MOOCs: What Part of Learning Goes on Where and How?
My university just announced that we have joined a MOOC
(massive online open course, for those of you who like me didn?t know what the
acronym stood for). Specifically we joined EDx. The decision was made at a
level far above my pay grade. No one asked my opinion, which is actually a good
thing because I?m not sure what my opinion is at this point.
There are lots of good, altruistic reasons for higher
education to take this step. The intent is to make high level education
available widely at a very low cost to the consumer (not to the institution, by
the way). We?ve seen how freer access to more information has put the fear of
Truth into even the most dictatorial systems to the extent that they attempt to
shut it down as fast as they can and find that they can?t. I like that part. I
also like the possibility that freer access to information that is based on
solid research and realistic thinking might empower people to be less subject
to thinking based on superstitions and misinformation (not that it?s working
that well here). More selfishly, I like the idea that really good teachers
could be challenged to change the way they think about learning and put their
talents to work finding new ways to structure learning environments that can
handle the ever-expanding population of students with widely varying
backgrounds.
But I think there may be lots of good reasons for us to
take this step more slowly. Despite all the miraculous claims of how
transformative technology can be, right now there is still a lot of work to do.
Even the very successful Khan Academy is founded on a lot of delivery of
information, granted by a very gifted deliverer. But information is not
synonymous with understanding, and delivery is not synonymous with education.
So before I rush into volunteering to create courses for our new MOOC, I
thought as an educational psychologist I might take a crack at analyzing what I
know about learning that needs to be considered in the process. Here it goes.
Learning means focusing attention on the key concepts in
a topic. OK, online learning can take advantage of the magic of visual images
and presentation strategies to highlight key ideas and put them in a form that
will not only draw learner attention but create memorable images that will be
easy to recall later. Check!
Learning means making connections with a learner?s prior
knowledge. Hmmm, maybe not so easy here. Given the size and diversity of the
audience for a MOOC, being able to make those connections in the presentation
itself is going to be difficult. It?s possible that one of the affordances of
technology?gathering and analyzing data?might make this possible. After all
Amazon can keep track of the books and other things I buy and point me toward
other books of the same genre or that other people like me (i.e., those who
bought the same things I bought) liked. So it might be possible in the future
for an online course to analyze the kinds of interests and background I have
(from a population perspective) and offer me links from the information of this
course to other examples on the web that are related to it. I?m pretty sure
that doesn?t exist in the programming yet, but it could. It might take a while
to build up enough of a database (computers ARE good at collecting data) to
make those
predictions, but it?s possible.
Learning means actively processing the incoming
information, digesting it, working with it, summarizing, paraphrasing, applying
it. Yes, that works online, too, provided the information delivery part of the
course leads to opportunities for the learners to try out the ideas in various
ways. Most online classes have finally gotten around to realizing that just
listening to information is not the process of learning. As a result most of
them include activities for the learners. That?s good, but here?s the stumbling
block.
Learning also requires that the learners? attempts receive
guiding feedback. Uh-oh. That works pretty well in areas where there are
?correct? answers that can be evaluated readily by a computer, but there?s a
ways to go before it works in more complex content that involves decisions and
judgments. I actually ran into this problem recently in a project to provide
instruction in teaching to adjunct faculty using an online program. It was easy
to respond to questions that had simple answers, like who suggested the idea of
the Zone of Proximal Development (Lev Vygotsky). But evaluating the
significance of the ZPD for teaching requires a whole other level of
sophistication from the learners. Not so easy to anticipate all the things a
learner might offer as important. This is not to say that it can?t be done, but
rather that it can?t be done so easily YET. There are ways of providing
electronic feedback to this kind of active learning. Our solution was to
provide examples of answers that would fit
the task and let the learners compare theirs. Not totally satisfying and
sometimes not totally accurate.
There are some possibilities to consider when
contemplating this issue of feedback. One is the ?community of learners?
possibility. I think in the vernacular of MOOCs this would be called ?crowd
sourcing.? It?s a more elaborate version of peer feedback, where the large
group of learners respond to one another?s ideas in hopes of finding some kind
of consensus. I think this probably works in an informed community of
participants where there is a distribution of prior knowledge that can be drawn
on. I think a community of novices still needs the guidance of a more informed
individual or group of individuals.
Another possibility that has been around, but not
perfected in education yet is artificial intelligence providing individual
tutoring based on expert models and language matching. A new wrinkle that might
make this more feasible is the idea of learning analytics and large databases.
When this idea first came around, I was fascinated, but skeptical. I have seen
too many really strange thought trails in my students writing to believe that
even a computer could follow and guide them. But possibly the computer just
needs more information to develop a case inventory of potential student ideas.
I guess if they can create a computer that can win at Jeopardy, they can figure
out how to interpret student responses to open ended questions. But I (and many
other psychologists) believe that the essence of deep learning is in the
interaction with others as we grapple with what we think we know versus what we
really know. That?s the kind of online learning I?d like to see us build.
So am I going to try this thing? I?m conflicted. I see a
lot of possibilities, but we are definitely not there yet. The technology world
might be there, but those of us in education take longer to learn. Too busy
giving guided feedback.
Tomorrow's Professor: MOOCs: What Part of Learning Goes on Where and How?
