{"id":205,"date":"2016-08-08T10:04:58","date_gmt":"2016-08-08T15:04:58","guid":{"rendered":"https:\/\/wp.stolaf.edu\/cir\/?page_id=205"},"modified":"2016-10-03T11:14:44","modified_gmt":"2016-10-03T16:14:44","slug":"projects-for-2016-17","status":"publish","type":"page","link":"https:\/\/wp.stolaf.edu\/cir\/projects-for-2016-17\/","title":{"rendered":"Projects for 2016-17"},"content":{"rendered":"
\"_dsc0083\"<\/a>
Professor Sharon Lane-Getaz, Kate Nole, Taylor Okonek, Alex Knutson and not pictured is Professor Louis Epstein<\/figcaption><\/figure>\n

Domain Expert: <\/strong>Louis Epstein\u00a0<\/strong>
\nTitle: The Music History Game:\u00a0Assessing Learning through Play<\/p>\n

Description: How can we harness the pedagogical power of gaming to help students learn music history? In the last 30 years, \u00a0\u201cgamification\u201d has changed how students learn\u00a0content and acquire\u00a0skills in k-12 education, but it remains relatively untested in higher education settings, especially in music. Our project explores the potential for gaming to enhance how music students acquire historical knowledge and develop critical listening skills. In the summer of 2015,\u00a0CS and Music majors\u00a0designed a computer-based, educational game that students in Music 241 played in the fall of 2015. The game consists of hundreds of flashcards featuring multiple-choice questions, each question relying on a musical excerpt that students listen to before answering. Questions are organized into “missions” and “levels,” and students are graded based on how many levels they complete.\u00a0Collectively, students attempted 38,000 questions (answering 33,000 correctly after multiple tries), generating a glut of data that we will use\u00a0to answer questions about the reliability of teacher-assigned\u00a0“difficulty” levels\u00a0for\u00a0tasks within the game; the impact of repetition and interleaving of tasks across levels;\u00a0and how best to measure the effects of\u00a0differences in time on task between students. Students will continue playing the game during the 2016-2017 academic year, generating new data\u00a0for the next phase of the project: measuring\u00a0the effects of metacognitive exercises on retention and transfer.<\/p>\n

\"_dsc0094\"<\/a>
Sarah Pellici, Holly Jansen, Professor Ashley Hodgson, Professor Bob Eisinger, Jinhee Cha<\/figcaption><\/figure>\n

Domain Expert:<\/strong> Ashley Hodgson
\n<\/strong>Title: The Effect of Hospitalist Collaboration on Medical Mistakes<\/p>\n

Description: Hospital patients often get shifted between many specialist doctors within the same hospital stay, often with a lack of organized coordination. Patients needing the most coordination across specialist doctors experience more medical mistakes. This is likely due to the miscommunications that happen as a patient\u2019s care team becomes larger. Some hospitals employ hospitalists, who are doctors that specialize in managing a patient\u2019s care during their hospital stay. Our research will explore questions related to hospitalist\u2019s effect on medical mistakes for both their own patients and also the patients of doctors who spend time collaborating with hospitalists. The questions are: Do patients experience fewer medical mistakes when their doctors work with a hospitalist to coordinate care? Do doctors with a longer tenure working in collaboration with a hospitalist have patients with fewer medical mistakes? This project utilizes a large patient-level hospital data set which includes Florida hospital patients from 2005 to 2012. Included in the data set is information on each patient\u2019s doctor(s). Our main dependent variables will be Patient Safety Indicators (medical mistakes), as defined by the Agency for Healthcare Quality and Research. The independent variables we will work with most will be the presence or absence of a hospitalist (at both the patient-level and hospital-level), the duration of time the patient\u2019s doctor has worked with hospitalists, the patient\u2019s comorbidities and the patient\u2019s expected need for coordinated care. We will also explore potential instrumental variables, such as admission during a weekend.\u00a0<\/strong><\/p>\n

