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Sheila Seiler
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Learner. Educator. // 2017 United Arab Emirates Librarian of the Year
Learner. Educator. // 2017 United Arab Emirates Librarian of the Year

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+Carmen Weaver Okay, coming down the home stretch in terms of finding information and writing up all the categories needed for each document. My questions:

Are we sharing the 20 write-ups in a document separate from annotating them under Notes in Mendeley (which was a great tip from you)? If so, how would you like us to send you that document?

Next - the books I ordered have not yet arrived, so I have summaries of them that I can use instead of abstracts (which is what I did for the Draft assignment), but I can't input them into Mendeley. How would you like for us to share our notes with you on any book-length texts? (Before, I did it in Word. Does the same method work?)

Thanks for any help you can give! This is a big one and I want to make sure I nail it. :-)

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Here's my link; I did a combo of tables and bullet-pointed lists because that's how my brain works. After I saw everyone else's, I thought about trying to do a mind-mapping document, but then, nah, I just need to be able to access information quickly and easily.

Also, whoah - that was intense! :-)

https://drive.google.com/file/d/0Bz-JyKXrsrfTOHBMd3lwVXkxRVk/view?usp=sharing

+Carmen Weaver I'm in a panic! The assignment for the Annotated Bibliography is to cite articles, but I'm having a hard time finding anything that's less than book-length. (I've ordered four of the books online, which will take a month, and the rest are available as ebooks through the U of M library, which is great.)

Okay, so that's not completely true - I can find articles, but I think they're wrong. For example, "deep learning" and "machine learning" are ONLY correctly used when referring to machines that learn how to code themselves and from their mistakes. But the articles are using them to describe how humans can learn better teaching techniques from examining machines and computers, whereas I want to look at the opposite. So it's a misuse of the terms, which brings the articles into question in terms of credibility (something you asked us to pay attention to).

So why am I sharing all of this with you? Why not just solve it by citing other sources?

My answers will be incomplete when outlining each article (research questions, participant descriptions, etc.) because I don't have the books yet. I'm skerrred!

Any advice?

+Carmen Weaver Hey teach! I have a question: what if no one gives feedback on our Research Interest Profile? We're down to 27 hours before the final draft is due and for those of us who need to substantially revise (after viewing other students' work, I have a LOT of ideas about how I can hone my work), that's cutting it close with work and life commitments. So if no one comments on ours - or not until the last minute - do we just proceed with revisions anyway?

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Hi all! I want to apologize to the community for the formatting of my Research Interest Profile - I've been locked out of Gmail, Google Drive, and Google Plus on all devices, except I can access Google Plus by phone for some reason/miracle. Anyway, here are my thoughts:

Area of research interest:
Machine learning is an aspect of machine intelligence that is being studied in various other disciplines, including education. It examines the ways in which programs - like Google's autocomplete function - learn, as well as computational approaches to learning. Analysis of machine learning involves theoretical study, empirical studies, applied research, and comparison to human learning. How do machines solve problems that they haven't been coded to solve? How can they be coded so that they create their own codes in the same way that humans learn and evolve? How can understanding machine learning help us to solve problems? Those are some of my starting questions.

Problem or need:
I don't know what problem or need would be addressed, so I set up interviews this week with the following people to ask about what their organizational needs are or what problems they perceive need solving in the area of machine learning:
-Andrew Wang, creative director of Beach Creative, an international design and development lab "dedicated to rethinking and redefining what is possible"
-Chris Matthews, tech startup entrepreneur, founder of Yunio (the Dropbox of China)
-Steve Hoffman, serial entrepreneur who has worked with hundreds of startups all over the world
-Catherine Erpen, vice principal of my school (GEMS World Academy in Abu Dhabi) and techie
I don't think it's appropriate for me to say what problems need solving until I've checked in with "clients" and thought-leaders.

Target audience:
According to Regina M. Daigre's article, "Orienting Questions," instructional designers need to examine stable and changing similarities among learners. Stable similarities in working with machine learning are: sensory capacities, information processing, types of learning, and conditions of learning. Stable differences are intelligence quotient, cognitive style, psychosocial traits, and gender, ethnicity, and racial group, but with machine learning, the former two are stable differences and the latter two nonexistent. How would this affect machine learning to have no bias except that which has been programmed?

Types of development used to address problems:
Technological singularity, which is the process through which machines learn to upgrade and continually improve themselves, has not yet happened. Computer programmers are working on writing codes that can write their own codes and have achieved some success in this area. Starting as early as the 1950s, machines have been invented that are able to sense, recognize, remember, categorize, and respond "like the human mind" and are "capable of what amounts to thought" (Marcus, 2012). Deep learning is the process of unsupervised learning through which computers learn abstract thought, deductive reasoning, and even how to beat humans at "Jeopardy," like in the case of Watson. Advanced coders are able to create codes that learn - something we all know when our phones stop autocorrecting certain words because it learns that we meant to type them that way.

Benefits to proposed instructional intervention:
This all sounds very sci-fi, but the future is now. Teaching machines how to learn is the next step in education - it's beyond driverless cars and towards problem-solving with greater efficacy than humans. According to Yottamine Analytics, benefits include self-modifying behavior, multiple iterations, intelligent decisions that take into account variables and which information to include and exclude without being told, and pattern recognition. We are at the cutting edge of all this and it would be amazing to discover how instructional design techniques and theories can influence non-human learning.

Barriers:
I'm learning the basics of coding and programming this summer, but do not yet fully understand what machine-makers do or how they do it. I know they're interested in learning from me, as I was able to easily get appointments this week through my network with people with whom I might want to work. The machine-makers and coders want to know what instructional designers can do for their work, but neither group has worked with the other much that I can find. That said, there's a first time for everything, as we learned from our last class, which covered the history of instructional design.

Why I am interested:
The two fields - education and computers - are linked in the sense that each supports the other, but yet, no one from the field of education seems to be looking at how computers learn. I can find information about just about every other area of teaching and learning, but not on how to teach computers and machines, how inanimate objects reflect and learn, and how metacognition works for nonhumans. The reason is probably that both coding and instructional design are new fields. I'm interested because I have questions and we're at a point in history when there are few answers. Maybe I can help answer them while asking better questions.

Works cited:

Analytics: The Machine Learning Advantage (2013). Retrieved July 11, 2016, from https://yottamine.com/machine-learning-svm

Daigre, R. (1999). An Overview of Learner Analysis. Retrieved July 11, 2016, from http://www.angelfire.com/la2/learners/learners.html

Marcus, G. (2012, November 25). Is "Deep Learning" a Revolution in Artificial Intelligence? Retrieved July 11, 2016, from http://www.newyorker.com/news/news-desk/is-deep-learning-a-revolution-in-artificial-intelligence

Hey, team, hey. Heyyyyy.

Okay, this is me:
Raised all over the South with part of elementary school and all of high school in Memphis, I moved away for college and grad school in Massachusetts and New York and continued getting farther and farther away from the Delta with each move.

After nine years in Shanghai, I moved to Abu Dhabi this past August. I work as a Media Literacy Specialist (fancy way to say "librarian") and Innovation Leader for GEMS World Academy. "GEMS" stands for Global Education Management System and is the largest private school system in the world, which has its drawbacks, but I'm in it for the network.

I'll be in Memphis around Christmas to see family. We should hang. OR come to the Middle East - it's fun! :-)
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