Faculty and Staff

This paper presents a Bayesian framework for evaluative classification. Current education policy debates center on arguments about whether and how to use student test score data in school and personnel evaluation. Proponents of such use argue that refusing to use data violates both the public’s need to hold schools accountable when they use taxpayer dollars and students’ right to educational opportunities. Opponents of formulaic use of test-score data argue that most standardized test data is susceptible to fatal technical flaws, is a partial picture of student achievement, and leads to behavior that corrupts the measures.

A Bayesian perspective on summative ordinal classification is a possible framework for combining quantitative outcome data for students with the qualitative types of evaluation that critics of high-stakes testing advocate. This paper describes the key characteristics of a Bayesian perspective on classification, describes a method to translate a naïve Bayesian classifier into a point-based system for evaluation, and draws conclusions from the comparison on the construction of algorithmic (including point-based) systems that could capture the political and practical benefits of a Bayesian approach. The most important practical conclusion is that point-based systems with fixed components and weights cannot capture the dynamic and political benefits of a reciprocal relationship between professional judgment and quantitative student outcome data.

This is a brief text intended for use in undergraduate school-and-society classes. Your class may also be titled “Social foundations of education.” “Social foundations of education” is an interdisciplinary field that includes both humanities and social-science perspectives on schooling. It thus includes study of the philosophy and history of education as well as sociological, economic, anthropological, and political perspectives on schooling.

The core of most social foundations classes lies in the relationship between formal schooling and broader society. This emphasis means that while some parts of psychology may be related to the core issues of social foundations classes—primarily social psychology—the questions that are asked within a social-foundations class are different from the questions raised in child development, educational psychology, and most teaching-methods classes. For example, after finishing the first chapter of this text, you should be able to answer the question, “Why does the federal government pay public schools to feed poor students at breakfast and lunch?” Though there is some psychology research tying nutrition to behavior and learning, the policy is based on much broader expectations of schools. In this case, “Children learn better if they are well-fed” both is based on research and also is an incomplete answer.

The current debate over graduate rate calculations and results has glossed over the relationship between student migration and the accuracy of various graduation rates proposed over the past five years. Three general grade-based graduation rates have been proposed recently, and each has a parallel version that includes an adjustment for migration, whether international, internal to the U.S., or between different school sectors. All of the adjustment factors have a similar form, allowing simulation of estimates from real data, assuming different unmeasured net migration rates. In addition, a new age-based graduation rate, based on mathematical demography, allows the simulation of estimates on a parallel basis using data from Virginia's public schools.

Both the direct analysis and simulation demonstrate that graduation rates can only be useful with accurate information about student migration. A discussion of Florida's experiences with longitudinal cohort graduation rates highlights some of the difficulties with the current status of the oldest state databases and the need for both technical confidence and definitional clarity. Meeting the No Child Left Behind mandates for school-level graduation rates requires confirmation of transfers and an audit of any state system for accuracy, and basing graduation rates on age would be a significant improvement over rates calculated using grade-based data.

The spread of academic testing for accountability purposes in multiple countries has obscured at least two historical purposes of academic testing: community ritual and management of the social structure. Testing for accountability is very different from the purpose of academic challenges one can identify in community “examinations” in 19th century North America, or exams’ controlling access to the civil service in Imperial China. Rather than testing for ritual or access to mobility, the modern uses of testing are much closer to the state-building project of a tax census, such as the Domesday Book of medieval Britain after the Norman Invasion, the social engineering projects described in James Scott's Seeing like a State (1998), or the “mapping the world” project that David Nye described in America as Second Creation (2004). This paper will explore both the instrumental and cultural differences among testing as ritual, testing as mobility control, and testing as state-building.

