The absorption and emission spectrum of radiative cooling galactic fountain gas

We have calculated the time-dependent, nonequilibrium thermal and ionization history of gas cooling radiatively from 10(exp 6) K in a one-dimensional, planar, steady-state flow model of the galactic fountain, including the effects of radiative transfer. Our previous optically thin calculations explored the effects of photoionization on such a flow and demonstrated that self-ionization was sufficient to cause the flow to match the observed galactic halo column densities of C 4, Si 4, and N 5 and UV emission from C 4 and O 3 in the constant density (isochoric) limit, which corresponded to cooling regions homogeneous on scales D less than or approximately equal to 1 kpc. Our new calculations which take full account of radiative transfer confirm the importance of self-ionization in enabling such a flow to match the data but allow a much larger range for cooling region sizes, i.e. D(sub 0) greater than or approximately equal to 15 pc. For an initial flow velocity v(sub 0) approximately equal to 100 km/s, comparable to the sound speed of a 10(exp 6) K gas, the initial density is found to be n(sub h,0) is approximately 2 x 10(exp -2) cm(exp -3), in reasonable agreement with other observation estimates, and D(sub 0) is approximately equal to 40 pc. We also compare predicted H(alpha) fluxes, UV line emission, and broadband x-ray fluxes with observed values. One dimensional numerical hydrodynamical calculations including the effects of radiative cooling are also presented

Interaction Geography & the Learning Sciences

The three papers in this dissertation contribute to research that seeks to characterize the complex and multi-dimensional relation between the physical environment and human learning. The first paper outlines a new approach to describe, represent, and interpret people’s interaction as they move within and across physical environments. I call this approach interaction geography. It encompasses Mondrian Transcription, a method to map people’s movement and conversation over space and time, and the Interaction Geography Slicer (IGS), a dynamic visualization tool that supports new forms of interaction and multi-modal analysis. The second paper extends this work to provide a conceptual framework to expand interaction geography in studies of learning. I show how interaction geography offers resources to integrate four historically separate research perspectives in order to study how people’s interaction, movement, and responses to, and actions on, the physical environment lead people to learn. The third paper adapts and uses the IGS to visualize and discuss data about New York City’s Stop-And-Frisk Program. I show how the IGS provides new ways to view, interact with, and query large-scale data sets of stop-and-frisk and crime data over space and through time to support analyses of and public discussion about a controversial social and political issue

Personal Curation in a Museum

An established body of work in CSCW and related communities studies social and cooperative interaction in museums and cultural heritage sites. A separate and growing body of research in these same communities is developing ways to understand the design and use of social media from a curating perspective. A curating perspective focuses on how social media is designed and used by people to develop and manage their own digital archives. This paper uses a cultural heritage museum as the empirical basis and setting along with new information visualization methods we have developed to better integrate these bodies of work and introduce the concept of personal curation; a socio-technical practice in which people collect, edit, and share information using personal information devices and social media as they move through physical environments rich with meaning potential. In doing so this paper makes three contributions. First, it illustrates how to combine a spatial focus on people’s movement and interaction through the physical environment with an analysis of social media use in order to gain a deeper understanding of practices such as personal curation. Second, it shows in greater detail how visitors to museums and cultural heritage sites use and link digital information with physical information to shape others’ understandings of cultural heritage. Third, it suggests how museums and cultural heritage sites may leverage personal curation to support more expansive learning opportunities for visitors

Interactive Transcription Techniques for Interaction Analysis

Interaction analysis is a valuable method and approach to study knowledge in use in the learning sciences and CSCL communities. Central to interaction analysis is the creation of transcripts to selectively encode and represent audio and video data. However, current transcription techniques used in interaction analysis, including multimodal transcription techniques, have yet to explore the strengths and weaknesses of interactive visualization to selectively encode and represent people’s interaction in context. Drawing from our recent efforts to amplify, not automate, transcription in qualitative research, this paper interactively visualizes one video dataset in five different ways using contemporary interactive visualization techniques. Findings and discussion characterize these visualizations as interactive transcripts that demonstrate techniques valuable to interaction analysis, but also highlight the need to expand how people, things, and context are represented through visualization mediums such as visualization programming languages to align with work more meaningfully in the learning sciences and CSCL communities

Using the Interaction Geography Slicer to Visualize New York City Stop & Frisk

This paper adapts and uses a dynamic visualization environment called the Interaction Geography Slicer (IGS) developed by the 1st author to visualize data about New York City’s Stop & Frisk Program. Findings and discussion focus on how this environment provides new ways to view, interact with and query large-scale data sets over space and through time to support analyses of and public discussion about New York City’s Stop & Frisk Program

