Week 6
Another worthwhile TED Talk that applies to our topic from Kahn Academy: http://www.youtube.com/watch?feature=player_embedded&v=gM95HHI4gLk

Again, I had trouble with the recordings from this weeks webinars - that is frustrating...

Week 5 – Activities, Thoughts and Questions

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This week’s topic was one that I was looking forward to and think is most important. It is was however also the week where I had the least time to devote to the activities and readings and am thus trying to create a list of issues and questions that I want to go back to:

In the Aspen report the three questions raised are ones that I will want to follow up on:

·   Do huge datasets and advanced correlation techniques mean we no longer need to rely on hypothesis in scientific inquiry?

• When does “now-casting,” the search through massive amounts of aggregated data to estimate individual behavior, go over the line of personal privacy?

• How will healthcare companies and insurers use the correla­tions of aggregated health behaviors in addressing the future care of patients?

Why am I not surprised that the most attention was received as big data applies to financial markets and risks there?

I did like Bollier’s (2010) description thought: “Computing has become ubiquitous, creating countless new digi­tal puddles, lakes, tributaries and oceans of information” (p.1).

Key words:

·        -  Real-time decision making tool

·         - Teasing out potentially useful patterns

·         - Petabites have 15 zeros

·         ... imperil personal privacy, civil liberties and consumer freedoms

·         - Visualization of data and other data cleaning choices

·         - Now-casts

·         - “The benefits of personalization tend to accrue to businesses but the harms are inflicted on dispersed and unorganized individuals, Taipale noted” (p. 23).

·         - “smart mobs” demonstrate the ability of non-com­mercial actors to influence trends

·         - Science Commons

·         - “securitize” people’s health

·         - Data integrity

Boyd & Crawford was a good read:

·         - analysis conducted only at a fixed point in time

·         - possiblity to de-anonymize parts of the dataset

·         - accountability is a multi-directional relationship

·          -   the “difference between being in public and being public” (boyd & Crawford, 2011, p. 12)

·         - “While institutional inequalities may be a forgone conclusion in academia, they should nevertheless be examined and questioned. They produce a bias in the data and the types of research that emerge” (p. 13).

I liked the Times multimedia options for the resources this week. Yes, the power of habit...

Yesterday I watched a video interview with George where he explained the difference between complicated and complex: http://www.youtube.com/watch?v=qesp9b2w_aY

I liked the meeting with Erik Duval and his insight and European perspective.

Week 5 Materials

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Is it just me or are there no materials so far for week 5?

Week 4 Activities

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I've enjoyed the week so far. The first two readings on the semantic web were too techy for me and I have yet to read the reamining ones.
However, as I was watching Tim Berners-Lee TED talk I had made a note of his comment regarding the stats presentation by Hans Rosling. I watched it and wanted to share with everyone that it really is - in more ways thatn one - a fascinating presentation. If you have a little extra time it is totally worth watching >

http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html

The other resource that I wanted to share was Tony Bates' e-learning outlook for 2012. His 2nd prediction relates to Learning Analytics. His other predictions are an enjoyable read as well > http://www.tonybates.ca/2012/01/02/e-learning-outlook-for-2012-will-it-be-a-rough-ride/

Finally, I had a really hard time concentrating on the LAK meeting this week. The audio was so poor that it took the joy out of learning for me - which goes to say (to me at any rate) that quality does make a difference.

Week 3 Readings

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This has been my favorite week to date. I enjoyed the reading and the various clips. I definately have a better understanding of 'big data' and can image what a data scientist would do and/or needs to know. There were some additional resources that I made note of: Stephan Wolfram, NKI's Quality Barometers, First Monday and Gartner.
I learned that behaviors are good predictors and like the Purdue example --- (yes, Signals) -- really brought it home for me. But I also totally liked the Educause panel discussion with George and Rio Salado' s person (I would really encourage everyone to watch from the beginning and not just start at minute 19...) 
Note to self: # of LogIns, Site engagement and place were the big three for Rio Salado.

I will want to look into the Cambridge Handbook of the Learning Sciences and recommend the Knowton site to some folks in my network who arent' involved in this space.
Whew -- lots to do and take away.

Week 2 Readings

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I was glad to learn about the distincition between learning analytics (learners and their contexts) and academic analytics (business focus on the institutional, regional and international level). This helps to understand where and how analytics can be transformative.

The Educause article by Campbell and Oblinger was informative with respect to the depth and breadth of academic analytics and who the players and stakeholders are as well as describing the data, how it is gatehered and reported and what can be achieved. I particulary appreciated the straightforward listing of the potential and the concerns.

The wordle was fun as always. The article on data mining for education was too researchy for my taste and too specific for my purposes.

During Week 2

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I'm not sure why my blog isn't showing up on the lak-12 Daily Newsletter, but that is another thing.

I attended the live session on Tuesday and feel that the technology got in the way of making the session (and no doubt the recording) a less than effective learning moment.
Serendipitously, I had another opportunity to listen to Wally Boston, President and CEU at APUS who presented on how his institution uses learning analytics and some of the tools they employ. A very good overview of some examples and tools used and issues and challenges - in a nut shell.

Below is the link to the recording of the



https://sas.elluminate.com/mr.jnlp?suid=M.5B29576A09D50CB715DC37A91117C1&sid=251

Wally Boston's presentation is about 29 minutes into the recording.

An now to this weeks readings...

Week One Readings

I had some time over the weekend to devote to the readings.  The McKinsey Report was a great overview of big data and what it all can mean and what needs to be considered.

I found the ECAR findings interesting and enjoyed seeing an alignment to educational institutions. I was particularly interested in the finding that institutions were least successful in reducing ‘shadow systems’, but that those that use reporting dashboards  did have greater success. It may be(come) obvious, but I was wondering what data was on these dashboards and how the impact was measured.

The IBM efforts were most interesting to me and I would love to hear if anyone in the group has had firsthand experience at their institution in either training their faculty or including IBM curriculum in their courses.

Week One Presentation

I enjoyed the first presentation (I had to watch the recording since I could not attend live. I thought it very valuable to have someone discuss analytics in a completely different area. I especially iliked the many graphics and images as forms of data.

Got some motivation today

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I've been working on setting everything up and haven't yet had time to devote to the readings. Learned today that a work colleague has joined as well - this should be a motivator.

Starting with lak12 setup today.