I believe on-line learning can work.
Why? Three reasons:
First, a 'dirty little secret' of the US software
industry is how much of the learning from the
beginning of electronic computing to the present has
been just from individuals teaching themselves from
books, e.g., K&R on C, Lippman on C++, Ullman on
database, Sedgewick on algorithms, and on-line,
e.g., Microsoft's MSDN site, StackOverflow, etc.,
essentially independently without courses, lectures,
problem sessions, credits, homework, tests, etc.
Or since just K&R, ..., StackOverflow, etc. have
been responsible for so much learning so far, then
'the bar is low' and on-line courses should do even
better.
Second, in my experience in technical subjects, pure
and applied math, mathematical physics, some topics
in electronic engineering, e.g., surrounding the
fast Fourier transform (FFT), and software, with a
class or not, nearly all the learning (in my case)
took place from study, alone, in a quiet room, from
good materials just on paper. My 'educated guess'
is that on-line learning can't replace such learning
but can help stimulate more of it.
Third, for a researcher in applied math and
software, and also likely some other fields, one of
the main 'work items' is to take recent books and
papers and work through them much as working through
advanced course materials in such subjects.
Back to my case, in the fields I worked hardest on
and did the best in, math, physics, and software,
starting in the ninth grade, through my Ph.D., and
in my career to the present, I did nearly all the
work with relatively little contribution from
teachers. E.g., in plane geometry my teacher was
the most offensive person I've ever known in
education, and I slept in her class and refused to
admit doing her assigned homework. Instead, I
worked every non-trivial problem in the book
including the more advanced supplementary problems
in the back where she never made any assignments.
Then, after working all those problems, no wonder,
on the state test in the subject, I did fine: I
came in second best in the class; the guy who beat
me also beat me by a few points on the Math SAT --
we were 1, 2 in the school. Net, my approach to
learning plane geometry worked fine.
I never took freshman calculus. The college I
started at wanted me to take some math that really
was just a review of what I'd covered in four years
of math in high school. So, a girl in the class let
me know when the tests were, and I showed for those.
The teacher said I was the best math student he'd
ever had. Meanwhile, I got a good calculus book and
started in, worked hard, and did well. For my
sophomore year I went to a much better college and
started on their sophomore calculus and did fine.
Yup, never took freshman calculus.
When I went to graduate school, I took a problem
with me and had an intuitive solution. My first
year had some good courses (one was just terrific,
from a star student of E. Cinlar now long at
Princeton) and gave me what I needed to turn my
intuitive solution into a solid math solution; I did
that in my first summer, independently; and that was
the research for my Ph.D.
I continued that way in my career: E.g., in a
software house working for the US DoD, I saw a
problem in a specification, got Blackman and Tukey,
'The Measurement of Power Spectra', and read it
carefully enough to see what was wrong with the
specification and how to fix it. Right: without
courses, lectures, problem sessions, ....
As far as I can tell, nearly all the technical
content on HN, StackOverflow and other Internet fora
is from people who taught themselves in similar ways
with little or nothing in courses, lectures, problem
sessions, .... And that's part of what researchers
have to do and is just part of getting tenure as a
research professor.
So, since so much work is being done by essentially
independent study now, just by not making things
worse on-line courses should be able to look
successful.
But I see some problems with the on-line materials I
tried:
(1) The video quality just sucked. I couldn't read
the board. That meant I couldn't copy what was on
the board and study it. Bummer.
(2) The sound quality was not good enough.
(3) The course materials, e.g., on paper or in PDF
files, were from not good enough down to just
missing.
(4) Sadly the quality of the course content was too
low; apparently the main reason was the desire to
make the course more 'appropriate', that is,
'easier', for 'the common man in the street'. But,
omitting material 'waters down' the course content
and, really, for a good student, requires that they
fill in the gaps for themselves -- bummer.
E.g., I looked at the course by Stanford professor
Ng on 'Machine Learning'. What I saw were
weaknesses (1)-(4) above. For more, (A) a lot that
he was doing was maximum likelihood estimation but
with far too little explanation and justification;
so, I would have had to have run off and studied
maximum likelihood estimation on my own. So, again
I was on my own to do some independent work,
trusting Professor Ng that somehow maximum
likelihood estimation was better than it has long
seemed in the statistics community. (B) He
mentioned the 'maximization' to be done via
following gradients, and that is an overly
simplistic and not very promising approach to
maximization -- the standard, first problem is that
spend nearly all the computing time moving in
directions nearly orthogonal to the direction really
should be moving in.
So, from (A) and (B), I concluded that for a good
course I would have had to have taken his lectures
just as topics to be investigated, gone to good
materials elsewhere, collected good details, and
written my own text. That's his job as a professor,
not my job as a student. His field, 'machine
learning', didn't look worth that much work for me
now. I've done some serious work in several cases
of applied math that could be called 'machine
learning' as much as his material, and I'm left
without much respect for his material.
I looked at the course 'Probabilistic Graphical
Models' taught by Daphne Koller. Since I very much
liked a course by a star student of E. Cinlar, maybe
I should like Kollar's course. Sorry, I didn't --
the quality looked too low. Better quality from
Stanford? Sure, K. Chung, H. Royden, D. Luenberger
(his 'Optimization by Vector Space Methods' is a
beautifully, even elegantly, done one mile long
applied math dessert buffet), D. Knuth.
For courses in 'how to code', that is, introductory
material in software, gotta be kidding! 'Coding'
alone is easy; it's just, pick a language, learn the
basic syntax, and write if-the-else, do-while,
call-return, allocate-free, etc. It's easy but
doesn't take one very far. So, don't get very far
with thousands of Web pages of documentation at MSDN
on .NET, ASP.NET, ADO.NET, administration of SQL
Server, IIS, Windows Server, etc. or the equivalent
in the Linux world.
I have two broad conclusions:
First, traditionally in academic material in
technical subjects, the author and the student
'reached' to each other, and they connected at a
well written textbook. So, the author went far
enough toward the student to prepare a good text --
and the best texts are terrific. And the student
reached far enough toward the author to make do with
little or no more than a good text. It's how I
learned plane geometry, freshman calculus,
theoretical, applied, and numerical linear algebra,
everything I learned about statistics, most of what
I learned about advanced calculus, signal processing
and the FFT, stochastic optimal control, artificial
intelligence, ..., and everything I learned about
software. E.g., it's heavily what worked for me.
The on-line community will have to face the fact of
this 'reaching'. In effect, on-line learning
requires the professor to do more work of a kind
that promises not to be well rewarded by tenure and
promotion committees. So, net, so far a student
should still reach mostly for one of the best texts,
on paper or PDF.
Second, the situation will 'settle out': The
professors will come to understand what minimum
quality is needed, and the students will realize
that the learning is not just a spectator sport, is
not like watching a movie, and still requires nearly
all the traditional work from a book or PDF file.
Then the courses will get better; the students just
looking to watch a movie won't sign up; and the
course completion rates will increase.