Active learning generally increases student achievement, but not all instructors experience the same magnitude of gains. This variation in student achievement is likely due to differences in how active learning is implemented in the classroom as well as differences in total classroom time devoted to active learning. Although multiple tools exist for characterizing active learning in the classroom, none have been used to explain variation in student achievement. We are developing a new type of Classroom Observation Tool (COT) that characterizes how closely an instructor’s use of active learning matches the best practices suggested in education literature and can be correlated with observed variation in student exam achievement. Currently, we are using the COT to analyze 3 randomly selected classroom sessions from 27 different introductory biology instructors using archived footage. We will create a linear model that combines instructor’s COT scores with controls for variability in student ability and exam challenge between instructors to predict student exam performance. This model will allow us to identify which elements measured by the COT are most strongly correlated with variation in student performance. With this baseline data, we will be able to recommend the use of the COT to help Faculty assess the effectiveness of their instruction, thereby enhancing teaching and student learning not only within Biology education at UW, but also across all postsecondary education.

Methylotrophic bacteria have long been recognized for their metabolism of reduced single carbon (C₁) compounds. Their potential for biotechnology and the occurrence of C₁ metabolism in all organisms signify their importance on an industrial and fundamental scale. Currently, mechanisms used by methylotrophs to regulate and reset their metabolic network in response to perturbations are not well understood. Previous studies suggest abrupt shifts in nucleotide levels drastically affect growth. This project will examine how nucleotide ratios correlate with carbon flux in Methylobacterium extorquens AM1. Once C₁ compounds undergo serial oxidation to formate, carbon flux is partitioned for further oxidation or assimilation. Two reactions involved in C₁ oxidation are known to generate reducing power: (1) the dehydrogenation of methylene-dH₄MPT into methenyl-dH₄MPT catalyzed by MtdA or MtdB and (2) the oxidation of formate into CO₂ catalyzed by Fdh1 or Fdh2. Genetic studies demonstrated differential phenotypes in which mtdB fdh1 grew similarly to wild type while mtdB fdh2 grew worse relative to the mtdB mutant strain. One possible explanation is a global decrease in NADH production offsets the delicate balance of intracellular nucleotides required for an already reducing power-limited mode of growth. To explore this hypothesis, I will conduct experiments to: (1) quantify the levels of NADP⁺, NADPH, NAD⁺, and NADH in WT, mtdB, mtdB fdh1, and mtdB fdh2 and (2) manipulate nucleotide ratios with overexpression and deletion of the pntAB and udhA genes. These genes encode for membrane bound (PntAB) and soluble (UdhA) transhydrogenases capable of interconverting between NADPH and NADH. Since mechanisms exist in other bacteria to alter nucleotides pools to meet metabolic demands, a similar mechanism can be predicted to operate in M. extorquens AM1. Success in this project will lead to better understanding of how cells balance reducing power and energy for oxidation and growth, ultimately leading to improved biotechnological utilization.

We estimate a Gaussian graphical model corresponding to a covariance matrix using machine learning techniques. A motivating application is to identify genes associated with cancer in the human genome. Suppose we have genetic data from two people, one of whom is healthy, while the other has cancer. Our goal is to identify gene expressions that differ between datasets and contribute to cancer. We model each dataset as a Gaussian graphical model, which is a network of edges and nodes. Each node represents a random variable, or gene. Each edge represents the dependence between the two variables it connects. An edge with zero value indicates the two variables are independent when conditioned on the rest of the variables. Such networks are analogously represented as inverse covariance matrices. Our goal is to use empirical genetic information from cancer patients to recover the true inverse covariance matrices. We suppose that the inverse covariance matrices have a certain structure and we set up a problem to encourage that structure. Structure refers to the relative magnitudes of matrix elements. A structure of interest is a hub node, which is highly connected to other nodes. These nodes play a regulatory role in gene expression and may be related to cancer. Our goal is to identify hub nodes in the difference between two inverse covariance matrices. We formulate this question as a convex optimization problem. We encourage the solution to have a certain structure by adding regularizer terms to the objective function. We recover the overall structure of the inverse matrices, while simultaneously encouraging the solution to have specific structures of interest. An alternating directions method of multipliers (ADMM) algorithm is used to solve the optimization problem. We run the algorithm on synthetic genetic data, and on real gene expression data to identify cancer related genes.

Schizophrenia is a debilitating neuropsychiatric disorder with a worldwide prevalence of about 1%. Although the heritability of schizophrenia is high, there are many sporadic cases; that is, affected individuals with no family history of mental illness. We are sequencing persons with schizophrenia in the absence of family history of mental illness (probands), their unaffected parents, and whenever possible, an unaffected older sibling, in order to identify de novo mutations that may be responsible for the disorder. Our hypothesis is that de novo events will be observed in many different genes, and that the functions of the impacted genes will differ between probands and their unaffected siblings. From exome sequence, we filter variants to include only those predicted to be both de novo and damaging to the protein product. Next, we validate all candidate variants passing these filters by Sanger sequencing, using diagnostic PCR primers to amplify genomic DNA of probands, siblings, and parents. Results to date suggest that approximately 50% of probands and siblings carry at least one damaging de novo mutation. The analysis of pathways in which the genes converge is in progress. Next, we will target these candidate genes and determine their complete variant profiles in 5000 cases and 5000 controls. These results can help us identify critical pathways that are affected in schizophrenia.

Throughout their lives, children in the United States public education system are bombarded with messages of equality and the promise of the American dream (i.e., no matter who you are, you can succeed through merit and hard work). Yet, the field of science is still dominated by White men in both number and power. Young girls of color are thus faced with two conflicting narratives: "You can achieve anything you set your mind to," and, "There are few people like you in the field of science." My research asks how middle school girls of color process this dichotomy. Based on my past experience as a female minority pursuing a career in science, it is my hypothesis that these girls will consciously believe and express the first narrative, while internalizing and acting according to the latter. One of my research methods is the Draw-a-Scientist Test, a tool used to gauge a student's perceptions of scientists by asking her to make a drawing of one. I expect the girls to express their belief that anyone can become a scientist, while drawing stereotypical images of scientists (i.e., people unlike themselves). I will also analyze and look for themes in observations, recorded interviews, and interactions of girls participating in an after-school program called Chemical Oceanography After School Time (COAST). I believe that as the girls gain firsthand experience with science in the COAST program, they will begin to interact in ways that show growing confidence in their own potential to become scientists. These findings indicate a need for more science intervention programs, like COAST, for girls of color. My research aims to open up dialogue about how the prevailing ideologies and realities of race and gender in the United States impact the potential in science for girls of color.

Alcohol use consistently correlates with negative physical and psychological consequences like dependence, memory loss, impaired judgment, etc. Studies also link the use of sleep medications with similar negative consequences. Yet, no study examines the interaction of sleep medication and alcohol use onto these negative consequences. Therefore the present study investigated the relationship between peak blood alcohol content (BAC) in the past 6 months, negative consequences of alcohol use in the last 12 months as measured by the Rutgers Alcohol Problem Index, and lifetime, 3- and 12-month non-prescribed sleep medication use in Washington state and Swedish high school seniors participating in a larger study (N = 3,352, 56.6% Female). Regression analyses revealed a significant main effect of BAC and lifetime use of sleep medication onto negative consequences (β = 18.69, F (3, 2875) = 115.86, p < .05) such that individuals with a higher BAC and who had a lifetime incidence of sleep medication usage experienced significantly greater negative consequences than those who only drank or used sleep medications. There was no significant moderating effect of frequency of sleep medication use in the last 3 or 12 months onto BAC and negative consequences (p >.05). While these results suggest that use of sleep medication and alcohol interact to contribute to increased risk for negative consequences, there are limitations. Lifetime use of sleep medication may reflect a tendency to act impulsively or self-medicate (e.g. for sleep/depression/anxiety), not a direct effect of the medication per se. Additionally, analyses did not control for other drug usage or mood disturbances, and all sleep medication drugs were grouped under one survey item. Given our observations, additional research testing combined effect of sleep mediation and alcohol use as related to negative consequences is warranted.

