Instructor Insights

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Course Overview

This page focuses on the course 6.01 Introduction to Electrical Engineering and Computer Science I as it is typically taught at MIT. Professor Dennis Freeman, who has taught the course since its development, and Visiting Professor Sanjoy Mahajan, who has taught the course in recent semesters, share their insights about the pedagogy behind this core learning experience in EECS. The course was developed by Professors Hal Abelson, Leslie Kaelbling, Tomás Lozano-Peréz, and Jacob White, with substantial inputs from the EECS Curriculum Initiative Committee. 

Taught using substantial laboratory experiments with mobile robots, this course provides an integrated introduction to electrical engineering and computer science. Key issues in the design of engineered artifacts operating in the natural world are addressed, including measuring and modeling system behaviors; assessing errors in sensors and effectors; specifying tasks; designing solutions based on analytical and computational models; planning, executing, and evaluating experimental tests of performance; and refining models and designs. These issues are addressed in the context of computer programs, control systems, probabilistic inference problems, and circuits and transducers, which all play important roles in achieving robust operation of a large variety of engineered systems.

Course Outcomes

Course Goals for Students

  • Learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science.
  • Understand that making mathematical models of real systems can help in the design and analysis of those systems.
  • Practice making decisions about which aspects of the real world are important to the problem being solved and how to model them in ways that give insight into the problem.
  • Gain exposure to basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.

Possibilities for Further Study/Careers

This course prepares students to take 6.02 Introduction to EESC II: Digital Communication Systems, 6.002 Circuits and Electronics and 6.007 Electromagnetic Energy: From Motors to Lasers.

 

Instructor Insights

In the following pages, Professor Dennis Freeman and Visiting Professor Sanjoy Mahajan describe various aspects of how they teach 6.01 Introduction to Electrical Engineering and Computer Science I.

Learn more! In a video at the following Residential Digital Innovations page, Professor Freeman discusses task-centered learning as a pedagogical approach in 6.01 Introduction to Electrical Engineering and Computer Science I.

 

 

Curriculum Information

Prerequisites

6.01 has no formal pre-requisites. Students at MIT are expected to take 8.02 Physics II: Electricity and Magnetism as a co-requisite.

Requirements Satisfied

Offered

Every fall and spring semester

The Classroom

  • Tiered classroom with red tablet armchairs. Five sliding blackboards and a table are at the front of the classroom.

    Room 1 of 2 Click for next classroom.

    Lecture

    Lectures are typically held in a classroom that seats more than 300 students and is equipped with A/V equipment.

  • Classroom with 13 square tables visible. Four laptops are on the table closest to the viewer. Four black chairs on wheels are arranged around each table. A blackboard lines one wall.

    Click for previous classroom. Room 2 of 2

    Lab

    Software and design labs are held in a space with tables that can seat up to 8 students with laptops. There is enough space between the tables for robots to roam.

 

Assessment

The students' grades are based on the following activities:

The color used on the preceding chart which represents the percentage of the total grade contributed by software labs. 10% Software labs
The color used on the preceding chart which represents the percentage of the total grade contributed by design labs and interviews. 20% Design labs and interviews
The color used on the preceding chart which represents the percentage of the total grade contributed by additional exercises. 5% Additional exercises
The color used on the preceding chart which represents the percentage of the total grade contributed by homework assignments. 5% Homework assignments
The color used on the preceding chart which represents the percentage of the total grade contributed by quizzes and exams. 60% Quizzes and exams
 

Instructor Insights on Assessment

Student Information

Enrollment

Enrollment ranges from 250 to 400 students.

Breakdown by Year

Mostly freshmen and sophomores.

Breakdown by Major

About 35% EECS majors and 65% from other departments.

 

How Student Time Was Spent

During an average week, students were expected to spend 12.5 hours on the course, roughly divided as follows:

Lecture

2 hours per week
  • Typically meets 1 time per week for 1.5 hours per session; usually about 11 sessions total; mandatory attendance.
  • Interactive lectures
 

Software Lab

1.5 hours per week
  • Typically meets 1 time per week for 1.5 hours per session; usually about 13 sessions total; mandatory attendance.
  • Students develop software, and sometimes hardware, that they use in their design lab sessions.
 

Design Lab

3 hours per week
  • Typically meets 1 time per week for 2 hours per session; usually 14 sessions total; mandatory attendance.
  • Students build and work with mobile robots to apply their understanding of key concepts taught during the lectures and software labs.
 

Out of Class

6 hours per week
  • Online tutor exercises
  • Required readings
  • Course notes review
  • Exam preparation
 

Semester Breakdown

WEEK M T W Th F
1 No classes throughout MIT. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
2 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
3 No classes throughout MIT. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
4 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
5 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
6 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
7 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
8 No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT.
9 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
10 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
11 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
12 No classes throughout MIT. No classes throughout MIT. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
13 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
14 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. Office hours scheduled.
15 Lecture session scheduled; online exercises assigned. Software lab session scheduled. Office hours scheduled. Design lab session scheduled. No classes throughout MIT.
16 No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT.
Displays the color and pattern used on the preceding table to indicate dates when classes are not held at MIT. No classes throughout MIT
Displays the color used on the preceding table to indicate dates when lecture sessions are held. Lecture session
Displays the color used on the preceding table to indicate dates when students presentations are held. Design lab
Displays the symbol used on the preceding table to indicate dates when office hours are held. Office hours (an additional time, not displayed, is also offered during the weekends)
Displays the color used on the preceding table to indicate dates when no class session is scheduled. No class session scheduled
Displays the color used on the preceding table to indicate dates when software lab sessions are held. Software lab
Displays the symbol used on the preceding table to indicate dates when exams are held. Online exercises assigned
 

Course Team Roles

When offered in the spring semester, 6.01 Introduction to Electrical Engineering and Computer Science I enrolls about 400 students and the course team is as follows:

Faculty Members (typically 6 or 7)

  • Generally, the lead faculty member provides the lectures for all of the sections.
  • This faculty member may also facilitate the design and software labs for one section of students.
  • Other faculty members on the teaching team facilitate the design and software labs for the remaining sections.
  • If a section is particularly large (around 80 or 90 students), two faculty members will co-facilitate the labs. 

Graduate Teaching Assistants (typically 6)

  • Graduate Teaching Assistants help with teaching and assessment in the course; they also support students during labs.

Undergraduate Teaching Assistants (typically 5 or 6)

  • Undergraduate Teaching Assistants have previously taken the course; they support current students during labs.

Lab Assistants (typically 30)

  • Lab Assistants have taken the course in a previous semester; they support current students during labs.

Student Lab Assistants (typically 30)

  • Student Lab Assistants are currently taking the class, but are working ahead; they support other students as they complete the lab experiences. 

 

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