Putting the Stars within Reach Using NASA 3D Data-Based Models

This study investigated the quantifiable effects of data-based 3D models and prints on spatial reasoning skills and interest in science, technology, engineering, and mathematics (STEM) fields, for n = 100 youths aged 9-12 (99 female and 1 non-binary), primarily from traditionally underrepresented groups in STEM. In a pre-post design, participants engaged in workshops using data-based astrophysical 3D models delivered via computer-based interactions, virtual reality, and 3D prints. Multivariate ANOVAs yielded significantly increased STEM interest but were not significant for increasing spatial ability. The results are discussed in terms of the need to extend exposure and science communications to STEM activities to female youths that are younger than middle school aged

Putting the stars within reach: NASA 3D data-based models in 3D print and virtual reality applications, and their potential effects on improving spatial reasoning skills and STEM interest in underrepresented groups of young female learners

This study examined the effects of data-based astrophysical 3D models delivered via computer based interactions, virtual reality, and 3D prints, on spatial reasoning skills and interest in science, technology, engineering, and mathematics (STEM) for females aged 9-12, in particular from underrepresented groups. Underrepresented, or underserved, audiences refer to the demographic status of, and the services that are offered or presented to, segments of a community, typically not currently being served within a larger population that might benefit from such services (Williams et al., 2009). Research to date has not focussed on the development of STEM interests and spatial reasoning skills of young females, particularly at the time when such young learners are forming potential identities in or with STEM and beginning to think about educational and career-related options. STEM interest has been shown to be a critical component of developing a STEM identity, and can be intertwined with issues of confidence and self-efficacy for young female learners (see e.g., Bian et al., 2017; Blotnicky et al., 2018; Fouad, & Smith, 1996; Simpkins et al., 2006). Mental manipulation and understanding of 2D or 3D objects has been posited as an important STEM skill, helping to indicate future mathematical success, science performance, and potential pursuit of STEM careers (Ganley et al., 2014; Hegarty & Waller, 2005; Rafi et al., 2005; Uttal & Cohen, 2012; Verdine et al., 2014). A mixed methods design was used for this research. In Study 1, a qualitative approach examined potential obstacles to and challenges in working in STEM field for females from underrepresented groups. Unstructured interviews with 11 adult females representing diverse groups and various STEM careers yielded important historical perspectives, along with recommendations for building STEM careers for young females today. The recommendations from Study 1 generated three areas that informed the development of Study 2: the critical role of having a strong mentor, role model, or support system in place along the STEM pathway; the need to work with and engage females in STEM activities and subjects when they are as young as possible, preferably while in primary/elementary school; and the importance of developing a sense of STEM self-efficacy in young females. Study 2 was a quantitative study that investigated the overall research question. Participants were three different groups of young female learners (n = 100), ages 9 -12. The participants worked directly with data-based astrophysical 3D models, in short term interventions in formal and informal educational workshop settings. The interventions concatenated concepts driven by current astrophysical data models, providing authentic learning experiences in full and half day formats through coding, 3D modeling, 3D printing and virtual reality, and delivered by women researchers in STEM. The results showed that such interventions that utilized real world data manipulations and 3D applications as part of hands-on activities significantly increased STEM interest for the participants from underserved groups. Results were not significant for increasing spatial ability. The results are discussed in terms of the need to extend exposure to STEM activities and interventions for females younger than middle school, especially in underserved areas, to encourage interest and self-confidence in further STEM education and future careers. The research also offers recommendations on how to better approach the evaluation of and potential improvement of spatial reasoning skills that take into consideration age and cognitive appropriateness. This study holds promise for helping to engage young and underserved females who might otherwise not have confidence in their abilities or even be aware of their potential to contribute in STEM areas