Impulsivity is often found to be related to alcohol use (Pearson and Henson, 2012; Simons, 2003). Additionally, a correlate of alcohol expectancies is increased alcohol use (Hull and Bond, 1986). However, no research to date has looked directly into the association of impulsivity, alcohol expectancies, and alcohol use. Therefore, the present study looks into impulsivity, alcohol use, and alcohol expectancies in high school seniors (N = 3,352, 56.6% Female) from Washington and Sweden. Participants completed a baseline online survey as part of a larger trial that assessed peak blood alcohol content (BAC) in the past 12 months, impulsivity as measured by the sensation seeking scale (Zuckerman, 1964), and alcohol expectancies as measured by the brief Comprehensive Effects of Alcohol questionnaire which consists of positive (sociability, tension-reduction, liquid courage, and sexuality) and negative (cognitive/behavioral impairment, risk/aggression, and self-perception) classifications (CEOA; Fromme, 1993). Regression analyses revealed a significant main effect of impulsivity, cognitive/behavioral impairment, sociability, risk/aggression, and self-perception onto peak BAC (p < .05). However, significant interactions were only found for impulsivity onto risk/aggression and self-perception. A significant moderating effect of risk/aggression onto the relationship between impulsivity and peak BAC (β = .002, F (3, 2913) = 114.71, p < .05) was found such that those with lower impulsivity and lower risk aggression scores (alcohol seen positively) have higher peak BAC. A significant moderating effect of self-perception onto the relationship between impulsivity and peak BAC was also found (β = .001, F (3, 2908) = 132.04, p < .05) suggesting that individuals with lower self-perception scores (alcohol seen positively) and higher impulsivity have higher peak BAC. These results suggest that individuals who are both highly impulsive and have higher positive expectancies for alcohol drink more. Future research should continue to investigate the relationship between alcohol expectancies and impulsivity in vivo.

Over the past two decades, inclusion has become a major topic in the field of education. Inclusion means that children with special needs attend school with thypically developing peers. Public schools have undergone significant reconstruction in order to fulfill the vision of inclusive classrooms. Much is known and various research studies exist about the benefit of inclusion for children with disabilities, as well as for typically developing children. Yet, what is the current status of inclusion? My research examines inclusion on a bigger scale and seeks to answer questions such as “what does a successful inclusion program look like?”, “what teaching strategies are important for inclusive classrooms?’, and “how do schools promote inclusive practices?”. As a mixed-methods study, I am conducting a review of research and other artifacts as well as performing semi-structured interviews of teachers who practice inclusive education. The artifacts I review, such as a research study examining principals' perspectives on inclusive education, provide different definitions and applications of inclusion. Other research studies look to see if inclusive classrooms are reaching the goals set by the concept of inclusion, such as membership, relationships, and development. Finally, I interview preschool and grade-level teachers at an elementary school in the Seattle Public School Distict. The teachers' experience varies from teaching inclusive classrooms, resource rooms, and general education classrooms; but all have taught in inclusive settings. My aim is to generate a perspective of the current state of inclusion and use teacher voice to capture experiences.

Burma is now undergoing an incredible transition toward peace, stability and democratic governance – a transition that we found requires a fundamental re-thinking of U.S. policy relations. While we discovered Burma’s commitment to reform to be genuine, its challenges are numerous. Instability and underdevelopment continue to dominate the Burmese landscape, defined by a weak constitutional government, repressed civil society, unreformed military, ethnic violence and an underdeveloped economy. This past year marked President Obama as the first American president to visit Burma, extending a hand of friendship, committed to strengthening political and economic ties between the United States and Burma. As well as a real commitment by the United States to reduce economic sanctions, aid in the democratization process, and lift the Burmese economy out of poverty -  elements we proved to be essential in ensuring a successful transition in Burma. Our task force recommends greater engagement, aid, and targeted policy consultation to help the country emerge from decades of military-junta rule and rejoin the international community. Ultimately, Burma offers a new roadmap in the United States in re-thinking the reform process of developing countries, one that now requires trading the tools of isolation and international pressure for those of integration and international cooperation. The world is now watching Burma as it prepares to chair the ASEAN council in 2014 and hold democratic elections in 2015. No one knows how long this moment for reform will last, but the time for action is now.