Another comment posted on somebody's blog

Among the recommended reviews is this one by Wolfgang Greller, at http://145.20.173.188/~wgr/wordpress/?p=799&cpage=1#comment-2085

Basically, he reviewed on the aspect of experiencing MOOC. Again, I feel that I'm in the same boat. So here's my comment:

Shazz Says: Your comment is awaiting moderation.
January 21st, 2011 at 05:57

I totally agree with you, especially the last part. I myself thought that I can use my old method of strategising my way in accessing the information from the MOOC, so I (by habit) created a blog for this, even followed George in creating the NetVibes, and etc.

But I still find that it’s too wide and diverse, that I still have to depend on my skimming skill (if I have the time), my time (to go through the email notifications) and the facilitator’s review (and from there I would rather read the reviews posted by other learners instead of recommended readings by the facilitator!).

As you said, I least worry about all these, because as long as we know where they are and how to ‘search’ for it later on after the course, I think we’re quite save to catch up at later stage. The important thing is to contribute via reviews, because that would ensure our understanding, at least for our own relief.

- Shazz, Kuala Lumpur

Finding own paths in MOOC,
- Shazz @ LAK
21 Jan 2011

A video worth a view...

I remember citing Peter Norvig's writing in my research paper, but only now I know he's from Google! Wow wee! ;D



Thanks for sharing this, LAK!

- Shazz @ LAK
20 Jan 2011

Comment on Sheila's Blog

One of the recommended feedbacks/reviews by our facilitator is a blog post by Sheila:

http://blogs.cetis.ac.uk/sheilamacneill/2011/01/20/thoughts-so-far-on-lak11/comment-page-1/#comment-121108

I didn't really read through her post yet, but I understand from Mark's comment that one of the points mentioned by Sheila was about getting herself adapted to MOOC - which is what everyone is experiencing even though we're already in the end of Week 2! Well, welcome to the club! ;D

So here's my comment (which is at this moment, still in waiting line for approval by Sheila):

Shazz

January 20th, 2011 at 3:50 pm

Your comment is awaiting moderation.

I agree with Mark. It's quite tough in the beginning, because of the 'panic' of not really knowing what we need to know in order to follow the topics... But thanks to previous experience in following George's teaching in 2008, I'm more confident in 'leaving behind' some of the texts/articles recommended to read in the study weeks.

In fact, I find it more comfortable reading others' reviews on the texts, and then go into the texts to 'understand the gist' myself and compare it with the reviews. At least some of the main ideas are already covered by the reviews, so we don't really miss much if we skim through and spot other points that interests us.

One thing for sure, what our eyes spot as interest might be a different angle of understanding compared to others. Interesting! ;D (even though it sounds like we tend to get lost too. LOL)

- Shazz, Kuala Lumpur

Sincerely, a learner,
- Shazz @ LAK

20 Jan 2011

A quick response to one of the topics in Week 2

Answering the discussion topic by Xavier Ochoa:

AK vs EDM vs Educational Research by Xavier Ochoa - Wednesday, 19 January 2011, 04:10 AM

Today at the very interesting talk of Ryan Baker a question arise about the differences (and similarities) between Educational Data Mining, Learning and Knowledge Analytics and the traditional field of Educational Research. I think that this question deserves further exploration in this course. The definitions that those terms have in Wikipedia are very similar: Educational Research: Educational research refers to a variety of methods in which individuals evaluate different aspects of education including but not limited to: “student learning, teaching methods, teacher training, and classroom dynamics”. Educational Data Mining: Educational Data Mining (called EDM) is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in. Learning (and Knowledge) Analytics: Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning. Is there a difference? Do you think that EDM and LAK are just an evolution of Educational Research, but with better tools and data, or there is something radically different and unique in the new approaches? Do you think that EDM and LAK are synonymous or there is a meaningful difference between the two fields? Should we merge or we should keep them separated? Let's discuss.

My review was as follows:

I do believe that both LAK and EDM are from the areas of Educational Research even though not directly; more on technicalities in terms of data/information, methods of analysis. They are the shared areas between Educational Research and other technological research, such as artificial intelligence and of course data mining.

So far, this is what I understand from the 'research areas' that makes LAK (as shown in attached diagram).

- Shazz
Kuala Lumpur 10:30PM

Just started to 'follow' Week 2 activities,
- Shazz @ LAK

20 Jan 2011

Dave's Review on Week 2 activities

Can't quite find a way to 'follow' Dave's blog from here, so I just bookmark the link from here so that I can refer to it when I'm free.

Thanks for the recommendation, George! I like Dave's way of review too. Clear!

http://davecormier.com/edblog/2011/01/20/mooc-newbie-voice-week-2-big-data-must-be-important-its-big/

Currently busy with PhD proposal defense preparation,

- Shazz @ LAK

20 Jan 2011

My review entailing Viplav Baxi's comments

I like the style Viplav explained on the difference between metrics/numeric measurement, and paths and patterns in analytics. I was trying to explain it in words for quite some time but I just couldn't, even with a clear vision in my head on how it looks like...

Re: What about learning analytics in the corporate sector? by Viplav Baxi - Sunday, 16 January 2011, 05:49 PM

One of the areas that greatly interest me is simulations for corporate training needs. I have done work in the IT and Financial sectors that show the power of simulations to bring together some complex information about how a learner navigated a simulated job situation. Scores are too simplistic to do justice to such complex tracking of learner progress and competence. Consequently, learning & knowledge analytics become more complex as well. For example, let us consider a scenario that has multiple decision points (connected like in a graph) and multiple paths to the correct outcome. Let us assume that there is an ideal path (not hard to imagine in a highly disciplined process training). A learner's decision making trail or actions trail could be compared to the ideal path/trail and analytics could be programmed to infer from deviations to get a better and more comprehensive picture of learner performance. (also not unlike the notion of knowledge analytics being used to compare competency levels in a discipline). If you know cricket, you would be familiar with a graph that shows runs scored vs overs for both teams with circles denoting fall of wickets, resulting in what are popularly called "worms" that deviate from each other on the graph as the match progresses. Point is, these analytics move from being comparisions between numbers (Peter spent 5 more minutes than Pan on the google group), to being comparisons and analytics based on patterns and paths. Viplav

My comments:

Thanks, Viplav... Your explanation really put my understanding in words, quite clearly (about the patterns and paths versus numbers).

Tailing this, I wonder:
- How can this pattern be presented to senior management (assuming they are not at 'our level of understanding') in a form that they appreciate?
- How can we be certain that the paths the employee takes in getting to the final point are something they learnt and contributing to the final result, or merely a waste of time until they found the right 'nodes'?
- How should the evaluation be designed to make it fair for every employee (because some people do take time to understand after a long-winded paths, etc...)?
- Does this mean an experienced 'wanderer' could achieve the KPI better than newbies? I don't think so too.

There's still further way to go after this, and I believe corporate sector is very particular about 'measurement' in evaluation.

Hope I'm in track with my points,
- Shazz
Kuala Lumpur 1:33AM

Still wonder if I'm in the same track,

- Shazz @ LAK

19 Jan 2011

Extracting the gist - Learning Analytics in Corporate Sector

Let me digest some points from the discussion that is going on in LAK11 MOOC this week. My review is yet to come, maybe tomorrow.

I like the points clearly outlined by Adam Weisblatt on this topic:

- Corporate training rarely has grades, but performance reviews and business outcomes. [KPI, as Tanya Elias mentioned.]

- Analytics is most important for decision making at the senior level.

- Prediction would be most helpful in creating development plans.

- Corporations are interested in the value of social media but they want to be able to track the advantage of its use because they pay for it in one way or another.

Skimming through the rest of the discussion thread, it makes me wonder how easy academicians wander out of topic (slightly) and back into the realm of education... as they started talking about grades, accreditations, and such, that they think corporate world should have certain standard for. To me, it's not at all about grades - because grades also mean that the person (or graduate) may or may not be practically useful at work. Well, long list of that from where it's coming from!

I love this part, since "lifelong learning" is also the 'aim' and mission of my organisation (private university in Kuala Lumpur):

"In the UK, the term ‘Lifelong Learning’ is applied to any learning that is undertaken after leaving formal education. In theory online corporate training would fall into this category but, to me, it does not fit well due to the simplistic methods used (in order to assure assessment) and because it does not address the acquisition of the ability and skills needed to apply the knowledge. Lifelong learning is more about knowledge based upon experience (both one’s own and that of colleagues) and therefore bound up with skills and ability. The trick is, understanding how to capture this lifelong learning in a way that is meaningful to employers (current and future). I am hoping that learning analytics may supply some of the answers." (Peter Condon, 15 Jan 2011)

Let me rest my case for a while,

- Shazz @ LAK

19 Jan 2011