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Abstract:
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Statistics courses have been developed where simulation methods are a major part of course content, changing numerous aspects of the student experience, including how students solve statistical tasks. Eight students from an introductory statistics course that taught only simulation-based inference methods engaged in guided task-based interviews to explore problem-solving cycles in students' approaches to the tasks. Participants attempted to solve four tasks from multiple contexts using randomization tests and bootstrapping procedures. Interview transcripts were qualitatively coded for the problem-solving phases that emerged. Results suggest that statistical problem-solving with simulation-methods may require students to navigate a cycle of phases unique to the application of simulation-methods, which corroborates with and expands upon current models of statistical problem-solving. A typical cycle arose composed of the following phases: Plan, Model, Simulate, Evaluate, Conclusions, and Context. Examples will be presented to highlight notable variations observed in participant success, the navigation of phases, and the complexity of cycles across participants and tasks.
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