In October 2017, the PBS NewsHour team produced a week and a half of opioid-related content, including several online explainers, which presented the opportunity for a natural experiment for the Experiments in Transmedia project.
Knology (formerly New Knowledge Organization Ltd.) conducted a two-wave research study to advance understanding of the youth audience’s knowledge and news consumption on the topic.
The first wave of the study, conducted in September 2017, provides a baseline. The content aired in October 2017, and the second wave of the study, conducted in November 2017, asked a
The summative evaluation documents and articulates what SCIENCES has improved or changed, and in what ways. The final design of the summative evaluation was based on findings from the front-end and formative evaluations, including using participatory evaluation techniques to engage community members in discussing their experience with the programs and assessment of community needs and assets at the close of the project.
The goal of the summative evaluation was to address discrete program impacts in the context of the project, as well as the cross-program impact of providing a thematically
The September 6 -7 COMPASS Conference held at the Exploratorium had 19 speakers and 80 attendees. The conference purpose was to take a focused look at indoor location aware mobile (ILAM) technology and how it was used in science centers and other museums.
The three primary project goals were:
1) Form an integrated vision by consolidating expertise from disparate disciplines connected to indoor location aware mobile (ILAM) tech development;
2) transform visitor mobile tools going beyond basic digital content to more innovative forms of interaction and personalization; and,
3) open
This project promises to help professionalize the field of informal science learning. In general, professional fields that developed guidance for growth and excellence tend to attract and retain professionals more successfully than those who do not, in part because expectations are transparent. Our analyses included a variety of potential target audiences who engaged with the Framework at differing depths. In addition to testing the potential efficacy of the Preliminary Framework as a guide for professionalizing ISL, reviewers helped to build the case for the value of professional development
A Teen Science Café is an out-of-school program that brings together teens and science professionals to engage in discussion and activities related to the scientist’s work. The Cafés are highly interactive, incorporating hands-on activities and discussion with scientists; each is co-organized by an adult and a group of Teen Leaders. The model was developed and refined in several different locations in New Mexico between 2008 and 2010.
This pilot study took advantage of the 10-year history of Café Sci NM, and sought to answer the question: What are the long-term influences of participation
A Teen Science Café is an out-of-school program in which teens and STEM experts engage in conversation and activities to explore a topic related to the STEM professional’s expertise. Teen Science Cafés are independently run and organized at more than 100 sites nationwide – from museums to libraries to aquariums. Prior evaluation of the Teen Science Café model has demonstrated a range of impacts achieved with youth participants, but relatively little research has focused on the experience of the scientist-presenters.
This report presents findings of a sequential mixed-methods study that
The independent evaluation firm, Knight Williams, Inc., developed a two-part post-program survey to gather information about the Year 1 SciGirls CONNECT2 outreach programs conducted by 14 partner organizations. The evaluation aimed for one educator from each organization to complete Part 1 of the survey, which consisted of program reporting questions. In all, one educator from 13 partner organizations completed Part 1, for a response rate of 93%. Part 2 of the survey asked for program reflections, with a focus on perceived program goals, impacts, highlights, and challenges. Given the
The independent evaluation firm Knight Williams, Inc. administered an online survey to educators from 16 SciGirls CONNECT2 partner organizations to gather information about their anticipated use of, reflections on, and recommendations relating to the draft updated SciGirls Strategies. The evaluation aimed for two educators from each partner organization – specifically the program leader and one educator who was familiar with the original SciGirls Seven strategies – to complete the survey about the draft updated strategies after they were shared by TPT in March 2018 via an online webinar and a
The independent evaluation firm, Knight Williams, Inc., administered an online survey and conducted follow-up interviews with educators from 14 SciGirls CONNECT2 partner organizations to gather information about their use of, reflections on, and recommendations relating to the SciGirls Seven strategies. The evaluation aimed for two educators from each partner organization – specifically the program leader and one educator who was familiar with the SciGirls Seven – to share reflections on the strategies after they completed their Year 1 programs. In all, 24 educators from 13 partners completed
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
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
This study examines the relative efficacy of citizen science recruitment messages appealing to four motivations that were derived from previous research on motives for participation in citizen-science projects. We report on an experiment (N=36,513) that compared the response to email messages designed to appeal to these four motives for participation. We found that the messages appealing to the possibility of contributing to science and learning about science attracted more attention than did one about helping scientists but that one about helping scientists generated more initial
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TEAM MEMBERS:
Tae Kyoung LeeKevin CrowstonMahboobeh HarandiCarsten ØsterlundGrant Miller