Promoting Teaming Metacognition

Improving students’ capacity to effectively perform teaming skills is a crucial outcome for engineering education, and has been the subject of considerable prior and ongoing research. Based upon review of research on teaming, it was hypothesized that greater awareness of appropriate opportunities to use teaming skills in authentic contexts would lead to greater teaming skills employment over time. Further, it was hypothesized that greater psychological safety in student teams would lead to more students choosing to employ appropriate teaming skills over time. An intervention to achieve such increases could therefore be expected to promote student teaming skills performance improvement. Seeking to evaluate potential new methods for teaming skills instruction and development in engineering contexts, a suite of interventions was designed to support growth in student metacognition and the promote psychological safety in student teams.^ This dissertation took the form of a quantitative study implemented in nine sections of the Purdue First-Year Engineering classes ENGR131 (five sections) and ENGR141 (four sections). Multiple psychometric instruments were administered across a semester. Results were investigated to assess the efficacy of the experimental interventions in supporting student teaming metacognition, raising psychological safety, altering relationships between measured variables, and ultimately in raising teaming skills performance. The experimental interventions used in this study incorporate tools and techniques that do not appear to have been previously employed in engineering education. Results suggest that the instrumentation for metacognition was not satisfactory, but that the intervention may have had effects on psychological safety in student teams. These findings are discussed along with directions for further inquiry in the design, implementation, and evaluation of teaming skills instruction

Taking Action: A Proposal for an Analytic Solution to Increase Gateway Course Success

As part of the 2012 SoLAR Flare gathering at Purdue University (October 1-3, 2012), colleagues from higher education institutions and technology service organizations participated in an exercise to develop a learning analytics application to improve college student performance college gateway courses. Defined as high enrollment, high failure rate courses taken by primarily first- and second-year college students, these gateway courses are critical to overall student success in college. This paper summarizes the activities of the group, including the conceptual frameworks that guided discussions and the proposed features of the analytics solution. The exercise was guided by Andrew K. Koch, Executive Vice President of the John N. Gardner Institute for Excellence in Undergraduate Education

Empirical bayes analysis of sequencing-based transcriptional profiling without replicates

Background: Recent technological advancements have made high throughput sequencing an increasingly popular approach for transcriptome analysis. Advantages of sequencing-based transcriptional profiling over microarrays have been reported, including lower technical variability. However, advances in technology do not remove biological variation between replicates and this variation is often neglected in many analyses. Results: We propose an empirical Bayes method, titled Analysis of Sequence Counts (ASC), to detect differential expression based on sequencing technology. ASC borrows information across sequences to establish prior distribution of sample variation, so that biological variation can be accounted for even when replicates are not available. Compared to current approaches that simply tests for equality of proportions in two samples, ASC is less biased towards highly expressed sequences and can identify more genes with a greater log fold change at lower overall abundance. Conclusions: ASC unifies the biological and statistical significance of differential expression by estimating the posterior mean of log fold change and estimating false discovery rates based on the posterior mean. The implementation in R is available at http://www.stat.brown.edu/Zwu/research.aspx

Intraspecific variability in Karlodinium veneficum:Growth rates, mixotrophy and lipid composition

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EXPORTS Measurements and Protocols for the NE Pacific Campaign

EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led and NSF co-funded field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite information and state of the art technology

An operational overview of the EXport processes in the ocean from RemoTe sensing (EXPORTS) northeast pacific field deployment

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set

The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification

Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH)