Student Background and Implications for Design of Technology-Enhanced Instruction

Knowledge of students’ construction and technology background is an important input to the process of designing technology enhanced instruction. Current literature in student background is either not specific for the construction/civil engineering student population or lacks direct implications for pedagogical design. This paper presents a survey study that assesses students’ self-reported technology skills and attitude, learning preferences, and baseline construction knowledge. The survey is designed as a questionnaire with three sections: demographic and background information, technology attitude and exposure, and construction-related knowledge. From the 280 data points collected, it was found that today’s students are exposed to a wide range of technology applications. They had a positive attitude toward technology, were enthusiastic video-game players, and strongly preferred learning activities that involved interactions, whether these interactions were face-to-face or mediated by technology. These findings suggest that technology-assisted learning would excite and engage students. The paper also provides a discussion on specific pedagogical design implications of the findings and ways in which these could be incorporated in the design of technology-enhanced learning tools.Civil, Architectural, and Environmental Engineerin

Learning to teach (LETS): developing curricular and cross curricular competences in becoming a 'good' secondary teacher: executive summary

The aim of this research, the Learning to Teach Study (LETS), the first of its kind on the Postgraduate Diploma in Education (PGDE) in Ireland, funded by the Department of Education and Skills (DES), was to develop and implement a study of initial teacher education in the PGDE in post-primary education, in the School of Education, University College Cork. Its aim was to identify the individual and contextual dynamics of how student teachers develop curricular and cross-curricular competences during initial teacher education (ITE). Within an overall framework that explores how student teachers develop their skills, competences and identity as teachers, it focuses on curricular competences in mathematics, science and language teaching, and on the cross-curricular competences of reading and digital literacy and the development of inclusive teaching practices. LETS is the first programme level research on the PGDE, familiarly known to generations of student teachers and teachers as ‘the Dip’ or ‘the HDip’. Drawing on research on teacher education both in Ireland and internationally, the LETS report is divided into six sections encompassing thirteen chapters. Section 1 includes the review of literature and study aims in Chapter 1 and the research methodology in Chapter 2. Adopting an interpretive approach, LETS involved the collaborative development of three interviews protocols and a survey by the research team. Seventeen (n=17) students were interviewed three times over the course of PGDE programme, and one hundred and thirty three students completed a detailed survey on their learning to teach experience (n=133, i.e. response rate of 62.7% of the 212 students in the PGDE 2008/09 cohort). The four chapters in Section 2 focus on professional identity as a central dimension of learning to teach. Among the dimensions of learning to teach addressed in this section are the role of observation and cultural scripts in becoming a teacher, the visibility/invisibility of PGDE students as learners and the relationships between emotions, resilience and commitment to teaching. The three chapters in Section 3 focus on mathematics, modern languages and science respectively in the context of conventional and reform-oriented visions of good teaching. A number of common as well as subject-specific themes emerged in this section in relation to subject matter teaching. Section 4 focuses on PGDE students’ experience of inclusion (chapter 10) and reading literacy (chapter 11) while learning to teach. Section 5 focuses on a key aspect of initial teacher education, namely, the school-university partnership. The final section provides a summary of the findings, identifies seven key issues emerging from these findings, makes Learning to Teach Study (LETS) recommendations under four headings (system, teacher education institutions, partnerships in ITE and further research) and discusses some implications for research, policy and practice in initial teacher education. Among the main findings emerging from the study are: (i) schools provide valuable support for PGDE students but this typically does not focus on classroom pedagogy, (ii) PGDE students typically felt that they had to be ‘invisible’ as learners in schools to gain and maintain authority and status, (iii) inherited cultural scripts about what it means to be a ‘good’ subject teacher shaped teacher identity and classroom practice, and (iv) as PGDE students begin to feel competent as teachers of maths, modern languages and science, this feeling of competence typically does not include their capacity to teach for inclusion and reading literacy within their subject teaching. In the context of research on teacher education, many of the findings are not unique to the PGDE or to UCC but reflect perennial dilemmas and emerging challenges in initial teacher education. This fact is important in setting a context for the wider dissemination2 of the Learning to Teach Study

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol

Introduction Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision.Methods and analysis Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set.Ethics and dissemination The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public

US National Climate Assessment (NCA) Scenarios for Assessing Our Climate Future: Issues and Methodological Perspectives Background Whitepaper for Participants

This whitepaper is intended to provide a starting point for discussion at a workshop for the National Climate Assessment (NCA) that focuses on the use and development of scenarios. The paper will provide background needed by participants in the workshop in order to review options for developing and using scenarios in NCA. The paper briefly defines key terms and establishes a conceptual framework for developing consistent scenarios across different end uses and spatial scales. It reviews uses of scenarios in past U.S. national assessments and identifies potential users of and needs for scenarios for both the report scheduled for release in June 2013 and to support an ongoing distributed assessment process in sectors and regions around the country. Because scenarios prepared for the NCA will need to leverage existing research, the paper takes account of recent scientific advances and activities that could provide needed inputs. Finally, it considers potential approaches for providing methods, data, and other tools for assessment participants. We note that the term 'scenarios' has many meanings. An important goal of the whitepaper (and portions of the workshop agenda) is pedagogical (i.e., to compare different meanings and uses of the term and make assessment participants aware of the need to be explicit about types and uses of scenarios). In climate change research, scenarios have been used to establish bounds for future climate conditions and resulting effects on human and natural systems, given a defined level of greenhouse gas emissions. This quasi-predictive use contrasts with the way decision analysts typically use scenarios (i.e., to consider how robust alternative decisions or strategies may be to variation in key aspects of the future that are uncertain). As will be discussed, in climate change research and assessment, scenarios describe a range of aspects of the future, including major driving forces (both human activities and natural processes), changes in climate and related environmental conditions (e.g., sea level), and evolution of societal capability to respond to climate change. This wide range of scenarios is needed because the implications of climate change for the environment and society depend not only on changes in climate themselves, but also on human responses. This degree of breadth introduces and number of challenges for communication and research

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The Evolutionary Dynamics of the Lion Panthera leo Revealed by Host and Viral Population Genomics

The lion Panthera leo is one of the world's most charismatic carnivores and is one of Africa's key predators. Here, we used a large dataset from 357 lions comprehending 1.13 megabases of sequence data and genotypes from 22 microsatellite loci to characterize its recent evolutionary history. Patterns of molecular genetic variation in multiple maternal (mtDNA), paternal (Y-chromosome), and biparental nuclear (nDNA) genetic markers were compared with patterns of sequence and subtype variation of the lion feline immunodeficiency virus (FIVPle), a lentivirus analogous to human immunodeficiency virus (HIV). In spite of the ability of lions to disperse long distances, patterns of lion genetic diversity suggest substantial population subdivision (mtDNA ΦST = 0.92; nDNA FST = 0.18), and reduced gene flow, which, along with large differences in sero-prevalence of six distinct FIVPle subtypes among lion populations, refute the hypothesis that African lions consist of a single panmictic population. Our results suggest that extant lion populations derive from several Pleistocene refugia in East and Southern Africa (∼324,000–169,000 years ago), which expanded during the Late Pleistocene (∼100,000 years ago) into Central and North Africa and into Asia. During the Pleistocene/Holocene transition (∼14,000–7,000 years), another expansion occurred from southern refugia northwards towards East Africa, causing population interbreeding. In particular, lion and FIVPle variation affirms that the large, well-studied lion population occupying the greater Serengeti Ecosystem is derived from three distinct populations that admixed recently