Classroom Interaction Geography: A Case Study

The study of classroom discourse is central to understanding and supporting effective teaching practice. Recently, researchers have begun to explore the spatial dimension of classroom discourse. However, this work emphasizes the lack of methods, particularly visual methods, to fully explore the spatial dimension of classroom discourse. This paper uses an approach to studying collaborative interaction we have developed called interaction geography to revisit a classic case known as “Sean Numbers” from the work of renown teacher educator Deborah Ball. Our analysis highlights the value of interaction geography to visually and dynamically explore the spatial and temporal dimensions of classroom discourse. We also make a data visualization of this work available to support further discussion and work to describe classroom interaction geograph

When Wrong is Right: The Instructional Power of Multiple Conceptions

For many decades, educational communities, including computing education, have debated the value of telling students what they need to know (i.e., direct instruction) compared to guiding them to construct knowledge themselves (i.e., constructivism). Comparisons of these two instructional approaches have inconsistent results. Direct instruction can be more efficient for short-term performance but worse for retention and transfer. Constructivism can produce better retention and transfer, but this outcome is unreliable. To contribute to this debate, we propose a new theory to better explain these research results. Our theory, multiple conceptions theory, states that learners develop better conceptual knowledge when they are guided to compare multiple conceptions of a concept during instruction. To examine the validity of this theory, we used this lens to evaluate the literature for eight instructional techniques that guide learners to compare multiple conceptions, four from direct instruction (i.e., test-enhanced learning, erroneous examples, analogical reasoning, and refutation texts) and four from constructivism (i.e., productive failure, ambitious pedagogy, problem-based learning, and inquiry learning). We specifically searched for variations in the techniques that made them more or less successful, the mechanisms responsible, and how those mechanisms promote conceptual knowledge, which is critical for retention and transfer. To make the paper directly applicable to education, we propose instructional design principles based on the mechanisms that we identified. Moreover, we illustrate the theory by examining instructional techniques commonly used in computing education that compare multiple conceptions. Finally, we propose ways in which this theory can advance our instruction in computing and how computing education researchers can advance this general education theory

Exploring Approaches to Data Literacy Through a Critical Race Theory Perspective

In this paper, we describe and analyze a workshop developed for a work training program called DataWorks. In thisworkshop, data workers chose a topic of their interest, sourced and processed data on that topic, and used that data to createpresentations. Drawing from discourses of data literacy; epistemic agency and lived experience; and critical race theory, we analyze the workshops’ activities and outcomes. Through this analysis, three themes emerge: the tensions between epistemic agency and the context of work, encountering the ordinariness of racism through data work, and understanding the personal as communal and intersectional. Finally, critical race theory also prompts us to consider the very notions of data literacy that undergird our workshop activities. From this analysis, we offer a series of suggestions for approaching designing data literacy activities, taking into account critical race theory

The Linear Perturbation Theory of Reionization in Position-Space: Cosmological Radiative Transfer Along the Light-Cone

The linear perturbation theory of inhomogeneous reionization (LPTR) has been developed as an analytical tool for predicting the global ionized fraction and large-scale power spectrum of ionized density fluctuations during reionization. In the original formulation of the LPTR, the ionization balance and radiative transfer equations are linearized and solved in Fourier space. However, the LPTR's approximation to the full solution of the radiative transfer equation is not straightforward to interpret, since the latter is most intuitively conceptualized in position space. To bridge the gap between the LPTR and the language of numerical radiative transfer, we present a new, equivalent, position-space formulation of the LPTR that clarifies the approximations it makes and facilitates its interpretation. We offer a comparison between the LPTR and the excursion-set model of reionization (ESMR), and demonstrate the built-in capability of the LPTR to explore a wide range of reionization scenarios, and to go beyond the ESMR in exploring scenarios involving X-rays.Comment: 10 pages, 1 figure, 1 table. Accepted by PRD with minor change

ARtonomous: Introducing Middle School Students to Reinforcement Learning Through Virtual Robotics

Typical educational robotics approaches rely on imperative programming for robot navigation. However, with the increasing presence of AI in everyday life, these approaches miss an opportunity to introduce machine learning (ML) techniques grounded in an authentic and engaging learning context. Furthermore, the needs for costly specialized equipment and ample physical space are barriers that limit access to robotics experiences for all learners. We propose ARtonomous, a relatively low-cost, virtual alternative to physical, programming-only robotics kits. With ARtonomous, students employ reinforcement learning (RL) alongside code to train and customize virtual autonomous robotic vehicles. Through a study evaluating ARtonomous, we found that middle-school students developed an understanding of RL, reported high levels of engagement, and demonstrated curiosity for learning more about ML. This research demonstrates the feasibility of an approach like ARtonomous for 1) eliminating barriers to robotics education and 2) promoting student learning and interest in RL and ML.Comment: In Proceedings of Interaction Design and Children (IDC '22