excellence and innovation. As one of the top 50 medical schools receiving NIH funds, MCW has well-established mechanisms to evaluate and recognize the scholarship of discovery. Understanding, evaluating, and recognizing the value of individuals engaged in the scholarship of teaching, however, required changes in individuals' beliefs and in the MCW's promotion processes and organizational infrastructure. Building on the successful introduction of the MCW's Educator's PortfolioCopyright, a tool for documenting educational scholarship, a multifaceted change strategy was implemented to influence underlying beliefs and values about clinician-educators. Retrospectively, this strategy was consistent with John Kotter's eight-step change model, which the authors apply as an organizing framework for this case report of educational evolution at the MCW. Through creating a guiding coalition, developing vision and strategy, generating short-term wins, and anchoring new approaches in the MCW's culture, the MCW has made substantive progress in recognizing and rewarding educational scholarship. Changing academic cultures to value education is itself an educational process, requiring persistence and the ability to teach others about educational scholarship and its associated criteria.

No Child Left Behind has highlighted the need for new types of assessments that not only provide high-quality evidence about what students know and can do, but also help to move learning forward. This paper describes a linked set of formative and summative reading assessments designed to address the tradeoffs inherent in these two goals. Targeted skills include the full range of competencies underlying proficient reading at the middle-school level, including both lower-order skills such as oral reading fluency and decoding, and higher-order skills such as the ability to integrate and synthesize information from multiple texts. Data collected in pilot administrations of two prototype test forms are presented. Analyses suggest that this new approach yields acceptable measurement properties while simultaneously addressing crucial learning outcomes. This paper was presented June 23, 2009 at the National Conference on Student Assessment, Los Angeles, CA.

The Common Core Standards call for students to be exposed to a much greater level of text complexity than has been the norm in schools for the past forty years. Textbook publishers, teachers, and assessment developers are being asked to refocus materials and methods to ensure that students are challenged to read texts at steadily increasing complexity levels as they progress through school so that all students remain on track to achieve college and career readiness by the end of 12th grade. Although automated text analysis tools have been proposed as one method for helping educators achieve this goal, research suggests that existing tools are subject to three limitations: inadequate construct coverage; overly narrow criterion variables; and inappropriate treatment of genre effects. Modeling approaches developed to address these limitations are described. Recommended approaches are incorporated into a new text analysis system called SourceRater. Validity analyses implemented on an independent sample of texts suggest that, compared to existing approaches, SourceRater's estimates of text complexity are more reflective of the complexity classifications given in the new Standards. Implications for the development of learning progressions designed to help educators organize curriculum, instruction and assessment in reading are discussed.

This paper presents the rationale and research base for a reading competency model designed to guide the development of cognitively based assessment of reading comprehension. The model was developed from a detailed review of the cognitive research on reading and learning and a review of state standards for language arts. A survey of the literature revealed three key areas of reading competency: prerequisite reading skill, model building skill, and applied comprehension skill. Prerequisite reading skill is the ability to read text accurately and fluently. Model building skill is the ability to construct meaning from either decoded text or spoken language. Applied comprehension skill is the ability to use and apply the information contained in text for some particular purpose. The framework is discussed in terms of 7 key principles that have implications for the design of a modern assessment of reading.

This paper explores alternative approaches for facilitating efficient, evidence-centered item development for a new type of verbal reasoning item developed for use on the GRE® General Test. Results obtained in two separate studies are reported. The first study documented the development and validation of a fully automated approach for locating the types of stimulus materials needed to support more efficient generation of the studied item type. The validation results confirmed that the proposed filtering technique can help item writers increase the percentage of acceptable stimulus paragraphs located per unit time interval from the current level of about 10% to nearly 30%. The second study documented the development and validation of a set of task models designed to help item writers generate new items that are optimally constructed to provide high-quality evidence about targeted skills. The proposed models were validated by considering the percentage of difficulty variance accounted for by the specified item classifications. That amount ranged from slightly more than 30% for items designed to test vocabulary skills to slightly more than 40% for items designed to test additional verbal reasoning skills, such as generating near and far inferences and understanding complex oppositional reasoning.

This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given document will be deemed acceptable for use in completing a specified passage-creation assignment by at least one test developer. The text features that form the basis of the estimated models are automatically extracted by natural language processing techniques. Model performance is evaluated by comparing the proportion of acceptable documents located with the screening capability turned on to the proportion of acceptable documents located with the screening capability turned off. The evaluation suggests that the estimated models have succeeded in capturing useful information about the characteristics of texts that affect test developers' ratings of source acceptability and that they can help test developers find a greater number of high-quality sources in less time.