Gender on the box: Self-reflexivity as a starting point     

Amber Johnson 《Communication Teacher》2019,33(3):228-233

This self-reflexive activity acts as an introduction to how we talk about and express gender identity, as well as the assumptions we may have about gender identity norms and expression. The activity illuminates student’s subconscious behaviors and understandings of gender, pushing them to sit self-reflexively with their own understandings of gender as an identity, expression, binary, and potential locus of shame/freedom.

Courses: Introduction to Women and Gender Studies, Intercultural Communication, Media Studies, Gender and Communication, Performance Studies

Objectives: Designed to introduce students to their own understandings and embodiment of gender, this activity asks students to be honest about their preconceived notions regarding gender that they bring with them into the classroom. The activity utilizes predesigned components that test students’ subconscious knowledge of the gender binary. This is a one-time activity that can be conducted in one 50- or 75-minute class period.  相似文献   

The Grand Challenges Discourse: Transforming Identity Work in Science and Science Policy     

David Kaldewey 《Minerva》2018,56(2):161-182

This article analyzes the concept of “grand challenges” as part of a shift in how scientists and policymakers frame and communicate their respective agendas. The history of the grand challenges discourse helps to understand how identity work in science and science policy has been transformed in recent decades. Furthermore, the question is raised whether this discourse is only an indicator, or also a factor in this transformation. Building on conceptual history and historical semantics, the two parts of the article reconstruct two discursive shifts. First, the observation that in scientific communication references to “problems” are increasingly substituted by references to “challenges” indicates a broader cultural trend of how attitudes towards what is problematic have shifted in the last decades. Second, as the grand challenges discourse is rooted in the sphere of sports and competition, it introduces a specific new set of societal values and practices into the spheres of science and technology. The article concludes that this process can be characterized as the sportification of science, which contributes to self-mobilization and, ultimately, to self-optimization of the participating scientists, engineers, and policymakers.  相似文献   

Progress Is Not an Illusion     

Oren Harman 《Science & Education》2018,27(1-2):219-224

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Letters     

Seth Forman 《Academic Questions》2018,31(3):251-251

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Kuhn’s Image of Science     

William Rehg 《Metascience》2018,27(2):213-215

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Disconnect: Kentucky and the Political Ideology of its Public Universities     

Ben Foster 《Academic Questions》2018,31(3):313-321

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The Evolution of U.S. Museums and Science Centers as Informal Learning Environments     

Renee M. Clary 《Science & Education》2018,27(3-4):371-377

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The Historical Heart of Atmospheric Science     

Anthony J. Sadar 《Science & Education》2018,27(1-2):233-235

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Digital Module 16: Longitudinal Data Analysis     

Jeffrey R. Harring  Tessa L. Johnson 《Educational Measurement》2020,39(3):137-138

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献   

Fußball in Geschichte und Gesellschaft     

Tina Nobis 《Sportwissenschaft》2004,34(4):510-513

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