Batch Informed Trees (BIT*)

Path planning through complex obstacle spaces is a fundamental requirement of many mobile robot applications. Recently a rapid convergence path planning algorithm, Batch Informed Trees (BIT*), was introduced. This work serves as a concise write-up and explanation of BIT*. This work includes a description of BIT* and how BIT* operates, a graphical demonstration of BIT*, and simulation results where BIT* is compared to Optimal Rapidly-exploring Random Trees (RRT*).Comment: 10 pages, 7 figure

A Person-Centered, Asset-Based Community Development Framework for Youth with Special Health Care Needs/Disabilities in Transition to Adulthood

In the United States, 12.8 percent of children under 18 have special health care needs. Ninety percent of youth in America with special health care needs and/or disabilities can now be expected to reach adulthood. Youth with special health care needs and/or disabilities are less likely to experience successful transition to adulthood in comparison to youth without special health care needs. This article presents a person-centered, asset-based community development approach that assisted youth in achieving transition and inclusion-oriented outcomes. Examples are drawn from a Healthy & Ready to Work demonstration project in Wisconsin. At the center of our approach to transition were community connectors -- adults who knew the personal interests and assets of youth and who found opportunities in the community that matched individual youth interests. Implications for youth development professionals as successful community connectors are described

Domain-based perceptions of risk:a case study of lay and technical community attitudes towards managed aquifer recharge

Despite growing water scarcity, communities in many parts of the developed world often reject technically and economically sound options for water augmentation. This paper reports findings from a study investigating risk perceptions associated with a proposed Managed Aquifer Recharge scheme in Australia. Q-Methodology was used to compare decision-making frameworks of lay community and „technical expert‟ participants. Technical expert participants were also asked to approximate the decision-making framework of a „typical‟ community member. The emerging contrasts between lay community frameworks and those approximated by technical experts suggest that there are prevailing yet errant assumptions about lay community attitudes towards new technologies. The findings challenge the characterisation of the lay community and technical experts as being in entrenched opposition with one another

Bootstrapping Q Methodology to Improve the Understanding of Human Perspectives.

Q is a semi-qualitative methodology to identify typologies of perspectives. It is appropriate to address questions concerning diverse viewpoints, plurality of discourses, or participation processes across disciplines. Perspectives are interpreted based on rankings of a set of statements. These rankings are analysed using multivariate data reduction techniques in order to find similarities between respondents. Discussing the analytical process and looking for progress in Q methodology is becoming increasingly relevant. While its use is growing in social, health and environmental studies, the analytical process has received little attention in the last decades and it has not benefited from recent statistical and computational advances. Specifically, the standard procedure provides overall and arguably simplistic variability measures for perspectives and none of these measures are associated to individual statements, on which the interpretation is based. This paper presents an innovative approach of bootstrapping Q to obtain additional and more detailed measures of variability, which helps researchers understand better their data and the perspectives therein. This approach provides measures of variability that are specific to each statement and perspective, and additional measures that indicate the degree of certainty with which each respondent relates to each perspective. This supplementary information may add or subtract strength to particular arguments used to describe the perspectives. We illustrate and show the usefulness of this approach with an empirical example. The paper provides full details for other researchers to implement the bootstrap in Q studies with any data collection design

First Steps in Critical Literacy

This thesis study examines the experience of a class of teacher education students learning about and working with critical literacy. The study specifically focuses on students' attitudes towards critical literacy and their ability to put critical literacy into practice through the creation of literacy thematic units examining social issues. Data was collected through administering a survey to the whole class, examining a random sample of developed thematic units for evidence of critical literacy practice, and analyzing a random sample of responses to reflective questions for common themes in the students' experience with critical literacy. Results indicated that, while the students felt positive towards critical literacy, they were unable to create lessons that contained critical literacy practice. The study suggests that the students were not prepared to critically examine the social issues under study, and were therefore not able to create authentically critical lessons. Preparing teacher education students to become critical educators may require more than introducing critical methodologies; it may require a rethinking of teacher education programs

Examining the Diagnostic Accuracy and Predictive Validity for FastBridge aReading and CBM-R on High Stakes State Tests

PDF.The current study examined the diagnostic accuracy of two common screening assessments in reading, FastBridge Adaptive Reading (aReading) and Curriculum Based Measurement of Oral Reading (CBM-R) when used to predict future performance on the Minnesota Comprehensive Assessment – Third Edition (MCA-III) in spring of 3rd grade. The sample consisted of 164 students enrolled in a school district in the Upper Midwest. Both screeners were moderately correlated with the MCA and had strong diagnostic accuracy; however, both screeners showed poorer sensitivity when vendor cut scores were applied. These results demonstrate the importance of considering local norms for the most accurate screening decisions. Future research could explore the diagnostic accuracy of both screeners combined, using other data to inform decision making, or exploring different cut-scores for defining “at-risk” students