Community Planning for Climate Change: Visible Thinking Tools Facilitate Shared Understanding

An engagement project examined the effectiveness of the visible thinking tools of concept mapping and influence diagramming to facilitate community planning for climate change through a series of workshops. The workshops were developed in coordination with a local nonprofit as part of a strategy of communicating about climate risks. Guided by university engagement faculty, workshop participants thoughtfully identified and mapped how specific risks associated with climate change may affect their rural coastal community, what could be done to address each risk, and who was responsible for taking action. Post-workshop interviews and surveys revealed that participants recognized the civic importance of facilitating dialogue on the contended issue of climate change and that visible thinking tools were beneficial towards developing understanding and consensus. Through the project, the community members and university personnel learned about local climate change concerns and some effective means for future collaboration, and the community set initial action priorities

Teacher perceptions of training and pedagogical value of cross-reality and sensor data from smart buildings

This paper discusses elementary, and secondary (K-12) teachers’ perceptions of cross-reality (XR) tools for data visualization and use of sensor data from the built environment in classroom curricula. Our objective was to explore the use of sensor-informed XR in the built environment and civil engineering (BECE) field to support K-12 science, technology, engineering, and mathematics (STEM) experiential learning and foster BECE-related career awareness. We conducted surveys and informal questionnaires with 33 primary and secondary teachers attending an annual two-day university-based teacher professional development workshop as part of a statewide STEM afterschool program serving students in rural communities. We assessed teachers’ familiarity with, knowledge about, and appraisal of using cross-reality platforms and sensor data in classrooms and after school curricula. Findings show that, while all teachers reported relatively high interest in learning about sensor applications and innovative interactive techniques, middle school teachers in particular were most likely to see value in using these applications for teaching and learning. Implications for teacher professional development are discussed

Detection Of KOI-13.01 Using The Photometric Orbit

We use the KOI-13 transiting star-planet system as a test case for the recently developed BEER algorithm (Faigler & Mazeh 2011), aimed at identifying non-transiting low-mass companions by detecting the photometric variability induced by the companion along its orbit. Such photometric variability is generated by three mechanisms, including the beaming effect, tidal ellipsoidal distortion, and reflection/heating. We use data from three Kepler quarters, from the first year of the mission, while ignoring measurements within the transit and occultation, and show that the planet's ephemeris is clearly detected. We fit for the amplitude of each of the three effects and use the beaming effect amplitude to estimate the planet's minimum mass, which results in M_p sin i = 9.2 +/- 1.1 M_J (assuming the host star parameters derived by Szabo et al. 2011). Our results show that non-transiting star-planet systems similar to KOI-13.01 can be detected in Kepler data, including a measurement of the orbital ephemeris and the planet's minimum mass. Moreover, we derive a realistic estimate of the amplitudes uncertainties, and use it to show that data obtained during the entire lifetime of the Kepler mission, of 3.5 years, will allow detecting non-transiting close-in low-mass companions orbiting bright stars, down to the few Jupiter mass level. Data from the Kepler Extended Mission, if funded by NASA, will further improve the detection capabilities.Comment: Accepted to AJ on October 4, 2011. Kepler Q5 Long Cadence data will become publicly available on MAST by October 23. Comments welcome (V2: minor changes, to reflect proof corrections

The Promise and Realities of the Use of Cyber Technologies for Promoting Research in Public STEM Museum Experiences

Cyberlab at OSU Final Report.A seven-year effort funded by the United States’ National Science Foundation and the Oregon Sea Grant College Program sought to identify and deploy in a public STEM museum setting a suite of digital tools for collecting and supporting analysis of data on the use of the setting in near real time and as evidence for in situ learning. In addition to full-museum camera coverage and data collection, five exhibit-based research platforms were developed to allow for collection of linked video, audio, and digital input (keystroke, touch screen manipulation) data at particular locations in the museum. A further effort explored the use of social media data mining tools as well as apps for research on how learners create continuity across STEM learning experiences distributed temporally and geographically. Returns on investment for research on informal learning were proven to be high with signifiant gains for researchers working with the museum and for building research partnerships with other museums and informal STEM learning environments (e.g., Maker Faires, public exhibits, tourism in marine environments), but return on investment for museum operations and programmatic advancement were relatively minor. While the project proved that a public museum can successfully employ current video-based, cyber-linked technologies to document and study learning outside of a laboratory setting, it also demonstrated that such activity is most likely beyond the budgetary and information technology capacity of most public institutions. However, the project also piloted and provided proof of concept for smaller, mobile efforts using many of the same technologies and tools in scaled-down but efficient research and evaluation efforts.Keywords: Cyberlearning; Informal Learning Environments; STEM; Video-based Researc

