An Exploratory Study of the Impact of a Meaningful, Mastery Project Based Learning Curriculum Structure Based on Self-Determination Theory and Agentic Engagement on Motivation, Engagement and Outcomes in a SEND Secondary School in England

This study looks to address the challenges of engagement in learning for those with additional needs in the UK in the 21st century. In doing so, the model’s aim is to improve access to roles of social value and address the 6% employment rate through better educational outcomes and future opportunities. The meaningful, mastery project-based learning (MMPBL) curriculum model was designed to best facilitate the psychological needs of Ryan and Deci (2000) Self Determination Theory (SDT) and enhance engagement, enhancing student agency. It was tested on Key Stage 4 students (n51) in a secondary special education needs or disability (SEND) school. They chose one of six MMPBL projects and dedicated 350hours towards ‘mastery’ of their strengths. The mixed-method methodology sought to explore what impact, if any, the MMPBL would have compared to the previous ‘typical’ delivery of the national curriculum. Secondary data was drawn from typical academic outcomes and stakeholder voice through focus groups and surveys, using coded analysis of the presence of motivational components and observations of engagement. As an exploratory piece of research, the study was also left open to spontaneous data. The results showed an increase in the presence of competence, relatedness and autonomy, but also built conceptual and applied learning into education. The model led to a positive spiral in outcomes, including engagement (behaviourally- 83% reduction in negative behaviour incidents and +4.16% attendance), improved academic outcomes (cognitively- increasing 0.4 qualifications per student and quality, 0.5 in level), improving autonomy in transition choices (those who went on to subject specific college courses increased by 32% and 2 students gained employment). Stakeholders highlighted a positive impact on culture, perceptions (including identity), development and connecting networks locally and globally (entrepreneurially supporting 29 causes). The research will benefit practitioners, policy makers and academic research as it is the first whole curriculum based on SDT and agentic engagement in SEND. Future studies look to explore if sustainable projects can be built into post-19 social entrepreneurship in SEND

Acculturative stress, challenges, and experiences of asian international students in the United States

Within the United States, many international students may experience the process of acculturation. Acculturation exists when an individual, or group of individuals, from one culture, encounters another culture. Within that context is the experience of acculturative stress (AS). AS is the negative outcome resulting from the pressure and unsuccess of acculturation. In the psychology (and sociology) literature AS is measured among many international communities for many more host countries. Within the United States, Asian International Students (AIS) especially have been seen to have higher rates of AS and a greater hesitation to pursue therapeutic intervention to mitigate the symptoms and related outcomes of that AS. Additionally, the resources offered do not always meet the unique needs of the AIS community. This paper explores the concept of AS as it relates to the AIS community, the assessments used to analyze the effects of AS among AIS, the unique challenges experienced by AIS while studying in the United States (including language barriers, perceived discrimination, academic pressure, and social isolation), best practices established within the counseling community to help combat AS therapeutically and through advocacy, and provides a sample training resource that counselors might use to improve their effectiveness with AS

Teaching the Emergency Department Patient Experience: Needs Assessment from the CORD-EM Task Force.

INTRODUCTION: Since the creation of Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) patient satisfaction (PS) scores, patient experience (PE) has become a metric that can profoundly affect the fiscal balance of hospital systems, reputation of entire departments and welfare of individual physicians. While government and hospital mandates demonstrate the prominence of PE as a quality measure, no such mandate exists for its education. The objective of this study was to determine the education and evaluation landscape for PE in categorical emergency medicine (EM) residencies. METHODS: This was a prospective survey analysis of the Council of Emergency Medicine Residency Directors (CORD) membership. Program directors (PDs), assistant PDs and core faculty who are part of the CORD listserv were sent an email link to a brief, anonymous electronic survey. Respondents were asked their position in the residency, the name of their department, and questions regarding the presence and types of PS evaluative data and PE education they provide. RESULTS: We obtained 168 responses from 139 individual residencies, representing 72% of all categorical EM residencies. This survey found that only 27% of responding residencies provide PS data to their residents. Of those programs, 61% offer simulation scores, 39% provide third-party attending data on cases with resident participation, 37% provide third-party acquired data specifically about residents and 37% provide internally acquired quantitative data. Only 35% of residencies reported having any organized PE curricula. Of the programs that provide an organized PE curriculum, most offer multiple modalities; 96% provide didactic lectures, 49% small group sessions, 47% simulation sessions and 27% specifically use standardized patient encounters in their simulation sessions. CONCLUSION: The majority of categorical EM residencies do not provide either PS data or any organized PE curriculum. Those that do use a heterogeneous set of data collection modalities and educational techniques. American Osteopathic Association and Accreditation Council for Graduate Medical Education residencies show no significant differences in their resident PS data provision or formal curricula. Further work is needed to improve education given the high stakes of PS scores in the emergency physician\u27s career

On the neuroendocrine regulation of reproduction: Functional characterization and kinetic studies of the lamprey gonadotropin -releasing hormone receptor and cloning and analysis of the cDNA encoding lamprey gonadotropin-releasing hormone-III

