The neurocognitive gains of diagnostic reasoning training using simulated interactive veterinary cases

The present longitudinal study ascertained training-associated transformations in the neural underpinnings of diagnostic reasoning, using a simulation game named “Equine Virtual Farm” (EVF). Twenty participants underwent structural, EVF/task-based and resting-state MRI and diffusion tensor imaging (DTI) before and after completing their training on diagnosing simulated veterinary cases. Comparing playing veterinarian versus seeing a colorful image across training sessions revealed the transition of brain activity from scientific creativity regions pre-training (left middle frontal and temporal gyrus) to insight problem-solving regions post-training (right cerebellum, middle cingulate and medial superior gyrus and left postcentral gyrus). Further, applying linear mixed-effects modelling on graph centrality metrics revealed the central roles of the creative semantic (inferior frontal, middle frontal and angular gyrus and parahippocampus) and reward systems (orbital gyrus, nucleus accumbens and putamen) in driving pre-training diagnostic reasoning; whereas, regions implicated in inductive reasoning (superior temporal and medial postcentral gyrus and parahippocampus) were the main post-training hubs. Lastly, resting-state and DTI analysis revealed post-training effects within the occipitotemporal semantic processing region. Altogether, these results suggest that simulation-based training transforms diagnostic reasoning in novices from regions implicated in creative semantic processing to regions implicated in improvised rule-based problem-solving

Developing NGSS-Aligned Assessments to Measure Crosscutting Concepts in Student Reasoning of Earth Structures and Systems

The past two decades of research on how students develop their science understandings as they make sense of phenomena that occur in the natural world has culminated in a movement to redefine science educational standards. The so-called Next Generation Science Standards (or NGSS) codify this new definition into a set of distinct performance expectations, which outline how students might reveal to what extent they have sufficient understanding of disciplinary core ideas (DCIs), science practices (SEPs), and crosscutting concepts (CCCs). The latter of these three dimensions is unique both in being the most recent to the field and in being the least supported by prior science education research. More crucially, as a policy document, the NGSS alone does not provide the supports teachers need to bring reforms to their classrooms, particularly not summative assessments. This dissertation addresses both of these gaps using a combination of quantitative and qualitative techniques. First, I analyze differential categorization of problems that require respondents to engage with their CCC understandings via confirmatory factor analysis inference. Second, I use a set of Rasch models to measure preliminary learning progressions for CCCs evident in student activity within a computer-assisted assessment experience. Third, I analyze student artifacts, think-aloud interviews, and post-task reflective interviews via activity theory to adapt the progression into a task model in which students explain and predict aspects of Earth systems. The culmination of these three endeavors not only sets forth a methodology for researching CCCs in a way that is more integrative to the other dimensions of the NGSS, but also provides a framework for developing assessments that are aligned to the goals of these new standards

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Adaptive Targeting: Engaging Farmers to Assess Perceptions and Improve Watershed Modeling, Optimization, and Adoption of Agricultural Conservation Practices

Targeting agricultural conservation practices to farmland that has the greatest impact on surface water quality has received wide support from scientists and watershed managers. The targeting approach has, however, been politically contentious as many believe farmers will oppose the approach on grounds such as privacy invasion and unfair distribution of government incentives. Targeting conservation practices using complex optimization models has become common in the scientific community, and yet targeted results are underutilized in practice because of difficulties such as knowledge transfer and absence of a political framework for their use. For targeting to be successful, it must be politically supported in concept and practically demonstrated in implementation. In this work I have conducted an interdisciplinary study and targeting experiment that brings together the human dimensions of targeting with the engineering tools of watershed modeling and spatial optimization to demonstrate an adaptive targeting approach. The approach is adaptive in its involvement of stakeholders, namely farmers and landowners, in the targeting process. Fourteen farmers were engaged through in-depth interviews about their farmland, conservation practices, and opinions on targeting of conservation. Interviews and the targeting experiment were conducted in 2012-2013 in two small west-central Indiana watersheds - the Little Pine watershed (56 km2) and Little Wea watershed (45 km2). There was general support for the targeting approach among farmers interviewed, despite wide variation in farmer views of conservation and government programs. Farmer views of differing conservation practices varied as well, supporting a flexible targeting approach where farmers are consulted prior to targeting conservation on their lands. The watershed modeling and spatial optimization approach tailored to farm boundaries was a suitable tool for targeting field scale practices at the watershed scale. Conservation practices represented in the Soil and Water Assessment Tool (SWAT) varied in effectiveness of reducing total nitrogen, total phosphorus, and sediment from reaching surface waters. Grassed waterways, filter strips, and strategically cited wildlife habitats had the greatest efficiency in lands with little existing conservation, and cover crops and wetlands were capable of intercepting nutrients and sediments other practices could not reach. The adaptive targeting experiment resulted in a stated intention to adopt 35% of all targeted recommendations across ten farms. Interviews clearly improved the targeting approach, provided an avenue for knowledge transfer, and built trust with farmers

