Page 131 - Getting the Picture Modeling and Simulation in Secondary Computer Science Education

Students’ Understanding and Difficulties
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Structured walkthrough Review Consultation of domain experts Delphi test Turing test
Observe outcomes
Discuss the model
With others
Validating
Modelers themselves
Reflect
Extreme condition test Degenerate tests
Plausibility Credibility
Generate outcomes
Parameter variability – sensitivity analysis
Accuracy Satisfaction
Animation
Trace
Operational graphics Performance measures
Construct the model
Reasoning
Research Abstraction
Test the model
Comparison to other models Comparison to real data
Figure 13: Coding categories
Interpret outcomes
Checking input - output consistency
Stress test
Techniques to interpret data
Event validity
Approaches to data interpretation
Objectively Subjectively
for example comparizon using statistical tests
Data relationship correctness
Checking consistency with previously verified theories
Historical data validation Predictive validation