The Next Battle for Openness: Data, Algorithms, and Competency Mapping
I must admit to quite a remarkable change of heart after
this week’s videos and readings. At the start of the week, I read “The Next
Battle for Openness: Data, Algorithms, and Competency Mapping” and I had a
moment’s panic! What do I know about any of those things? I may have a fairly good
grasp of the science of learning, but I am only a novice instructional
designer, and I know nothing whatsoever about being a data scientist or
behavioural economist! However, I now understand so much more about learning
analytics, and the collection and usage of learner data. I was introduced to
the work of Candace Thielle and was blown away by her use of adaptive learning “long
before it was cool”!
Stephen Downes, George Siemens, & David Wiley
I have followed the work of George Siemens and Stephen
Downes for a number of years, and, since the start of this course, have a
profound respect for David Wiley. I currently provide staff development. That
is the work of the Tertiary Teaching Unit. My area of responsibility is that of
elearning. I can imagine how incredibly valuable it would be to have a system
that bundled up analytic information and translated the work of the underlying
algorithms into real language that our lecturers could use and understand. I
have worked with lecturers who have a profound knowledge of learning pedagogies
and practices in some faculties, but I have also worked with lecturers holding
multiple PhDs and/or years of work-place experience, in areas such as civil engineering
and maritime logistics, who really have no understanding of learning pedagogy
or practice. Many of these lecturers are faced with considerable barriers, including
English as a second, third, or even fourth language.
My institution, Manukau Institute of Technology
Yes, the process of collecting learner information leading
to efficient and facilitative learning environments, needs to be open. As Norman Bier (2017) indicated, “I think
we are already in a world where data-driven approaches and materials are
already being developed, adopted and embraced – by vendors, by schools, by
foundations and by government. The future is already here”. Bier (2017) indicated
that research has already shown lower costs, improved results, and the expedited
understanding that leads to new pedagogy and innovative practice. Mention was
made of ethical concerns. I appreciate these exist, but found so much that was impelling
and inspiring, that I would rather leave the negative arguments for another discussion
entirely.
Norman Bier
Bier (2017) warned against the learning analysis systems
operating as business models offering subscription services. He saw this as
counter-intuitive to the whole open movement. He cautioned about the urgency of
openness in learning analytics as “proprietary solutions have made enormous
inroads in claiming the data-driven space for their own”. He suggested full
transparency to inform decision-making. He further suggested that transparency
would facilitate the identification and remediation of biases introduced to the
digital sphere by individual coders and developers. “And the transparency
that’s inherent in the open approach is the best way that I know to ensure this
work can happen” (Bier, 2017).
Candace Thiell
I was very grateful for watching the video recording of
Candace Thiell and not just relying on the written article. Thiell
was interviewed by EdSurge (2017) for the Thought Leader Interview Series
when she was in attendance at the Arizona State University, plus Global Silicon
Valley (ASU+GSV) Summit. GSV are a group of companies and entrepreneurs who are
developing technology to transform the world of work and education. At 16
minutes, 30 seconds, the video includes a large segment that resonated with me
(not in the article). She spoke about mindset and working with algorithms that
used principles of mindset. As part of my PhD research, I have incorporated
mindset analysis.
At Stanford, Thiell has worked with mindset guru, Carol
Dweck. For an explanation of fixed versus growth mindsets, see the two, brief
videos below.
Dweck’s growth mindset suggests that the brain is
strengthened through struggle. Mindset interventions have been introduced into
courseware. Before the introduction of complex problems, the courseware introduces
“booster interventions” that educate the students on how the brain works. Data
collected reveals that mindset intervention has led to students persisting for
longer periods and achieving a greater amount of learning.
Another colleague of Thiell’s, Ryan Baker, has introduced
affect detectors, picking up on the learner’s affectual condition. The introduction
of timed mindset interventions when material is cognitively complex together
with information on the affective state of the learner, seems to be a most effective,
positive inclusion in to courseware. This is a most remarkable example of using
the power of the algorithm to make a teaching decision.
Ryan Baker * affect detectors
It seems appropriate to end with some thoughts from Stephen
Downes (2017) from The Next Battle for
Openness. Downes always thinks outside of the box. He suggested that the
challenges for openness may not be limited to the types of data but to the way
that data will be used. He referred to George Orwell’s “thought crime” and whether
we could be open with the way we think. He discussed the possibility of
mind-to-mind direct communication. That is not such an outrageous suggestion.
Back in 1982, when I was engaged in research into mutual hypnosis, I had
evidence of telepathic communication under mutual hypnosis. So, how open will
mind-to-mind communication be?
Downes speculated further about combining genetic and algorithmic
data to end up with a hybrid human-machine language. Would this be open? Would
it be ethical? Downes (2017) stated, “A lot of the issues of ethics and what it
means to be a person and what it means to be a society are going to be
challenged by the new possibilities of creating, manipulating, and sharing new
kinds of information. And I think openness is going to be challenged by these
things”. We really cannot conceive all the possibilities that we may face in
the future. Whatever happens, progress in learning and education needs to be
open, collegial, and shared, so that we can find solutions to problems that may
yet arise, together.
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