One way to view ‘equitable pedagogy’ is through an opportunity to learn (OTL) lens, meaning that regardless of race, class, or culture, a student has access to rigorous and meaningful content, as well as appropriate resources and instruction necessary to learn and demonstrate understanding of that content. Assessment holds a unique position in the classroom in that it can both uncover whether inequitable conditions exist (i.e., performance gaps, denied OTL) and provide an OTL by mediating communication between teacher and students regarding learning progress and what is important to learn. Nevertheless, individuals entering teacher education programs often hold deficit views toward marginalized students, such as Language Minorities (LMs), believe that assessment strictly serves to evaluate learning, and do not do consider how language and culture influence student thinking–views supplanting assessment’s role at supporting an equitable pedagogy for LMs. Through surveys, interviews, program artifacts, and classroom observation, I report on a case study of one pre-service physics teacher, Dean, to depict how his expertise at assessing science did evolve throughout his yearlong teacher education program in terms of (a) becoming more knowledgeable of the role of language and (b) developing a belief in incorporating ‘discourse’ while assessing science. Within the case study, I analyze one particular episode from Dean’s teaching practicum to highlight remaining challenges for pre-service teachers to integrate science and language in classroom assessment—namely, interpreting students’ use of language along with their understanding of core science ideas. The findings underscore the need for connecting language and equity issues to content-area assessment in teacher preparation.

Introduction: Abundance of immune cells has been shown to have prognostic and predictive significance in many tumor types. Beyond abundance, the spatial organization of immune cells in relation to cancer cells may also have significant functional and clinical implications. However there is a lack of systematic methods to quantify spatial associations between immune and cancer cells.

Methods: We applied ecological measures of species interactions to digital pathology images for investigating the spatial associations of immune and cancer cells in breast cancer. We used the Morisita-Horn similarity index, an ecological measure of community structure and predator–prey interactions, to quantify the extent to which cancer cells and immune cells colocalize in whole-tumor histology sections. We related this index to disease-specific survival of 486 women with breast cancer and validated our findings in a set of 516 patients from different hospitals.

Results: Colocalization of immune cells with cancer cells was significantly associated with a disease-specific survival benefit for all breast cancers combined. In HER2-positive subtypes, the prognostic value of immune-cancer cell colocalization was highly significant and exceeded those of known clinical variables. Furthermore, colocalization was a significant predictive factor for long-term outcome following chemotherapy and radiotherapy in HER2 and Luminal A subtypes, independent of and stronger than all known clinical variables.

Conclusions: Our study demonstrates how ecological methods applied to the tumor microenvironment using routine histology can provide reproducible, quantitative biomarkers for identifying high-risk breast cancer patients. We found that the clinical value of immune-cancer interaction patterns is highly subtype-specific but substantial and independent to known clinicopathologic variables that mostly focused on cancer itself. Our approach can be developed into computer-assisted prediction based on histology samples that are already routinely collected.

In a meta-analysis published by myself and co-authors, we report differences in the life history risk factors for estrogen receptor negative (ER−) and estrogen receptor positive (ER+) breast cancers. Our meta-analysis did not find the association of ER− breast cancer risk with fast life history characteristics that Hidaka and Boddy suggest in their response to our article. There are a number of possible explanations for the differences between their conclusions and the conclusions we drew from our meta-analysis, including limitations of our meta-analysis and methodological challenges in measuring and categorizing estrogen receptor status. These challenges, along with the association of ER+ breast cancer with slow life history characteristics, may make it challenging to find a clear signal of ER− breast cancer with fast life history characteristics, even if that relationship does exist. The contradictory results regarding breast cancer risk and life history characteristics illustrate a more general challenge in evolutionary medicine: often different sub-theories in evolutionary biology make contradictory predictions about disease risk. In this case, life history models predict that breast cancer risk should increase with faster life history characteristics, while the evolutionary mismatch hypothesis predicts that breast cancer risk should increase with delayed reproduction. Whether life history tradeoffs contribute to ER− breast cancer is still an open question, but current models and several lines of evidence suggest that it is a possibility.

It has long been accepted that modern reproductive patterns are likely contributors to breast cancer susceptibility because of their influence on hormones such as estrogen and the importance of these hormones in breast cancer. We conducted a meta-analysis to assess whether this ‘evolutionary mismatch hypothesis’ can explain susceptibility to both estrogen receptor positive (ER-positive) and estrogen receptor negative (ER-negative) cancer. Our meta-analysis includes a total of 33 studies and examines parity, age of first birth and age of menarche broken down by estrogen receptor status. We found that modern reproductive patterns are more closely linked to ER-positive than ER-negative breast cancer. Thus, the evolutionary mismatch hypothesis for breast cancer can account for ER-positive breast cancer susceptibility but not ER-negative breast cancer.