Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem

Is Adding the E Enough?: Investigating the Impact of K-12 Engineering Standards on the Implementation of STEM Integration.

The problems that we face in our ever-changing, increasingly global society are multidisciplinary, and many require the integration of multiple science, technology, engineering, and mathematics (STEM) concepts to solve them. National calls for improvement of STEM education in the United States are driving changes in policy, particularly in academic standards. Research on STEM integration in K-12 classrooms has not kept pace with the sweeping policy changes in STEM education. This study addresses the need for research to explore the translation of broad, national-level policy statements regarding STEM education and integration to state-level policies and implementation in K-12 classrooms. An interpretive multicase study design was employed to conduct an in-depth investigation of secondary STEM teachers\u27 implementation of STEM integration in their classrooms during a yearlong professional development program. The interpretive approach was used because it provides holistic descriptions and explanations for the particular phenomenon, in this case STEM integration. The results of this study demonstrate the possibilities of policies that use state standards documents as a mechanism to integrate engineering into science standards. Our cases suggest that STEM integration can be implemented most successfully when mathematics and science teachers work together both in a single classroom (co-teaching) and in multiple classrooms (content teaching—common theme)

Developing a conceptual framework for an evaluation system for the NIAID HIV/AIDS clinical trials networks

Globally, health research organizations are called upon to re-examine their policies and practices to more efficiently and effectively address current scientific and social needs, as well as increasing public demands for accountability

An evidence base to optimise methods for involving patient and public contributors in clinical trials: a mixed-methods study

BACKGROUND: In comparison with other study designs, randomised trials are regarded as particularly likely to benefit from patient and public involvement (PPI). Using mixed-methods research we investigated PPI from the perspectives of researchers and PPI contributors. METHODS: Randomised trials in receipt of funding from the Health Technology Assessment (HTA) programme between 2006 and 2010 were identified. Funding applications and board and referee comments were obtained and data relevant to PPI extracted. Chief investigators (CIs), PPI contributors and UK Clinical Research Collaboration Registered Clinical Trials Units (RCTUs) were surveyed. Interviews were conducted with researchers and PPI contributors. RESULTS: A total of 111 trials were included. Text relevant to PPI was identified in half of the trials for which the first-stage applications were available, but only one-quarter described PPI within their development. In the second stage of the application, the majority provided some text relevant to PPI, with over half having PPI in their development. Fewer than half of referees commented on PPI, and funding boards rarely provided comments in relation to PPI. Seventy-three per cent (81 of 111) of CIs responded to the survey and 98% (79 of 81) included PPI at some stage in their trial. CIs considered high impact from PPI contributors to occur more frequently in trial setup, with low or no impact being more common during trial conduct, analysis and dissemination. Only one-third of CIs provided PPI contributor contact details but all contributors contacted completed the survey. The majority of contributors felt engaged and valued by the research team. Interviews were conducted with researchers and/or PPI contributors for 28 trials identifying two main influences on perception of PPI impact: whether or not CIs expressed personal goals and plans for PPI; and the quality of their relationship with the PPI contributors. The importance of early engagement was identified, with opportunity for input thereafter limited. Three PPI roles were identified: oversight, managerial and responsive. Oversight roles, as required by funders, were associated with low impact in comparison with responsive or managerial roles. Most researchers could see some value in PPI training for researchers, although those that had received such training themselves expressed concerns about its purpose and evidence base. Training for PPI contributors was considered unnecessary, with conversational approaches preferred, although this did not appear to provide an opportunity for role negotiation. The RCTU survey response rate was 85% (39 of 46). The majority (37 of 39) reported PPI within trials co-ordinated by their unit. Trial characteristics were used by half to determine the approach to PPI. Two-thirds reported recent developments or changes in implementing plans for PPI (21 of 33). Support to PPI contributors was commonly offered through members of staff at the unit. CONCLUSIONS: PPI is occurring in the majority of trials funded by the HTA programme, but uncertainty remains about how it is assessed and valued. Early involvement, building a relationship between researchers and contributors, responsive or managerial roles, and having defined goals for PPI were associated with impact. Efficiency could be gained by utilising the RCTU network to identify and tackle challenges, and develop a risk-based approach utilising trial characteristics. Recommendations are made to trial funders and the research community. Given the difficulties for some informants in recalling PPI contributions, future research using a prospective approach would be valuable. Ethnographic research that combines observation and multi-informant interviews is likely to be informative in identifying impact. The research community needs to give further consideration to processes for selecting PPI contributors and models of implementing PPI

Identifying a Typology of High Schools Based on Their Orientation Toward STEM: A Latent Class Analysis of HSLS:09

The purpose of this study is to investigate the extent that there is a typology of high schools based on their orientation toward STEM, as well as the extent to which school-level demographic variables and student high school outcomes are associated with subgroup membership in the typology, by analyzing data from a large nationally representative sample of high schools (n=940) from the High School Longitudinal Study of 2009 (HSLS:09) using latent class analysis (LCA). We used a three-step LCA approach to identify significantly different subgroups of STEM-oriented high schools, what covariates predict subgroup membership, and how subgroup membership predicts observed distal outcomes. We find that there are four significantly different subgroups of STEM-oriented high schools based on their principal’s perceptions: Abundant (12.3%), Support (23.3%), Bounded (10.1%), and Comprehensive (54.3%). In addition, we find that these subgroups are associated with school demographics, such as the percent of students eligible for free and reduced-price lunch, school locale, and control (public or private). Subgroup membership is also associated with student outcomes, such as postsecondary program enrollment and intent to pursue a STEM degree. Keywords: STEM Education, High Schools, Multivariate Analysi

Creating an Instrument to Measure Student Response to Instructional Practices

BackgroundCalls for the reform of education in science, technology, engineering, and mathematics (STEM) have inspired many instructional innovations, some research based. Yet adoption of such instruction has been slow. Research has suggested that students’ response may significantly affect an instructor’s willingness to adopt different types of instruction.PurposeWe created the Student Response to Instructional Practices (StRIP) instrument to measure the effects of several variables on student response to instructional practices. We discuss the step‐by‐step process for creating this instrument.Design/MethodThe development process had six steps: item generation and construct development, validity testing, implementation, exploratory factor analysis, confirmatory factor analysis, and instrument modification and replication. We discuss pilot testing of the initial instrument, construct development, and validation using exploratory and confirmatory factor analyses.ResultsThis process produced 47 items measuring three parts of our framework. Types of instruction separated into four factors (interactive, constructive, active, and passive); strategies for using in‐class activities into two factors (explanation and facilitation); and student responses to instruction into five factors (value, positivity, participation, distraction, and evaluation).ConclusionsWe describe the design process and final results for our instrument, a useful tool for understanding the relationship between type of instruction and students’ response.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136692/1/jee20162_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136692/2/jee20162.pd

Environmental impact assessments of the Three Gorges Project in China: issues and interventions

The paper takes China's authoritative Environmental Impact Statement for the Yangzi (Yangtze) Three Gorges Project (TGP) in 1992 as a benchmark against which to evaluate emerging major environmental outcomes since the initial impoundment of the Three Gorges reservoir in 2003. The paper particularly examines five crucial environmental aspects and associated causal factors. The five domains include human resettlement and the carrying capacity of local environments (especially land), water quality, reservoir sedimentation and downstream riverbed erosion, soil erosion, and seismic activity and geological hazards. Lessons from the environmental impact assessments of the TGP are: (1) hydro project planning needs to take place at a broader scale, and a strategic environmental assessment at a broader scale is necessary in advance of individual environmental impact assessments; (2) national policy and planning adjustments need to react quickly to the impact changes of large projects; (3) long-term environmental monitoring systems and joint operations with other large projects in the upstream areas of a river basin should be established, and the cross-impacts of climate change on projects and possible impacts of projects on regional or local climate considered. © 2013 Elsevier B.V.Xibao Xu, Yan Tan, Guishan Yan