The vertebrate hypothalamic-pituitary-gonadal (HPG) axis is regulated by gonadotropin-releasing hormone (GnRH), a decapeptide that is produced and released from the hypothalamus. At the anterior pituitary, GnRH action is mediated through high affinity binding with the GnRH receptor, a rhodopsin-like seven transmembrane G-protein coupled receptor (GPCR). Interest in the evolution of reproductive physiology has led scientists to study the lamprey, a member of the oldest extant class of vertebrates, the agnathans. The studies presented herein contribute to the field of reproductive neuroendocrinology through developing our understanding of ancestral, or ancestral-like characteristics and mechanisms of the HPG axis. This dissertation is divided into two major components: (1) functional characterization and kinetic studies of the lamprey GnRH receptor (chapters II and III), and (2) an analysis of the lamprey GnRH-III cDNA (chapter IV). A type II lamprey GnRH receptor was recently identified via cDNA cloning, BLAST analysis and in situ hybridization, however the classification by these homology and expression studies was insufficient. Demonstration of function, through binding capacity or efficacy is a vital and required component of receptor characterization. To this end, a heterologous expression system was developed using COS7 cells transiently transfected with the lamprey GnRH receptor. The lamprey GnRH receptor was shown to be functional as well as lamprey GnRH-III selective based on a series of efficacy and kinetic studies. Ligand dependant internalization was characterized, which was dependant on a motif within the first forty amino acids of the C-terminal tail. Further function and kinetics studies were performed using C-terminal tail truncation mutants. The objective of the second component of this dissertation was to clone and characterize the cDNA encoding lamprey GnRH-III from eight species of lamprey, which were analyzed by phylogenetics methodology to address the molecular evolution of the GnRH family and the lamprey lineage. The lamprey GnRH-III sequences formed three groups, supporting the current view of the lamprey lineage at the family level. Phylogenetic analysis of these sequences together with 64 previously described GnRH sequences suggested that the lamprey GnRHs are unique, as they group together separately from the three previously described paralogous lineages of the GnRH family

Method and apparatus for determining and utilizing a time-expanded decision network

A method, apparatus and computer program for determining and utilizing a time-expanded decision network is presented. A set of potential system configurations is defined. Next, switching costs are quantified to create a "static network" that captures the difficulty of switching among these configurations. A time-expanded decision network is provided by expanding the static network in time, including chance and decision nodes. Minimum cost paths through the network are evaluated under plausible operating scenarios. The set of initial design configurations are iteratively modified to exploit high-leverage switches and the process is repeated to convergence. Time-expanded decision networks are applicable, but not limited to, the design of systems, products, services and contracts

Statistical Methods in Neuroimaging Genetics: Pathways Sparse Regression and Cluster Size Inference

In the field of neuroimaging genetics, brain images are used as phenotypes in the search for genetic variants associated with brain structure or function. This search presents a formidable statistical challenge, not least because of the very high dimensionality of genotype and phenotype data produced by modern SNP (single nucleotide polymorphism) arrays and high resolution MRI. This thesis focuses on the use of multivariate sparse regression models such as the group lasso and sparse group lasso for the identification of gene pathways associated with both univariate and multivariate quantitative traits. The methods described here take particular account of various factors specific to pathways genome-wide association studies including widespread correlation (linkage disequilibrium) between genetic predictors, and the fact that many variants overlap multiple pathways. A resampling strategy that exploits finite sample variability is employed to provide robust rankings for pathways, SNPs and genes. Comprehensive simulation studies are presented comparing one proposed method, pathways group lasso with adaptive weights, to a popular alternative. This method is extended to the case of a multivariate phenotype, and the resulting pathways sparse reduced-rank regression model and algorithm is applied to a study identifying gene pathways associated with structural change in the brain characteristic of Alzheimer’s disease. The original model is also adapted for the task of ’pathways-driven’ SNP and gene selection, and this latter model, pathways sparse group lasso with adaptive weights, is applied in a search for SNPs and genes associated with elevated lipid levels in two separate cohorts of Asian adults. Finally, in a separate section an existing method for the identification of spatially extended clusters of image voxels with heightened activation is evaluated in an imaging genetic context. This method, known as cluster size inference, rests on a number of assumptions. Using real imaging and SNP data, false positive rates are found to be poorly controlled outside of a narrow range of parameters related to image smoothness and activation thresholds for cluster formation

Interaction Tree Specifications: A Framework for Specifying Recursive, Effectful Computations That Supports Auto-Active Verification (Artifact)

This paper presents a specification framework for monadic, recursive, interactive programs that supports auto-active verification, an approach that combines user-provided guidance with automatic verification techniques. This verification tool is designed to have the flexibility of a manual approach to verification along with the usability benefits of automatic approaches. We accomplish this by augmenting Interaction Trees, a Coq datastructure for representing effectful computations, with logical quantifier events. We show that this yields a language of specifications that are easy to understand, automatable, and are powerful enough to handle properties that involve non-termination. Our framework is implemented as a library in Coq. We demonstrate the effectiveness of this framework by verifying real, low-level code

Creating a Differentiated Mathematics Classroom

Recognizing different mathematical learning styles and adapting differentiated teaching strategies can facilitate student learning

Interaction Tree Specifications: A Framework for Specifying Recursive, Effectful Computations That Supports Auto-Active Verification

This paper presents a specification framework for monadic, recursive, interactive programs that supports auto-active verification, an approach that combines user-provided guidance with automatic verification techniques. This verification tool is designed to have the flexibility of a manual approach to verification along with the usability benefits of automatic approaches. We accomplish this by augmenting Interaction Trees, a Coq datastructure for representing effectful computations, with logical quantifier events. We show that this yields a language of specifications that are easy to understand, automatable, and are powerful enough to handle properties that involve non-termination. Our framework is implemented as a library in Coq. We demonstrate the effectiveness of this framework by verifying real, low-level code