An Exploration of The Application of Spatial Network Screening Methods On Iowa Rural Road Crashes

Safety on the roadway system is important due to its usage on mobility and accessibility, especially on rural roads in the state of Iowa. Single vehicle run off road crashes have been increasing in the United States and studies and research has increased due to the concern with those. For this effort, a spatial-temporal method of traffic safety network screening is utilized in order to evaluate the concerning type of crashes in particular locations. The study of single vehicle run off road crashes using the proposed method is important since distributions and clusters of crashes along roadways can be observed and further evaluations can be performed

Synthesizing Functional Reactive Programs

Functional Reactive Programming (FRP) is a paradigm that has simplified the construction of reactive programs. There are many libraries that implement incarnations of FRP, using abstractions such as Applicative, Monads, and Arrows. However, finding a good control flow, that correctly manages state and switches behaviors at the right times, still poses a major challenge to developers. An attractive alternative is specifying the behavior instead of programming it, as made possible by the recently developed logic: Temporal Stream Logic (TSL). However, it has not been explored so far how Control Flow Models (CFMs), as synthesized from TSL specifications, can be turned into executable code that is compatible with libraries building on FRP. We bridge this gap, by showing that CFMs are indeed a suitable formalism to be turned into Applicative, Monadic, and Arrowized FRP. We demonstrate the effectiveness of our translations on a real-world kitchen timer application, which we translate to a desktop application using the Arrowized FRP library Yampa, a web application using the Monadic threepenny-gui library, and to hardware using the Applicative hardware description language ClaSH.Comment: arXiv admin note: text overlap with arXiv:1712.0024

The Use of Infographics to Assess Context Processing

Among high-order cognitive functions is the use of context to enhance comprehension of language or visual scenes. Although use of context is known to be impaired in certain clinical populations (e.g., schizophrenia), no existing test adequately assesses this construct. To fill this gap, we developed and attempted to validate a test of context use that employed Infographics (information graphics), which requires the use of context to interpret visual displays. The primary hypothesis was that interpreting Infographics would be sensitive to context processing. We further hypothesized that different levels of cognitive processing (requiring basic perceptual, real-world application, or verbal reasoning), as well as different categories of Infographics (Data Display, Maps, Diagrams, or Timelines) would tap differential cognitive functions. Forty Infographics test items were developed based upon design principles of Infographics. Following development of items, the Infographics test, as well as a battery of neuropsychological tests, were administered to 161 participants. Overall, results revealed that our Infographics did target context. However, the test also places significant demands on verbal reasoning and similar cognitive functions apply to each level of cognitive processing. Finally, results indicated that similar cognitive functions applied to all categories of Infographics, with the exception of the three of the categories of Data Display, Maps, and Diagrams, which were associated with graphical literacy skills, whereas Timeline was not. In sum, we present data that a newly developed Infographics test is a valuable tool to assess context, and may be applied to evaluate individual differences among healthy individuals, as well as to evaluate impairment in patients with specific clinical diagnoses. However, test performance is not specific to context processing and the test is also sensitive to other high-order cognitive functions, including verbal reasoning