# Instructor Insights

Instructor Insights pages are part of the OCW Educator initiative, which seeks to enhance the value of OCW for educators.

## Course Overview

This page focuses on the course 16.90 Computational Methods in Aerospace Engineering as it was taught by Professors Karen Willcox and Qiqi Wang in Spring 2014.

This course provided an introduction to numerical methods and computational techniques arising in aerospace engineering. Applications were drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques covered included numerical integration of systems of ordinary differential equations; numerical discretization of partial differential equations; and probabilistic methods for quantifying the impact of variability. Specific emphasis was given to finite volume methods in fluid mechanics, and finite element methods in structural mechanics.

This course was taught using the Residential MITx platform.

## Course Outcomes

### Course Goals for Students

- Attain a conceptual understanding of computational methods commonly used for analysis and design of aerospace systems
- Achieve a working knowledge of computational methods, including experience implementing them in model problems drawn from aerospace engineering applications
- Possess a basic foundation in theoretical techniques to analyze the behavior of computational methods

## Instructor Insights

Because students came to class having already engaged with the course materials, we were able to use in-class time for recitation-style interactions. Instead of lecturing for the full session, we focused on talking through the difficult parts of the theory and methods they had read about before class. Flipping the classroom also created opportunities for problem-solving in class.

— Karen Willcox

Below, Professor Karen Willcox describes various aspects of how she taught 16.90 Computational Methods in Aerospace Engineering.

- Flipping the Classroom
- Mapping Measurable Outcomes
- Assessing Students through Oral Exams
- Reflecting on the Programming Projects
- Co-Teaching the Course

## Curriculum Information

### Prerequisites

- 16.004 Unified Engineering or permission of the instructor
- Concurrent enrollment in 16.09 Statistics and Probability or 6.041 Probabilistic Systems Analysis

### Requirements Satisfied

16.90 can be applied towards a Bachelor of Science in Aerospace Engineering, but is not required.

### Offered

Every spring semester

## The Classroom

- ### Lecture

  This lecture-style classroom has a seating capacity of 48. The room can be darkened for viewing videos, and has an LCD video projector.

## Assessment

### Grade Breakdown

The students' grades were based on the following activities:

12% Reading questions and problem sets
36% Projects
25% Midterm exam
25% Final exam
2% Class participation

### Instructor Insights on Assessment

Professor Karen Willcox shares her insights about assessing students through oral exams.

## Student Information

### Breakdown by Year

Mostly juniors and seniors

### Breakdown by Major

Mostly aeronautics and astronautics majors

## How Student Time Was Spent

During an average week, students were expected to spend 12 hours on the course, roughly divided as follows:

## In Class

3 hours per week

- Course met 2 times a week for 1.5 hours per session; 25 sessions total.
- WebEx broadcasting of class sessions allowed students time away from campus to participate in engineering competitions or presenting at conferences.
- Sessions included concept questions, small group exercises, and project work.

## Out of Class

9 hours per week

- Online readings that included multiple choice, true/false, and short answer questions
- Problem sets
- Three programming projects
- Preparation for oral mid-term and final exams

## Semester Breakdown

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No classes throughout MIT
Class session
Reading/homework due
No class session scheduled
Oral exam