How can learners engage in constructing, applying and refining increasingly sophisticated scientific knowledge?

How can learners engage in constructing, applying and refining increasingly sophisticated scientific knowledge?
This question includes K-12 students, science educators, pre-service science educators, and citizen swcientists worldwide.

Various topics should be addressed to understand this question:
Scientific Argumentation and Construction
Scientific Modeling
Making sense of argumentation and explanation
Reasoning across ontologically distinct levels
Learning and teaching
Authentic learner practices
observational investigation
theory articulation

Iris Tabak describes a "disciplinary stance" to foster pragmatic understanding and help novices manage real world complexity in conducting science investigations.

Quotes from Tabak regarding disciplinary stance:
the general strategy of
making comparisons to look for changes and relationships, but we used the biologyspecific
form of the strategy by making comparisons across time in the predator of
the organism of focus. The decision to make this particular comparison out of the
many possible comparisons would be an obvious choice to an audience of biologists,
as would be the implied knowledge claims.

Goodwin (1995) noted that he, as an
outsider to the community of oceanographers, could not detect features of interest
to the oceanographers. He notes that in order to attend to these features one must
be equipped with the “interpretive structures that locate particular phenomena as
relevant and interesting,” which are derived from, and honed through membership
in a community of practitioners. He calls this type of “insider” knowledge
Professional Vision (Goodwin 1994), an idea very similar to what we refer to here
as a disciplinary stance.

(i.e., Chi, Feltovich, and
Glaser 1981; Larkin 1983), Greeno (1983) argues that expert problem solving includes
the availability of domain-dependent conceptual entities as arguments for
general methods of reasoning. In a study conducted by Schauble and colleagues
(1991), students who had more knowledge of electric circuitry, as well as more sophisticated
investigation strategies, were better able to uncover rules governing the
performance of electrical circuits. Studies of both experts and successful novices
(Klahr, Fay, and Dunbar 1993; Schauble 1990, 1996) provide converging evidence
that effective inquiry is characterized by an integration of disciplinary knowledge
and investigation skills.

Further learning technologies design:

1.Learning technologies are key in presenting students with rich problems and
engaging them in critical data analysis and synthesis (Bell, Davis, and Linn 1995;
Jackson, Stratford, Krajcik, and Soloway 1994; Snir, Smith, and Grosslight 1995;
White and Frederiksen 1995).
2.Learning technologies can import into the classroom
inquiry-contexts, which otherwise would not be available to students. For
example, they can provide real time dynamic data (e.g., Gomez, Fishman, and Pea
1998; Songer 1996),
3.provide observations of data from distant sites (e.g., Bell et al.
1995; Tabak et al. 1996),
4. make normally invisible processes visible (e.g., White
1993).
5.Learning technologies can engage students in scientific analyses that might
otherwise be too difficult for them, by providing simplified versions of scientific
tools (e.g., Edelson, Gordin, and Pea 1997; Jackson et al. 1994).
6.Technological tools
can offer a means for viewing, filtering, organizing, and labeling information so
that they create a balance between furnishing students with a sophisticated dataset
and helping them manage this complexity (Blumenfeld et al. 1991; Loh 1997;
Tabak and Reiser 1997).
7. software prompts can encourage students to
take actions that they are not inclined to take spontaneously, such as reflecting on
how a collection of data can warrant a specific argument (Davis 1996; Loh et al.
1997; Sandoval 2003, 2004).
8. DSSS is a form of software-realized scaffolding
(Guzdial 1994), that is, software supports that enable a novice to accomplish tasks
that he or she would not be able to accomplish independently.

A large piece of science learning and the ability to engage in discourse involves the ability to question appropriately, focus on questions, and utilize scientific reasoning and rules of evidence in making valid assumptions, conclusions, and theories.  These are shared knowledge in a scientific community.  However, knowledge within each sub-community in terms of vocabulary and ways of reporting, etc. may diverge. 

References
Smith, B. K., & Reiser, B. J. (2005). Explaining behavior through observational investigation and theory articulation. Journal of the Learning Sciences: 14(3), 315-360.
Reiser, Brian J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. Journal of the Learning Sciences: 13(3), 273-304.


Tabak, I., & Reiser, B. J. (2008). Software-realized inquiry support for cultivating a disciplinary stance. Pragmatics and Cognition: 307-355.
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Jackson, S.L., Stratford, S.J., Krajcik, J., and Soloway, E. 1994. “Making dynamic modeling accessible to precollege science students”. Interactive Learning Environments 4: 233–257.

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