\"_dsc0061\"<\/a>
Jeremy Storvick, Erin Cochrane, Mark Legler, Anna Wall, Allison Trezona, and Professor Julie Legler<\/figcaption><\/figure>\n

Domain Expert: Mark Legler<\/strong>
\nTitle: Understanding Homelessness in Hennepin County<\/p>\n

Description: There are approximately 6000 single adults who use county-contracted emergency shelters in Hennepin County in any given year. Use of shelter varies greatly \u2013 half are in shelter less than a week, another half are there more than a month, some as long as a year or more. It is imperative that we understand who uses emergency shelter and what strategies may help them leave shelter sooner. Using a over a decade\u2019s worth of data, we would like to understand the characteristics of the various shelter populations so we can design solutions that might best fit their needs. Are they disabled? Are they able-bodied but with criminal histories that make finding a job difficult? Do they go in and out of GRH facilities or in and out of the criminal justice system? The data file has 20,000 records and covers 11 years of shelter history. It also contains demographic information, use of county benefits and case management services, and criminal justice involvement. Qualitative interviews may also be conducted with single adults in shelter to understand their intermittent shelter use, where they go on other days, and what they think would help them leave shelter.<\/p>\n

\"_dsc0075\"<\/a>
Professor Katie Ziegler-Graham, Briana Wenande, Professor Shelly Dickinson, Sam Longenbach, Annika Fredrickson<\/figcaption><\/figure>\n

Domain Expert: Shelly Dickinson, Psychology & Neuroscience<\/strong>
\nTitle: Alcohol Place Conditioning Studies in Mice<\/p>\n

Description:\u00a0<\/strong>Most theories of drug abuse and addiction are predicated in part on the assumption that most humans use, abuse, and subsequently become addicted to alcohol and other drugs because of the reinforcing and rewarding effects these substances produce (e.g., euphoria, relief from negative feelings). My primary research interest is the understanding of the neuropharmacological mechanisms underlying the effects of drugs of abuse, in other words, what\u2019s happening in the brain while these drugs are on board. I\u2019m especially interested in whether adolescents are affected differently by alcohol than adults, and use adolescent mice in the lab to look at these questions.<\/p>\n

The processes of conditioning (association of environmental cues and drug effects) are thought to be extremely important in craving and relapse in humans in that environmental cues can come to guide and even control behaviors such as drug-seeking. We utilize a range of conditioning procedures in the lab, including place conditioning and taste conditioning. We are also developing a sign-tracking procedure to look specifically at conditioned approach behaviors.\u00a0<\/strong><\/p>\n

\"_dsc0048\"<\/a>
Alex Rosati, Isaac Leonhardi, Ella Balke, Professor Chris Chapp and not pictured is Professor Sharon Lane-Getaz<\/figcaption><\/figure>\n

Domain Expert: Chris Chapp, Political Science<\/strong>
\nTitle: Communities that vote: Can legal reforms and election administration policies influence turnout in low-income communities?<\/p>\n

Description: The question of why citizens do (or do not) vote attracts steady attention from political scientists. In recent years, researchers have made considerable progress in understanding why some people cast votes and others do not, identifying numerous institutional mechanisms that promote and\/or inhibit participation (for example, same-day registration likely promotes high participation, while voter identification laws likely discourage electoral participation). Despite these advances, we do not adequately understand the persistent gap in voter turnout between wealthy and poor communities.\u00a0 In 2014, for example, 24.5% those making less than $10,000\/year voted.\u00a0 Among those making over $150,000, the turnout was 56.6%.\u00a0 Recent scholarship suggests that part of the reason for this continued turnout gap is that reforms in election administration are not being equally felt by across the income spectrum.\u00a0 This study will empirically investigate this claim. This study builds on previous CIR studies, examining the relationship between county-level institutional mechanisms and turnout, with an emphasis on how these mechanisms interact with county socioeconomic status.\u00a0 We will draw on two primary data sources.\u00a0 First, we will examine a survey I administered in the summer of 2016 to county election officials. Second, where available,\u00a0we will examine state elections returns data following the 2016 presidential election.\u00a0 This project will allow students to develop several statistical and inferential skills, including working with nested (multilevel) data structures, working with missing data, data reduction techniques, and data visualization.<\/p>\n

