Program Description

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EI is an exciting, hands-on summer course for high school students interested in engineering. This program is offered at the JHU Homewood campus in Baltimore, MD and at other sites in California, the District of Columbia, Pennsylvania and Washington.  A residential experience is available at both the JHU Homewood campus and at the California State University – Fullerton campus.

Over four or five weeks (depending upon the site) students complete lab activities in computer engineering, chemical engineering, electrical engineering, material science, civil engineering, robotics, and mechanical engineering. They also prepare a presentation in response to a Request for Proposal, learn about engineering economics, write a research paper, take weekly quizzes, and complete a comprehensive take-home final exam.

Students who earn an A or B grade in the course are awarded 3 credits from Johns Hopkins University.

The objective of this course is to introduce engineering ideas, thoughts, and problem-solving to potential engineering students and help them answer the questions: Is engineering for me? If so, what field? Team-time-cost management projects, multi-parameter problems and, problems without single correct solutions are emphasized. The course is intended to expose students to the framework within which engineers typically operate. Although the course is “field independent”, it does introduce students to problems and ideas from specific engineering disciplines.

What is learning?

Synthesizing theory and knowledge in order to solve problems: Not just theory out of context--the “what”. But also the “why”, “when”, and under what conditions the theory may be invoked tosolve a problem. Learning is also discovering what doesn’t work.

". . . a failed structure provides a counterexample to a hypothesis and shows us incontrovertibly what cannot be done, while a structure that stands without incident often conceals whatever lessons or caveats it might hold for the next generation of engineers."

----------- Henri Petroski, To Engineer Is Human

  • Contextual--give reason to understand a theory or calculation
  • Problems “out of the chapter”
  • Assignments that involve efficiency, cost, functionality, accuracy
  • Back-of-the-envelope problems: “Fermi questions”
  • Assignments without single, deducible, correct answers
  • Taking data and deducing the underlying physical principles
  • Hands on--laboratories, virtual laboratories, projects

Topics are introduced by posing a problem

  • Suppose we need to devise a robot that moves toward light. . .
  • Suppose we want to separate fat from gravy for a Thanksgiving dinner. . .
  • Suppose we want to bid on a tree as material for a toothpick factory. . .
  • Suppose we need a bridge to support the weight of a car. . .
  • Suppose we would like to deduce the period of a pendulum. . .

Asking “Why”

  • Why do we want to do this?
  • Why do we care?
  • Why digital instead of analog?
  • Why binary instead of decimal?

 Asking “Why not?”

  • Why not use Elmer’s glue (or a glue gun) on spaghetti bridges?
  • Why not measure the weight of a single penny on a postal scale?
  • Why not use titanium to build bridges?

Asking “what?”

  • What tools/principles can we use on this problem?
    • finding forces in members attached to a pin joint on a stationary structure
    • separating alcohol from water
    • improving the accuracy of a measurement
    • What are the conditions under which XXXX will/will not work?
      • Can we have a stone lintel that spans 20 feet?
      • When will a model yield characteristics of its full-scale counterpart?
      • What does it mean if the mass entering a control volume does not equal the mass leaving a control volume

Giving examples and counter examples

Giving reasons for each step in solving a problem (the solution is less important than the strategy for approaching it)

Posing sub-problems, i.e., “What if. . .?”

Relating to other fields

  • mass conservation vs. Kirchhoff’s laws
  • heat flow vs. electron flow vs. particle diffusion (gradient transport)
  • Presenting theories/calculations without context
  • Using ambiguous or loosely defined terms
  • Giving “plug and chug” problems (well, maybe occasionally)
  • Presenting topics without placing them within a “bigger picture”
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