The basic unit of meaning on the Semantic Web is the RDF statement, or triple, which combines a distinct subject, predicate and object to make a definite assertion about the world. A set of triples constitutes a graph, to which they give a collective meaning. It is upon this simple foundation that the rich, complex knowledge structures of the Semantic Web are built. Yet the very expressiveness of RDF, by inviting comparison with real-world knowledge, highlights a fundamental shortcoming, in that RDF is limited to statements of absolute fact, independent of the context in which a statement is asserted. This is in stark contrast with the thoroughly context-sensitive nature of human thought. The model presented here provides a particularly simple means of contextualizing an RDF triple by associating it with related statements in the same graph. This approach, in combination with a notion of graph similarity, is sufficient to select only those statements from an RDF graph which are subjectively most relevant to the context of the requesting process.
We give a brief overview of some key features of WorldWide Telescope and its Ambassadors Program, and we describe two goals for expanding the program in the coming year: scaling up training efforts; and developing “plug and play” Visualization Lab modules that teach key Earth and Space Science concepts to students while emphasizing important scientific processes and skills. We discuss several different ways that members of the astronomy education and outreach community can incorporate WWT-based materials into their work.
We report results from an NSF-funded project to build, test, and research the impact of a WorldWide Telescope Visualization Lab (WWT Vizlab), meant to offer learners a deeper physical understanding of the causes of the Moon’s phases and eclipses. The Moon Phases VizLab is designed to promote accurate visualization of the complex, 3-dimensional Earth-Sun-Moon relationships required to understand the Moon’s phases, while also providing opportunities for middle school students to practice critical science skills, like using models, making predictions and observations, and linking them in evidence-based explanations. In the Moon Phases VizLab, students use both computer-based models and lamp + ball physical models. The VizLab emphasizes the use of different scales in models, why some models are to scale and some are not, and how choices we make in a model can sometimes inadvertently lead to misconceptions. For example, textbook images almost always depict the Earth and Moon as being vastly too close together, and this contributes to the common misconception that the Moon’s phases are caused by the Earth’s shadow. We tested the Moon Phases VizLab in two separate phases. In Phase 1 (fall 2012), we compared learning gains from the WorldWide Telescope (WWT) VizLab with a traditional 2-dimensional Moon phases simulator. Students in this study who used WWT had overall higher learning gains than students who used the traditional 2D simulator, and demonstrated greater enthusiasm for using the virtual model than students who used the 2D simulator. In Phase 2 (spring 2013), all students in the study used WWT for the virtual model, but we experimented with different sequencing of physical and virtual models in the classroom. We found that students who began the unit with higher prior knowledge of Moon phases (based on the pre-unit assessment) had overall higher learning gains when they used the virtual model first, followed by the physical model, while students who had lower prior knowledge benefited from using the physical model first, then the virtual model.