Processing Color in Astronomical Imagery

Every year, hundreds of images from telescopes on the ground and in space are released to the public, making their way into popular culture through everything from computer screens to postage stamps. These images span the entire electromagnetic spectrum from radio waves to infrared light to X-rays and gamma rays, a majority of which is undetectable to the human eye without technology. Once these data are collected, one or more specialists must process the data to create an image. Therefore, the creation of astronomical imagery involves a series of choices. How do these choices affect the comprehension of the science behind the images? What is the best way to represent data to a non-expert? Should these choices be based on aesthetics, scientific veracity, or is it possible to satisfy both? This paper reviews just one choice out of the many made by astronomical image processors: color. The choice of color is one of the most fundamental when creating an image taken with modern telescopes. We briefly explore the concept of the image as translation, particularly in the case of astronomical images from invisible portions of the electromagnetic spectrum. After placing modern astronomical imagery and photography in general in the context of its historical beginnings, we review the standards (or lack thereof) in making the basic choice of color. We discuss the possible implications for selecting one color palette over another in the context of the appropriateness of using these images as science communication products with a specific focus on how the non-expert perceives these images and how that affects their trust in science. Finally, we share new data sets that begin to look at these issues in scholarly research and discuss the need for a more robust examination of this and other related topics in the future to better understand the implications for science communications.Comment: 10 pages, 6 figures, published in Studies in Media and Communicatio

Black Holes and Vacuum Cleaners: Using Metaphor, Relevance, and Inquiry in Labels for Space Images

This study extended research on the development of explanatory labels for astronomical images for the non-expert lay public. The research questions addressed how labels with leading questions/metaphors and relevance to everyday life affect comprehension of the intended message for deep space images, the desire to learn more, and the aesthetic appreciation of images. Participants were a convenience sample of 1,921 respondents solicited from a variety of websites and through social media who completed an online survey that used four high-resolution images as stimuli: Sagittarius A*, Solar Flare, Cassiopeia A, and the Pinwheel Galaxy (M101). Participants were randomly assigned initially to 1 of 3 label conditions: the standard label originally written for the image, a label with a leading question containing a metaphor related to the information for the image, or a label that contained a fact about the image relevant to everyday life. Participants were randomly assigned to 1 image and compared all labels for that image. Open-ended items at various points asked participants to pose questions to a hypothetical astronomer. Main findings were that the relevance condition was significantly more likely to increase wanting to learn more; the original label was most likely to increase overall appreciation; and, smart phone users were more likely to want to learn more and report increased levels of appreciation. Results are discussed in terms of the need to examine individual viewer characteristics and goals in creating different labels for different audiences.Comment: 50 pages, 7 tables, 2 figures, accepted by the journal "Psychology of Aesthetics, Creativity, and the Arts

Women in STEM Interview Analysis: Encouraging Young Female Learners in STEM Pathways

This study used a qualitative approach to examine potential obstacles to and challenges in working in a STEM field for females from underrepresented groups. Unstructured interviews with 11 adult females representing diverse groups and various STEM careers yielded important historical perspectives, along with recommendations for building STEM careers for young females today. The findings indicated the critical role of having a strong mentor, role model, or support system in place along the STEM pathway; the need to work with and engage females in STEM activities and subjects when they are as young as possible, preferably while in primary/elementary school; and the importance of developing a sense of STEM self-efficacy in young females. Recommendations are given to inform studies in science communication and informal education

High Energy Vision: Processing X-rays

Astronomy is by nature a visual science. The high quality imagery produced by the world’s observatories can be a key to effectively engaging with the public and helping to inspire the next generation of scientists. Creating compelling astronomical imagery can, however, be particularly challenging in the non-optical wavelength regimes. In the case of X-ray astronomy, where the amount of light available to create an image is severely limited, it is necessary to employ sophisticated image processing algorithms to translate light beyond human vision into imagery that is aesthetically pleasing while still being scientifically accurate. This paper provides a brief overview of the history of X-ray astronomy leading to the deployment of NASA’s Chandra X-ray Observatory, followed by an examination of the specific challenges posed by processing X-ray imagery. The authors then explore image processing techniques used to mitigate such processing challenges in order to create effective public imagery for X-ray astronomy. A follow-up paper to this one will take a more in-depth look at the specific techniques and algorithms used to produce press-quality imagery