Carnegie Mellon University

Eberly Center

Teaching Excellence & Educational Innovation

Learning Objectives

In writing your own course-level learning objectives, consider the following questions:

  • What should my students be able to do/know after completing my course? Note: be sure to include action-oriented verbs that make learning objectives more explicit and observable.
  • Within my course, how will I measure (e.g., assessments) whether or not students are achieving the learning objectives I’ve written?
  • How do these learning objectives relate to students’ likely prior knowledge plus the amount of practice and feedback they will get during the course?

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In this course you will learn to apply the principles of chemical kinetics to the design of reactors.  By the end of the semester, you should be able to:
  • Choose a reactor and determine its size for a given application.
  • Analyze kinetic data and obtain rate laws.
  • Work with mass and energy balances in the design of non-isothermal reactors.

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This course is intended to allow students to synthesize technical knowledge and design intention regarding issues of site design and construction. Students should be able to:

  • Identify multiple ways of relating to site in precedents and their colleagues' work, generate their own alternatives, and synthesize them into a cohesive project.
  • Demonstrate building construction, structural design, and architectural composition gained in prior semesters’ courses.
  • Demonstrate an ongoing exploration of the details of occupancy.
  • Collaborate in a team to generate, evaluate and document design decisions.
  • Show evidence of a consistent exploration of alternatives.

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When you have successfully completed this course, you should be able to:

  • Analyze a business situation to determine information management need.
  • Design a database to address those needs.
  • Write SQL queries to retrieve information from a relational database.

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Students should be able to design an experimental study, carry out an appropriate statistical analysis of the data, and properly interpret and communicate the analyses.

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  • Solve problems using matrix techniques and algorithms.
  • Recognize and recall major linear algebraic definitions and theorems.
  • Develop short but rigorous proofs of true mathematical statements and construct counter-examples for false statements.
  • Apply major linear algebraic theorems to prove other results.

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