\"_dsc0070\"<\/a>
Professor Katie Ziegler-Graham, Katie Bews, Erik Berthelsen, Kate Henry and Professor Mary Walczak<\/figcaption><\/figure>\n

\u00a0<\/strong>Domain Expert: Mary Walczak<\/strong>
\nTitle: STEM persistence, trajectories, and open questions at St Olaf College<\/p>\n

Description:\u00a0St. Olaf students who begin college in science courses take a wide variety of paths through college. Some stay in science, some switch between sciences, and others choose to major in something other than science. Previous work used transcript and demographic data for students entering a St Olaf between 2002-2013 to answer questions about attrition and retention, trajectories, experiences, and programs relevant to Science, Technology, Engineering, and Mathematics (STEM). We categorized a student\u2019s intention to major in STEM at three points. First, the courses in which they enrolled during their first semester was used to categorize initial intent. Using a set of courses and\/or total number of STEM courses after 4 semesters we categorized students as STEM\/non-STEM at the end of the sophomore year. Major at graduation was used to identify STEM\/non-STEM students at a third and final point. We then quantified the number of students in each of the 8 different paths to graduation following our categorization exploring general trends in retention\/persistence. We were specifically interested in those students whose trajectories categorized them as early-switchers, late-switcher, or double-switchers. Next we investigated any potential gender effect or \u201cnew building effect\u201d and compared participation in an integrated introductory chemistry and biology course sequence to traditional discipline-specific sequences. We plan to build on this research, adding additional cohort years to the data.<\/p>\n

\"_dsc0064\"<\/a>
Professor Rodrigo Sanchez Gonzalez, Sasha Dmytrenko, Zach Norberg, Suzie Hoops, Michael Pearce, and Professor Matthew Richey<\/figcaption><\/figure>\n

Domain Expert:<\/strong> Rodrigo Sanchez Gonzalez
\n<\/strong>Title: Development of a Method for the Analysis of Molecular Tagging Velocimetry Images Based on Grid Parameterization<\/p>\n

Description: Numerous flowfields related to combustion and high-speed flight are characterized by non-equilibrium effects, and the acquisition of fundamental information to describe and model fluid behavior is required to drive technological advances in these fields. A detailed description of turbulence requires systematic integration between theoretical modeling and experimentation that directly relates model parameters to experimental observables. Molecular Tagging Velocimetry (MTV) methods are an alternative to Particle Image Velocimetry (PTV) for high-speed turbulent flowfield characterization. MTV methods are particularly useful when large errors in velocity determination that result from the use of particles make PTV ill suited. However, despite the potential of MTV methods for the study of high-speed flows, their application have been limited by a number of factors that include the lack of ready-to-use data analysis codes, which are largely written in-house. A method to analyze of MTV image pairs to estimate quantities such as vorticity as well as pressure and density fluctuations, in addition to space-resolved velocity, will be explored. This method will involve proper image transformations to map an entire MTV grid distorted by the flow velocity onto the first perfect grid.<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

Domain Expert: Louis Epstein\u00a0 Title: The Music History Game:\u00a0Assessing Learning through Play Description: How can we harness the pedagogical power of gaming to help students learn music history? In the […]<\/p>\n","protected":false},"author":343,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-205","page","type-page","status-publish","hentry"],"acf":[],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/pages\/205","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/users\/343"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/comments?post=205"}],"version-history":[{"count":21,"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/pages\/205\/revisions"}],"predecessor-version":[{"id":249,"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/pages\/205\/revisions\/249"}],"wp:attachment":[{"href":"https:\/\/wp.stolaf.edu\/cir\/wp-json\/wp\/v2\/media?parent=205"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}