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Case-Based Learning: Research Path

Overview

Navigate realistic research scenarios where your methodology decisions have consequences. This case-based approach helps you build research planning skills and learn from "failed" experiments without real-world costs.

Learning Objectives

How You Progress

Your research decisions are evaluated across five key dimensions:

  1. Validity: Controls for confounds, appropriate sample size
  2. Reliability: Measurement precision, replicability
  3. Efficiency: Resource use (time, budget, equipment)
  4. Safety/Ethics: Risk assessment, protocol compliance
  5. Impact: Ability to answer research question definitively

What You'll Achieve

You'll develop research planning skills with foresight about experimental consequences, pattern recognition for common pitfalls, ability to justify methodology choices, and resilience through learning from failed experimental paths.

Interactive Prototype

How to Use: You're the principal investigator planning a materials research study. Read the research scenario below, then make decisions at each critical choice point. Select the option that best balances validity, reliability, efficiency, safety, and impact. After each decision, you'll see the consequences of your choice. Complete all 5 decisions to receive your research quality rubric and expert feedback.

Research Scenario: Material Fatigue Study

You're investigating fatigue life of a new aluminum alloy for aerospace applications. Your goal is to determine how many load cycles the material can withstand before failure under different stress levels.

Budget: $50,000 | Timeline: 6 months | Deliverable: S-N curve (stress vs. cycles to failure)

Decision Path

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Decision 1: Sample Size & Test Points

How many specimens and stress levels should you test to build a reliable S-N curve?

🎉 Research Study Complete!

You've navigated all research decisions!

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Overall Research Quality