Rebuilding a Teaching Conference in a Pandemic: User-Centered Guiding Principles and Lessons Learned

The COVID-19 pandemic challenged educational developers, like instructors across the world, to pivot their traditionally face-to-face faculty development programs to online formats. At the Stearns Center for Teaching and Learning at George Mason University (classified as research-intensive and the largest public institution in Virginia, United States), we faced the challenge of reimagining our annual pedagogy conference that scaled from 497 registered in 2019 when it was face-to-face to over 800 in 2020 as it was moved online. Under pressures of limited resources and increased uncertainty, leaders can find it difficult to imagine pathways toward innovation rather than just daily responses to crises, yet centers for teaching and learning (CTLs) need to take and maintain leadership roles in our institutions. Here we outline our programmatic goals, our guiding user-centered principles (from user experience frameworks; that is, Zarour and Alharbi, 2017), and the user-centered iterative design process from learning engineering (Kessler, 2019) that enabled our evidence-based decision-making processes to select conference support technology platforms and create the conference infrastructure and workflows. We discuss a variety of data sources that informed our decision-making processes throughout the conference planning and actual event. We share assessment results and lessons learned that guide innovation in CTLs and can be applied to a range of educational development programs from large conferences like ours to small workshops and even one-to-one consultations

Designing Programs to Prepare Future Faculty for Academic Careers: Insights from a Longitudinal Case Study of a Multidisciplinary Cohort-based Program Model for Doctoral Students

Many universities offer some version of centrally offered professional development opportunities for graduate students seeking academic careers. Less is known about what impact these programs have on student career preparation and success and which design elements are most beneficial to each learner (Diggs et al., 2017; Schram et al., 2017). This article reports on a mixed methods decadal review (2011–2021) of one large, research-intensive institution’s multidisciplinary cohort-based year-long program, Preparing for Academic Careers, for graduate students near the end of their doctoral or master’s of fine arts (MFA) degree. Results from a systematic employment status search using publicly available records (Google and LinkedIn) indicate that a higher percentage of participants are employed in academic positions than national trends. Results from the analyses of closed and open-ended questions from an alumni survey suggest a range of perceived benefits: an increased sense of belonging in the academy, comfort talking to others about their work, confidence as an instructor, and interest in cross-disciplinary work. These findings will inform others seeking to design and implement academic career preparation programs that aim to provide student-level support in an inclusive and multidisciplinary environment

Creating Bridges: The Role of Exploratory Design Research in an Intelligent Tutoring System Project

Designers of Intelligent Tutoring Systems (ITS) have long been interested in delivering personalised teaching to individual students, typically by ensuring that the student receives content appropriate to their skills and knowledge. Nonetheless, a more holistic view on what constitutes good teaching practice has challenged whether this approach to user modelling is sufficient. Teaching is not only defined by what is taught, but also by how it is taught. In this paper, we demonstrate that exploratory design research can support this view by generating a more inclusive set of user attributes for purposes of user modelling. Through a case study, we show that design research for user modelling can function as a boundary object serving three important roles, that underpin more specifically the design of user modelling and more broadly ITS design. First, design research can establish common ground by encapsulating domain knowledge in an accessible form. This can support diverse project stakeholders to make decisions on what is to be modelled. Second, design research can reveal a wide range of teaching and learning perspectives that in turn introduce transparency to the decision-making process of user modelling and provoke a sense of criticality and accountability amongst project stakeholders. Third, design research can build new bridges between the design of the technology and the user model that underpins it. To this end, user attributes deemed important, yet too complex or cumbersome to develop, can become design principles in the context of the overall ITS design

Post-transcriptional control of tumor cell autonomous metastatic potential by the CCR4-NOT deadenylase CNOT7

Accumulating evidence supports the role of an aberrant transcriptome as a driver of metastatic potential. Deadenylation is a general regulatory node for post-transcriptional control by microRNAs and other determinants of RNA stability. Previously, we demonstrated that the CCR4-NOT scaffold component Cnot2 is an inherited metastasis susceptibility gene. In this study, using orthotopic metastasis assays and genetically engineered mouse models, we show that one of the enzymatic subunits of the CCR4-NOT complex, Cnot7, is also a metastasis modifying gene. We demonstrate that higher expression of Cnot7 drives tumor cell autonomous metastatic potential, which requires its deadenylase activity. Furthermore, metastasis promotion by CNOT7 is dependent on interaction with CNOT1 and TOB1. CNOT7 ribonucleoprotein-immunoprecipitation (RIP) and integrated transcriptome wide analyses reveal that CNOT7-regulated transcripts are enriched for a tripartite 3’UTR motif bound by RNA-binding proteins known to complex with CNOT7, TOB1, and CNOT1. Collectively, our data support a model of CNOT7, TOB1, CNOT1, and RNA-binding proteins collectively exerting post-transcriptional control on a metastasis suppressive transcriptional program to drive tumor cell metastasis

Waveform Modelling for the Laser Interferometer Space Antenna

LISA, the Laser Interferometer Space Antenna, will usher in a new era in gravitational-wave astronomy. As the first anticipated space-based gravitational-wave detector, it will expand our view to the millihertz gravitational-wave sky, where a spectacular variety of interesting new sources abound: from millions of ultra-compact binaries in our Galaxy, to mergers of massive black holes at cosmological distances; from the beginnings of inspirals that will venture into the ground-based detectors' view to the death spiral of compact objects into massive black holes, and many sources in between. Central to realising LISA's discovery potential are waveform models, the theoretical and phenomenological predictions of the pattern of gravitational waves that these sources emit. This white paper is presented on behalf of the Waveform Working Group for the LISA Consortium. It provides a review of the current state of waveform models for LISA sources, and describes the significant challenges that must yet be overcome.Comment: 239 pages, 11 figures, white paper from the LISA Consortium Waveform Working Group, invited for submission to Living Reviews in Relativity, updated with comments from communit

Geoscience Education Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Practitioners and researchers in geoscience education embrace collaboration applying ICON (Integrated, Coordinated, Open science, and Networked) principles and approaches ICON principles and approaches have been used to create and share large collections of educational resources, to move forward collective priorities, and to foster peer-learning among educators. These strategies can also support the advancement of coproduction between geoscientists and diverse communities. For this reason, many authors from the geoscience education community have co-created three commentaries on the use and future of ICON in geoscience education. We envision that sharing our expertise with ICON practice will be useful to other geoscience communities seeking to strengthen collaboration. Geoscience education brings substantial expertise in social science research and its application to building individual and collective capacity to address earth sustainability and equity issues at local to global scales The geoscience education community has expanded its own ICON capacity through access to and use of shared resources and research findings, enhancing data sharing and publication, and leadership development. We prioritize continued use of ICON principles to develop effective and inclusive communities that increase equity in geoscience education and beyond, support leadership and full participation of systemically non-dominant groups and enable global discussions and collaborations

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives