Theoretical
background |
Our focus on visualization is an attempt to promote students'
appropriation of the practices of scientists, thereby allowing students
to study topical problems of global change and the process whereby new scientific
knowledge emerges. Visualization is a good choice to provide this common
ground because it is (a) increasingly important to scientific practice,
(b) has powerful perceptual affordances that allow students to investigate
complex patterns through the use of visual patterns, (c) has powerful representational
affordances for investigating phenomena at various scales.
When students create and analyze visualizations they are using similar
tools and data sets as practicing scientists, thus leading them into the
scientific communities of practice. This participation can help students
realize that science is a dynamic field where a primary activity is the
design and analysis of theories, rather than the memorization of facts
and processes.
There are serious obstacles before students can effectively use visualization.
These obstacles need to be addressed through the design of material and
social supports. Specialized software can help ease the task of crafting
visualizations by extensive context for their creation, interpretation,
and critique. Project-enhanced learning contexts can promote their use
within meaning-making conversations, foster a community that creates scientific
knowledge and representational practices, and build bridges that connect
classroom-based communities with scientists and other professionals.
This approach was founded in the context of several NSF-EHR funded projects
at Northwestern University which have accumulated a significant body of
experience on using visualization for K-12 science learning. These projects
include Learning through Collaborative Visualization Project and the Supportive
Scientific Visualization Environments for Education Project.
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| Challenges |
Important challenges include:
- Forming distributed communities that link teachers and students to
one another and to scientists communities of practice
- Designing software architectures that ease the task of creating ³vertical
applications² that provide students with the context they need to understand
and use visualizations.
- Understanding how to combine studentsı use of visualization with other
representations, activities, and experiences. Especially, how should
visualization be combined with field studies? hands-on construction
of maps? analytical modeling exercises? structured curricula and their
accompanying textbooks, videos, and assignment sheets?
- Integrating visualizationıs visual patterns with modelingıs numeric
patterns so that the two methods complement one another. This is difficult
since visualization often provides complex data sets that show spatial
areas at high resolution and accuracy. In contrast, most educational
modeling tools use scalars to represent quantities and are only very
approximate. This means the inputs (observed data of visualizations)
and outputs (results of models) are not easily comparable. This gives
rise to difficult issues around helping students understand that the
results of the model are quite limited and fragile.
- Helping inservice and preservice teachers learn to use visualization
and modeling tools and data in the context of topical scientific problems
- Establishing a computational architecture whereby visualization and
modeling tools are available over the WWW so that teachers and students
need only use low-cost network computers
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