Signal Processing - July 2016 - 80
resulting automatically generated implementation used as
a basis for evaluation. Motivated by the goal of providing
detailed feedback to students, the scheduling algorithm
was also able to automatically analyze and reduce algebraic loops, forming an online implementation of the algorithm as shown in [16].
faculty and senior-level engineers working on projects at
well-known high-tech firms.
Impact on the MIT residential course
We have a very clear and strong sense of how MOOC content
has enhanced the residential experience and its impact for the
future. Although MOOC content by its nature is designed to
stand alone, in the residential context it becomes a very strong
Class by the numbers
multiplier on the in-class time that students have with the staff.
In the residential course, students were strongly encouraged to
Retention and engagement
preview the online content before coming to class, and the
In the spring 2015 run of 6.341x, the course began with
assumption during class time was that students had previewed
approximately 10,500 learners registered and closed with appthe videos and worked at least some of the online exercises. In
roximately 9,500 learners registered and 110 receiving certifithe context of a graduate-level course that carries an assumpcates. Early in the course, about 2,500 registrants were clearly
tion of a high level of maturity and commitment on the part of
active, with approximately 500 active at the close of the course.
students, we chose not to make previewing explicitly mandaPerhaps not surprisingly, the largest spikes and subsequent
tory, nor to have a graded mini-quiz at the beginning of each
drop offs in the number of registrants that were active coinin-class session. Furthermore, class sessions were not simply
cided with the three exams.
discussions or Q&A sessions. However, the level and pace of
the presentation was predicated on the assumption of previewDemographics
ing. The approximate experience was that about one-third of
The residential course 6.341 is taught once each academic
the class regularly previewed the topics, one-third sporadiyear at MIT, with typical end-of-semester enrollment of
cally or superficially did so, and about one30-40 (mostly) graduate students. With
third almost never did at all. Those who did
the acceptance rate of 2-3% in the MIT
Much in the same way,
uniformly (anecdotally) felt that it made a
EECS graduate program, it is reasonable to
the openness of online
significant difference. And whether or not
assume that the students in the residential
courses often causes
a student regularly previewed the content,
course have strong backgrounds and are
prospective learners
virtually all actively used the online conwell qualified. Attrition rates in 6.341 are
tent after in-class sessions.
typically on the order of 30% between the
to underestimate
Our conclusion is that the residential
first and last weeks of the semester.
the importance of
course
benefited enormously from the availIn the industry beta version of 6.341x,
prerequisites, which leads
ability of the rich online content and that stuthere were a total of approximately 170
to the low yield rates that
dents actively used it both before and after
registered students, with 36 completmost other instructors
the in-class interaction. The MOOC by itself
ing the course with a passing grade (i.e.,
experienced.
is no substitute for a well-taught residenperformance at the level of an A or B
tial course. However, it can be a significant
grade). In the spring 2015 open run of
enhancement to any residential course, and in our view it is a
the MOOC, the initial registrants represented a total of
strong substitute for any poorly taught residential course.
136 countries. Among those who successfully completed
the spring 2015 MOOC, the overwhelming majority were
those who joined from industry. Keeping in mind our goal
Feedback
of reaching a broader number of individuals than we were
Overall feedback about 6.341x was strongly positive, and perable to reach residentially at MIT, we were delighted that
haps the most common negative feedback was that the level of
while maintaining the same level of content depth, diffisophistication and time commitment required to take 6.341x was
culty, and sophistication, we were able in a single run of
higher than expected. However, for those who met the backthe course to impact the same number of students as would
ground prerequisites, this was viewed as an asset, commenting
be impacted residentially during approximately six-seven
that 6.341x stood apart from other MOOCs in this regard. Those
years of teaching at MIT. In addition, as further evidenced
students whose background was slightly weak but who actively
by the participant quotes and the modest percentage of parengaged with the forum generally found that the availability and
ticipants able to successfully complete the course, it was
encouragement of course staff and CTAs allowed them to brush
difficult and demanding in terms of time and background,
up on their weak spots and stay engaged with the course.
as would be expected with a course at the graduate level. It
As expressed by one of the students, "Right before the
was also especially encouraging that a significant percentcourse started, I thought I was well prepared for this course. After
age of those impacted by the MOOC were individuals who
all, I have a strong background in [signals and systems], and I am
do not traditionally constitute a major component of the
very familiar with digital signal processing. But after the first few
MIT EECS graduate-level student demographic; specifiweeks...I found the exercises and problem sets challenging....
cally, those completing 6.341x were primarily university
I almost gave up [were it not for] the helpful feedback from
80
IEEE Signal Processing Magazine
|
July 2016
|
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
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Signal Processing - July 2016 - 101
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Signal Processing - July 2016 - 103
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Signal Processing - July 2016 - Cover3
Signal Processing - July 2016 - Cover4
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