Background & Objective:
Over the past several decades, systematic reviews have become a major part of the biomedical research literature landscape. While systematic reviews were originally developed for medicine and its related fields, they are now published in other disciplines. Our initial goal was to broadly investigate and describe the non-health sciences subject areas and disciplines that are publishing systematic reviews. Specifically, our research questions were,“What disciplines outside of the health sciences are adopting systematic reviews as a research method?” and “What implications may this have for health sciences librarianship?” Based on our initial findings, we will propose avenues for future research.

Methods & Discussion:
We conducted a search in the Scopus database to serve as a representative sample of the research literature. We searched for the phrase “systematic review*” in the article title or abstract, and limited the results to review articles from journals. We filtered out articles published in health sciences disciplines using the Scopus subject categories, and examined the articles that remained. The resulting set of titles was screened by two independent reviewers in a stepwise fashion. First we read the titles, then the abstracts, then the full text of remaining articles to determine if each was a systematic review and addressed a topic outside of the health sciences. We reconciled any differences for citations on which there was not initial consensus between reviewers. Lastly, we examined each remaining article to categorize its subject area or discipline. Our initial search included a number of systematic reviews outside the health science disciplines, and will yield data that has implications for librarians in the health sciences and in disciplines outside the health sciences field.

Objective: to explore currently available Open Educational Resources related to Health Sciences programs to increase available options for free, high quality, online educational materials to support Health Sciences faculty, researchers, and students in online, hybrid, and in-person courses at Arizona State University.

Background/Methods: Following the successful Open Access movement, the Open Education movement is expanding free, online access to Open Educational Resources (OERs), beyond research published in scholarly journals. Similar to the Open Access movement, Open Educational resources are of high quality, available for free, online, with minimal or no licensing restrictions. They include, but are not limited to: syllabi and course modules, open textbooks, and massive open online courses (MOOCs). Arizona State University (ASU) has many fully online degree programs from undergraduate to graduate level, as well as supplemental and continuing education certificates. ASU also has many hybrid programs and in-person courses that include online components. Instructors are often searching for online videos or other high quality, online educational materials that they can incorporate in their courses. OERs may provide some useful options. ASU Libraries became involved in Open Education Week in March 2013. To expand on our involvement and increase resource options at ASU, the presenters decided to begin identifying useful OERs for health sciences. To do so, the presenters searched for and evaluated 2-3 sources for OERs each and noted the advantages and/or disadvantages of each, as well as any highly useful specific OERs.

Results: The presenters will discuss the advantages and/or disadvantages of evaluated sources for Open Educational Resources and any highly useful specific OERs identified. We will also provide a brief overview of open source tools related to citation management.

Conclusion: Come to this presentation to explore the Open Education movement: hear about one research university library system's start with Open Education Week, and get an overview of free, online options for high quality Open Educational Resources in the Health Sciences.

As health information professionals we are familiar with specialized resources such as PubMed and CINAHL but less familiar with general freely available tools such as Google, Google Scholar, and other open Google tools. We wondered:

1. What Google tools are Health Sciences Researchers and Healthcare Professionals using, and how are they using them?
2. How effective are Google and/or Google Scholar for literature searching?
3. What other research is needed in this area?

Methods:
We searched for: ‘Google’ across five health sciences and health sciences related databases (CINAHL, Cochrane, PsycInfo, PubMed, Web of Science) and in Google Scholar (*For Google Scholar we searched: health AND google). We reviewed the first 100 citations from each database and selected results that: 1. Mentioned use of a Google tool, or 2. Discussed the effectiveness of Google or Google Scholar in scholarly literature searching. Out of the second group, we selected and read the 10 most relevant articles discussing the effectiveness of Google and/or Google Scholar for literature searching. We tried out recommended best practices to search for topics we had previously searched only in subject specific databases.

Results:
Health Sciences Researchers and Healthcare Professionals use many Google tools for a variety of purposes. Each tool was used in different ways by authors writing in the Health Sciences (see pie charts and examples in poster). Regarding literature searching the poster includes Google Scholar content sources, Top Search Strategies for Google Scholar, and Considerations for using Google Scholar for literature searching.

Conclusions:
Health Science researchers use a variety of Google tools to gather and manipulate data, and to visualize and disseminate results. Health care professionals use Google tools to facilitate interventions and for interactive educational materials. For Literature searching our results encourage using Google Scholar to complement subject specific databases. Its unique content makes it a valuable resource for finding additional documents.

Patron Driven Acquisition (PDA) is a growing method of collection development in academic libraries that follows a Just-In-Time model versus the more traditional Just-In-Case model. Arizona State University (ASU) implemented our current PDA plan and profiles in 2009 with minimal changes occurring since this initial implementation date. Our PDA model of collection development involves purchasing print and e-books when users select them in the online catalog, rather than receiving items on an approval plan or by librarian selection. After an initial investigation concluded that several major health sciences publications had not been loaded into the catalog for potential patron selection, we began a more thorough examination of our PDA profile.

ASU serves over 6,500 students, faculty, and staff in Nursing and Allied Health fields in a range of programs requiring a robust collection. This poster details the process we used to determine whether the profiles created by previous librarians in 2009 have succeeded in uploading records for publications that appear on the 2014 nursing texts from Doody’s Core Titles into our catalog. Specifically, our poster will present on the number of Doody’s titles that were excluded from the PDA plan due to our profile settings and analyze why these titles were excluded. Our findings will allow us to order titles that are currently missing from our collection as well as tailor our PDA profiles to include key texts in nursing and allied health subjects in the future. We will also provide recommendations and considerations for other libraries considering or using a PDA model for purchasing texts in the health sciences.

The recent battle reported from Washington about proposed national testing program does not tell the most important political story about high stakes tests. Politically popular school accountability systems in many states already revolve around statistical results of testing with high-stakes environments. The future of high stakes tests thus does not depend on what happens on Capitol Hill. Rather, the existence of tests depends largely on the political culture of published test results. Most critics of high-stakes testing do not talk about that culture, however. They typically focus on the practice legacy of testing, the ways in which testing creates perverse incentives against good teaching.

More important may be the political legacy, or how testing defines legitimate discussion about school politics. The consequence of statistical accountability systems will be the narrowing of purpose for schools, impatience with reform, and the continuing erosion of political support for publicly funded schools. Dissent from the high-stakes accountability regime that has developed around standardized testing, including proposals for professionalism and performance assessment, commonly fails to consider these political legacies. Alternatives to standardized testing which do not also connect schooling with the public at large will not be politically viable.

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.