Virtual Solar System Project

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Virtual Solar System Project
The impact of 3-D Computational Modeling on
Student Understanding of Astronomical Concepts

• John A. Hansen
• Michael Barnett
• James G. MaKinster
• Indiana University
• Thomas Keating
• Boston College

NARST 2002, New Orleans
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Background Need for VSS course

• Computational Modeling Emergence
• The scientific process has been described as the
  process of constructing models for their
  predictive and conceptual value. (Gilbert, 1991)
  
• Computer models engage students (Stratford, 1996)
• Scientific models are used to argue points of
  public interest

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Background Astronomy Learning

• Students have intrinsic interest in astronomy
• Students have a number of alternative conceptions
  (Sneider Ohadi, 1998)
• Students have a difficult time learning astronomy
  concepts (e.g. Barnett Morran, in press)
• Challenge of understanding relationships between
  objects (Earth, Moon, etc)

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Research Question

• What astronomical concepts are supported by 3-D
  computational modeling support?
• Compared and contrasted student understanding of
  astronomical concepts who constructed 3-D
  computational models with students who
  experienced traditional lecture-based
  instruction.

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VSS Course Design

• Project-based (Blumenfeld, et al., 1991)
• Collaborative groups
• Constructing models of the Earth-Moon-Sun System
• Engage in inquiry process
• Students develop and answer their own questions
  about the solar system
• Originally designed for undergraduate astronomy
  courses

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Enabling Technology

• Students construct computer models using Virtual
  Reality software
• Students can post their models on the WWW
• Motivational element
• Students are able to shift their viewpoint from
  one object to another
• Look at Earth from Moons perspective

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VRML modeling software
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Study Context

• Interviewed xx VSS students (xx total)
• Interviewed xx traditional students (xx total)
• VSS course occurred during regular spring term
• Traditional course during regular (xx week)
  summer session

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Study Methods

• Pre-Post Interviews, convenient sample
• Rubric developed to evaluate the interview
  responses (Keating, Barnett, Barab, Hay, in
  press)
• Examination of student models
• Statistical tests (treat as ordinal data, John
  add a couple of points here)
• Inter-rater reliability goes here too

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Results Overall
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Results Question
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Results Question
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Results Question
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Discussion
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Implications
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Future Work and Remaining Questions