Signal Processing - July 2016 - 67

Table 2. Attendance figures on Coursera for the EPFL DSP class,
with "Yield" representing passed/registered in percentage.
Edition
First
Second
Third
Fourth
Fifth

■■

■■

Date
Feb. 2013
Oct. 2013
May 2014
Jan. 2015
Oct. 2015

Registered
48,000
35,000
19,000
25,000
16,000

Active
24,000
20,000
10,000
17,000
7,500

Passed
1,500
1,000
280
450
360

Yield
3.1
2.9
1.5
1.8
2.2

A peak of activity at the end of the class (April 2015)
occurs, but only in terms of visits. Apparently, in online
classes as in real classes, in the end students try to cram
(and then give up).
Interestingly enough, visits do not taper off to zero after
the end of the class (April 2015 in Figure 2) but remain at
the same level until the next offering of the course (homework submissions and forum participation obviously do
stop). This strongly indicates that a MOOC model based
on self-paced learning certainly has its place alongside
monitored editions of the class.

Demographics
(Note: Although the following data refer to the fourth edition
of the class, no significant differences have been remarked
in the latest edition.) The student population showed a pronounced gender imbalance, with an 87% male component; a
majority (42%) was in the 25-34 age range; and approximately
half of the attendees were full-time employees and 37% fulltime students. Overall, 31% held an M.S. degree and 34% a
bachelor's degree, which suggests many take online classes of
this kind more as a sort of refresher. The geographical distribution of students sees the United States at the top with 20%,
followed by India (17%) and China (8%). As a whole, Asia
leads with 38% of enrollments, followed by Europe (26%) and
North America (25%).

Impact on the EPFL residential course

common commentary in the exit questionnaire), but the rigor
was almost unanimously appreciated by the students who
made it to the end of the class. In general, the more senior and
more educated students tended to ask for more material and a
longer, in-depth class. Younger participants advocated splitting
the class into shorter independent units. We certainly cannot
claim to have pleased everyone, and we had our share of constructive and nonconstructive criticism. But the real privilege,
as teachers, is the wealth and diversity of direct feedback that a
MOOC provides. Considering that approximately 70 students
per year attend the residential class, we can now sift through a
century's worth of class evaluations!

Rice University's Discrete-Time Signals
and Systems on edX
Overview and goals
Discrete-Time Signals and Systems (301x) is a rigorous mathematical introduction to signal processing modeled on 50%
of the Rice University course ELE301, Signal and Systems, a
core undergraduate class taken by all electrical and computer
engineering (ECE) majors, typically in the junior year. Rather
than following the classical approach to teaching discrete-time
signals and systems as discretized versions of continuous-time
signals and circuits, the course approaches discrete-time signals and systems from first principles. The key overarching
theme is the importance of linear algebraic concepts in signal
processing: vector spaces, signals as vectors, linear systems
as matrices/operators, linear time-invariant (LTI) systems as
Toeplitz/circulant matrices, and the Fourier transform from
the eigendecomposition of these LTI matrices. The course,
which also covers the z transform and filter analysis and
design, teaches students to analyze discrete-time signals and
systems in both the time and frequency domains. Students
continuously apply these concepts in interactive MATLAB
programming exercises. The course has been taught twice on
edX: the first edition in spring 2014 as a ten-week course [19]
and the second edition in spring 2015 as two five-week minicourses [14], [20].

Initially, we thought about using MOOC recorded material to
flip the classroom on campus. We attempted this during the
first run of the online class, which coincided with a scheduled
offering of the residential course. Students were instructed to
watch the video lectures at home and prepare for Q&A sessions during the nominal lecture hours, but the experiment
was unsuccessful. Students expressed an unmitigated dislike
toward the absence of standard lecture time and considered
their learning experience to be incomplete. We therefore
decided not to repeat the format, and now we simply recommend that students enroll in the online classes and use the
material to review and catch up on the standard lectures.

10,000
8,000
6,000
4,000
2,000
0
February

Feedback
Overall feedback from the online students was decidedly
positive for every edition. The consensus held that the class
was hard ("harder than I anticipated" was perhaps the most

March

April

May

FIGURE 2. Engagement data for the fourth edition (19 January 2015-
6 April 2015) of the EPFL course: visits to the course page (black), video
views (blue), homework submission (red), and forum browsing (yellow).

IEEE Signal Processing Magazine

|

July 2016

|

67



Table of Contents for the Digital Edition of Signal Processing - July 2016

Signal Processing - July 2016 - Cover1
Signal Processing - July 2016 - Cover2
Signal Processing - July 2016 - 1
Signal Processing - July 2016 - 2
Signal Processing - July 2016 - 3
Signal Processing - July 2016 - 4
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Signal Processing - July 2016 - 97
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Signal Processing - July 2016 - 99
Signal Processing - July 2016 - 100
Signal Processing - July 2016 - 101
Signal Processing - July 2016 - 102
Signal Processing - July 2016 - 103
Signal Processing - July 2016 - 104
Signal Processing - July 2016 - Cover3
Signal Processing - July 2016 - Cover4
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