This report presents findings of the Latina SciGirls mixed methods study, investigating the experiences of young Latinas participating in informal STEM programs across the U.S. that utilized the SciGirls educational model (including the SciGirls Seven strategies) and augmented with materials and practices intended to better serve Hispanic girls. The project was led by Twin Cities Public Television with funding from the National Science Foundation as an AISL Innovations in Development project. The STEM-related identity framework and research model used to guide this investigation is presented
Knight Williams, Inc. completed a summative evaluation report that addresses: (i) the reach and breadth of the Latina SciGirls broadcast program and online components compared to project expectations; (ii) the impact of the Family Fiesta events that incorporated use of SciGirls videos, in-person role models, and hands-on activities as experienced by the girls, family members, and role models that participated in the events; and (iii) the partners’ Latina SciGirls programs and how they used and reflected on the value of the SciGirls resources.
How can creators of STEM learning media reach underserved parents and children, and support the kinds of playful STEM interactions that are foundational for future STEM learning?
This research report summarizes findings from a pilot study of Cyberchase: Mobile Adventures in STEM, a program that uses mobile text messaging and short videos to encourage hands-on family learning among low-income Latino families.
In the study, 95 mostly Latino families received weekly text messages with video clips from the popular children's series Cyberchase, and fun activities to do with their
This INSPIRE award is partially funded by the Cyber-Human Systems Program in the Division of Information and Intelligent Systems in the Directorate for Computer Science and Engineering, the Gravitational Physics Program in the Division of Physics in the Directorate for Mathematical and Physical Sciences, and the Office of Integrative Activities.
This innovative project will develop a citizen science system to support the Advanced Laser Interferometer Gravitational wave Observatory (aLIGO), the most complicated experiment ever undertaken in gravitational physics. Before the end of this decade it will open up the window of gravitational wave observations on the Universe. However, the high detector sensitivity needed for astrophysical discoveries makes aLIGO very susceptible to noncosmic artifacts and noise that must be identified and separated from cosmic signals. Teaching computers to identify and morphologically classify these artifacts in detector data is exceedingly difficult. Human eyesight is a proven tool for classification, but the aLIGO data streams from approximately 30,000 sensors and monitors easily overwhelm a single human. This research will address these problems by coupling human classification with a machine learning model that learns from the citizen scientists and also guides how information is provided to participants. A novel feature of this system will be its reliance on volunteers to discover new glitch classes, not just use existing ones. The project includes research on the human-centered computing aspects of this sociocomputational system, and thus can inspire future citizen science projects that do not merely exploit the labor of volunteers but engage them as partners in scientific discovery. Therefore, the project will have substantial educational benefits for the volunteers, who will gain a good understanding on how science works, and will be a part of the excitement of opening up a new window on the universe.
This is an innovative, interdisciplinary collaboration between the existing LIGO, at the time it is being technically enhanced, and Zooniverse, which has fielded a workable crowdsourcing model, currently involving over a million people on 30 projects. The work will help aLIGO to quickly identify noise and artifacts in the science data stream, separating out legitimate astrophysical events, and allowing those events to be distributed to other observatories for more detailed source identification and study. This project will also build and evaluate an interface between machine learning and human learning that will itself be an advance on current methods. It can be depicted as a loop: (1) By sifting through enormous amounts of aLIGO data, the citizen scientists will produce a robust "gold standard" glitch dataset that can be used to seed and train machine learning algorithms that will aid in the identification task. (2) The machine learning protocols that select and classify glitch events will be developed to maximize the potential of the citizen scientists by organizing and passing the data to them in more effective ways. The project will experiment with the task design and workflow organization (leveraging previous Zooniverse experience) to build a system that takes advantage of the distinctive strengths of the machines (ability to process large amounts of data systematically) and the humans (ability to identify patterns and spot discrepancies), and then using the model to enable high quality aLIGO detector characterization and gravitational wave searches
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TEAM MEMBERS:
Vassiliki KalogeraAggelos KatsaggelosKevin CrowstonLaura TrouilleJoshua SmithShane LarsonLaura Whyte
resourceresearchProfessional Development, Conferences, and Networks
This handout was prepared for the Climate Change Showcase at the 2019 ASTC Conference in Toronto, Ontario. It highlights resources available on InformalScience.org related to the topic of climate change.
In this poster, the Center for Research on Lifelong STEM Learning shared lessons learned from a study that used audio and video data from GoPros to investigate the entry characteristics of zoo and aquarium visitors and how those characteristics played out in terms of decision-making behaviors and meaning-making talk during a visit.
The poster presents information about a research study where we used video-based data collection to investigate how framing of interpretive signage influences visitors’ talk and behaviors at exhibits. The poster shared details of our methods as well as lessons learned from using cameras for capturing video of visiting groups.
One way to motivate young people from diverse backgrounds to pursue engineering careers is to enlist them as educators who can help the general public understand how engineers help respond to the challenges of everyday life. The New York Hall of Science, which serves a large and diverse audience, is an ideal setting for testing the promise of this strategy. Youth educators and curators of public programs at the Hall of Science will mentor two groups of high school- and early college-aged youth, who will contribute to the design and facilitation of engineering-focused events and activities for museum visitors. They will work together to develop engineering programming for the public that emphasizes the cultural and interpersonal dimensions of engineering practices. This group of young people will be recruited from the Hall of Science's more than 100 Explainers, a very diverse group of young people who work part-time at the Hall of Science and engage with visitors as they explore the museum. Researchers will track participants' experiences and document their impact on museum visitors' perceptions of engineering. The expectation is that creating and delivering these experiences for visitors will have a positive impact on the youth participants' understanding of the engineering disciplines, and on visitors' perceptions of engineering and its relationship to everyday life.
The project will use observations, interviews, journaling, and the Engineering Professional Skills Assessment to explore youth experience, and visitor exit surveys and interviews to probe visitor perceptions. Both the skills assessment and visitor surveys are NSF-funded instruments. Data coding will be grounded in the engineering habits of mind defined by the National Research Council's Committee on Understanding and Improving K-12 Engineering Education in the United States (2009). The project will capture evidence regarding which habits of mind the Fellows are most frequently engaged with. The effort will also explore how interactions with peers (as colleagues), with experts (as learners, such as with Designers in Residence) and with visitors (as teachers and leaders) may be associated with different combinations of the habits of mind over the course of the project. Visitor data and assessment data will allow the project to begin to make analytic connections between participating young people's increased understanding of culturally-situated engineering challenges, and their impact on the experiences of museum visitors who engage with engineering programming at the Hall of Science.
In this paper we share an emerging analytical approach to designing and studying STEAM programs that focuses on how programs integrate the respective epistemic practices—the ways in which knowledge is constructed—of science and art. We share the rationale for moving beyond surface features of STEAM programs (e.g., putting textiles and electronics on the same table) to the disciplinary-specific ways in which participants are engaged in creative inquiry and production. We share a brief example from a public STEAM event to demonstrate the ways in which this approach can foster reflection and
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group