Evolving interest and sense of self in an environmental citizen science program

Citizen science is a growing phenomenon across many branches of environmental science facilitating both increased science literacy and the collection of highly rigorous, longitudinal data. Understanding the motivations of adults to join and remain active in citizen science programs is important as the diversity and abundance of opportunities for public participation in science grow. We conducted a mixed-methods study of newly recruited and “seasoned” (1 year plus) participants in the Coastal Observation and Seabird Survey Team, a hands-on, environmental citizen science program focused on adult coastal residents, to explore the degree to which engagement, measured as time in the program, influenced motivation. We used constructs of functionalism, person-object theory of interest, and activity theoretic approaches to situational identity to deconstruct motivation into three interacting components: objects of interest, actions directed toward those objects, and situated senses of self. Newly recruited participants came with a strong interest in being outside on the beach and learning about birds and saw themselves as data collectors defined in part by their birding and degree/job-based credentials and their social relationships. By contrast, seasoned participants aligned their interests and situational identity more directly with the program, calling out the importance of program data and results, elevating science-based actions such as monitoring over learning, intensifying their desire to contribute to science, subjugating individual attributes in favor of their science identity, and increasing their sense of self-worth attached to the project. Our results suggest that hands-on, environmental citizen science programs focused on adults should shape their data collector roles and projects around context-specific motivations including senses of place and biodiversity, support both the altruistic and self-interest needs of participants, and combine rigorous science experience with social interaction

Transit Timing Observations from Kepler: VI. Potentially interesting candidate systems from Fourier-based statistical tests

We analyze the deviations of transit times from a linear ephemeris for the Kepler Objects of Interest (KOI) through Quarter six (Q6) of science data. We conduct two statistical tests for all KOIs and a related statistical test for all pairs of KOIs in multi-transiting systems. These tests identify several systems which show potentially interesting transit timing variations (TTVs). Strong TTV systems have been valuable for the confirmation of planets and their mass measurements. Many of the systems identified in this study should prove fruitful for detailed TTV studies.Comment: 32 pages, 6 of text and one long table, Accepted to Ap

Kepler Data Validation IITransit Model Fitting and Multiple-Planet Search

This paper discusses the transit model-fitting and multiple-planet search algorithms and performance of the Kepler Science Data Processing Pipeline, developed by the Kepler Science Operations Center (SOC). Threshold crossing events (TCEs), which are transit candidate events, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the data validation (DV) component. The transit model is used in DV to fit TCEs to characterize planetary candidates and to derive parameters that are used in various diagnostic tests to classify them. After the signature associated with the TCE is removed from the light curve of the target star, the residual light curve goes through TPS again to search for additional TCEs. The iterative process of transit model fitting and multiple-planet search continues until no TCE is generated from the residual light curve or an upper limit is reached. The transit model-fitting and multiple-planet search performance of the final release (9.3, 2016January) of the pipeline is demonstrated with the results of the processing of four years (17 quarters) of flight data from the primary Kepler Mission. The transit model-fitting results are accessible from the NASA Exoplanet Archive. The final version of the SOC codebase is available through GitHub

Reframing Engagement Methods for Climate Change Adaptation

Climate change poses known and unknown risks for coastal communities and also challenges for university faculty and local government staff who communicate about climate sciences. Conceived as a way to move beyond traditional models of science communication, this project involved public and private decision makers in specific at-risk communities in Oregon (U.S. Pacific coast) and Maine (Atlantic coast). Both state projects sought to move behavior toward decisive action that results in coastal communities that are more resilient to climate variability at all scales. To promote engagement between project staffs and publics, a dialogic model of communication was advanced, beginning with interviews and focus groups which in turn shaped further engagement through workshops and targeted video products. This means of communication led to a deeper understanding of participants’ knowledge, beliefs, perceptions, values, and barriers to action related to climate change and its effects. Coinciding with this, project participant evaluations in both Oregon and Maine indicate that the workshops and videos were successful at informing them on this complex issue; and in both states, project participation led to action outcomes. We believe that applied elsewhere our multi-faceted and adaptive approach will garner similar results, provided sufficient dedicated staffing and attention to methods

Terrestrial Planet Occurrence Rates for the Kepler GK Dwarf Sample

We measure planet occurrence rates using the planet candidates discovered by the Q1-Q16 Kepler pipeline search. This study examines planet occurrence rates for the Kepler GK dwarf target sample for planet radii, 0.75<Rp<2.5 Rearth, and orbital periods, 50<Porb<300 days, with an emphasis on a thorough exploration and identification of the most important sources of systematic uncertainties. Integrating over this parameter space, we measure an occurrence rate of F=0.77 planets per star, with an allowed range of 0.3<F<1.9. The allowed range takes into account both statistical and systematic uncertainties, and values of F beyond the allowed range are significantly in disagreement with our analysis. We generally find higher planet occurrence rates and a steeper increase in planet occurrence rates towards small planets than previous studies of the Kepler GK dwarf sample. Through extrapolation, we find that the one year orbital period terrestrial planet occurrence rate, zeta_1=0.1, with an allowed range of 0.01<zeta_1<2, where zeta_1 is defined as the number of planets per star within 20% of the Rp and Porb of Earth. For G dwarf hosts, the zeta_1 parameter space is a subset of the larger eta_earth parameter space, thus zeta_1 places a lower limit on eta_earth for G dwarf hosts. From our analysis, we identify the leading sources of systematics impacting Kepler occurrence rate determinations as: reliability of the planet candidate sample, planet radii, pipeline completeness, and stellar parameters.Comment: 19 Pages, 17 Figures, Submitted ApJ. Python source to support Kepler pipeline completeness estimates available at http://github.com/christopherburke/KeplerPORTs