Multilitteratus Incognitus

Hey!  We've made it! It's the final blog post about #dalmooc... well... the final blog post with regard to the paced course on Edx anyway :)  Since we're now in vacation territory, I've decided to combine Weeks 9 and 10 of DALMOOC into one week.   These last two weeks have been a little light on the DALMOOC side, at least for me.  Work, and other work-related pursuits, made my experimentation with LightSIDE a little light (no pun intended).  I did go through the videos for these two weeks and I did pick out some interesting things to keep in mind as I move through this field. First, the challenges with this sort of endeavor: First we have data preparation. This part is important since you can't just dump from a database into programs like LightSIDE. Data needs some massaging before we can do anything with it.  I think this was covered in a previous week, but I think it needs to be mentioned again since there is no magic involved, just hard work! T...

Hello to fellow #dalmooc participants, and those who are interested in my own explorations of #dalmooc and learning analytics in general.  It's been a crazy week at work with many things coming down all at the same time such as finishing advising, keeping an eye on student course registrations, and new student matriculations, making sure that our December graduates are ready to take the comprehensive exam...and many, many more things. This past week I really needed a clone of myself to keep up ;-)  As such, I am a week behind on dalmooc (so for those keeping score at home, these are my musings for Week 7). In week 7 we are tackling Text Mining, a combination of my two previous disciplines: computer science and linguistics (yay!). This module brought back some fond memories of corpus linguistics exploration that I had done a while while I was doing my MA in applied linguistics. This is something I want to get back to, at some point - perhaps when I am done with my doctorat...

I see a lot of WTF behavior from learners. This is bad... or is it? Oh hey!  It's week 6 in DALMOOC and I am actually "on time" this time!  Even if I weren't it's perfectly OK since there are cohorts starting all throughout the duration of the MOOC (or so I suspect), so whoever is reading this: Hello! This week the topic of DALMOOC is looking at behavior detectors (types of prediction models).  Behavior detection is a type of model (or types of models) that we can infer from the data collected in the system, or set of systems, that we discussed in previous weeks (like the LMS for example).  Some of these are behaviors like off-task behavior such as playing candy crush during class or doodling when you're supposed to be solving for x . Other behaviors are gaming the system, disengaged behaviors, careless errors, and WTF behaviors (without thinking fastidiously?  or...work time fun? you decide ;-) ). WTF behavior is working on the system but not the task ...

Whooooa! What is all this? Alright, we're in Week six of DALMOOC, but as usual I am posting a week behind.  In previous weeks I was having a top of fun playing with Gephi and Tableau. Even thought the source material wasn't that meaningful to me I was having fun exploring the potential of these tools for analytics. This week we got our hands on Rapidminer a free(mium) piece of software that provides an environment for machine learning, data mining and predictive analysis.  Sounds pretty cool, doesn't it?  I do have to say that the drag and drop aspect of the application does make it ridiculously easy quickly put together some blocks to analyze a chunk of data. The caveat is that you need to know what the heck you are doing (and obviously I didn't ;-) ).  I was having loads of issues navigating the application, and I somehow managed to not get some windows that I needed in order to input information to, and I couldn't find where to find the functions that I...

Week 6 CCK11 blog connections I was trying for a smarter title for this episode of #dalmooc thoughts, but I guess I have to go with Armchair Analyst since I ended up not spending a ton of time with either Gephi or Tableau last week. So, the reflection for week 4 is mostly on theoretical grounds; things I've been thinking about (with regard to learning analytics) and "a ha" moments from the videos posted. I think week 3 and week 4 blend together for me.  For example, in looking at analytics the advice, or recommendation, given is that an exploration of a chunk of data should be question driven rather than data-driven.  Just because you have the data it doesn't necessarily mean that you'll get something out of it.  I agree with this in principle, and many times I think that this is true.  For instance, looking back at one of our previous weeks, we saw the analytics cycle.  We see that questions we want to ask (and hopefully answer) inform what sort of data...

CCK11 Tweet visualization Alright, after a few days of being sidelined with a seasonal cold, I'm back on #dalmooc.  Still catching up, but I have a feeling I am getting closer to being at the same pace as the rest of the MOOC ;-)  In any case, this is a reflection on week 3 where we started messing around with social network analysis (SNA).  This is cool because it's something that I had started doing on another MOOC on coursera, with Gephi, so it was an opportunity to get back on and messing with the tool. So, what is SNA?  SNA is the use of network theory to analyze social networks.  Each person in this network is represented by a node (or edge), and nodes  can be connected to other nodes with a vertex (or many vertices). These connections can indicate a variety of things (depending on what you are examing), however for my usage in educational contexts I am thinking of vertices as indicators of message flow, who sends messages to whom in a network...

Continuing with my exploration of DALMOOC, we've reached the end of Week 2 (only a few days late ;-)  ).  I've been playing with Tableau, which I can describe as Pivot Tables on steroids.  I briefly explored the idea of getting some IPEDS data to mess around with, however that proved to be a bit more challenging than I had anticipated. So, I ended up using the sample data of course evaluations to figure out how to work Tableau.  The following are some interesting visualizations of the data that I had: The one thing I realized, as I was playing around with the data, is that it's really important to really know what your data means.  I thought I knew what the categories meant, because I thought that institutions of higher education used similar lingo.  The more I played with the data, the more I realized that some things weren't what I was expecting them to be.  Thus, in order to know what is being described and portrayed through the visualiza...

I've had this app on my iPad, by TechSmith, for the past few years, but I've never really used it.  The App is called ScreenChomp and it allows you to have a digital whiteboard that you can use to write and narrate.  I through that a plain text description of the learning analytics cycle (still catching up on week 2 of DALMOOC) would probably be confusing, and using PowerPoint and Adobe Presenter would be too static.  So, I applied the learning analytics cycle to a course I teach, and I decided to hand-write everything. Heck I attempted to draw as well, but my lack of artistic talent shows ;-) Direct link to the screenchomp (if the embed doesn't work):  http://www.screenchomp.com/t/qE1lplho DALMOOC Week 2, Description of the Data Analytics Cycle from Apostolos K. on Vimeo . How does this cycle apply to your courses?

View from Itea, Greece Some people bring a book on vacation (which I have) and others immerse themselves in the local culture (which I am also doing to some extent), but since I find myself lucky enough to be vacationing somewhere with fast wifi access I decided to continue to MOOC while I am on vacation from the day job. I honestly don't know how well the experiment will go, but I decided to follow three MOOCs. One on FutureLearn, focusing on management (making those connections with my MBA), and two MOOCs on MiriadaX, the Spanish MOOC platform: one focusing on social media and marketing, and another focusing on media studies called "the 3rd golden age of television." I didn't really think about my MOOCing until I had a back and forth with a friend and colleague on a Facebook about "completing MOOCs" and whoever completes one gets a unicorn ;). I guess the point he was trying to make is that completion is mission impossible. This made me think of my presen...

Well, last week of #rhizo14 and we're all pondering where to go from here, planning the next steps I guess.  Although I am getting the distinct feeling that participants are going through the stages of grief ;-)  In any case, the topic of this last week ties into enabling student independence, which was the topic of week 3, except that this week it feels more like kicking the birds out of the nest :) The other day, independent of rhizo14, I was having a conversation with one of my graduate assistants, who also happens to be in the graduate course I am teaching this semester (titled: The Design and Instruction of Online Courses ).  This, and #rhizo14, mixed and produced the following thought process, pondering, and question at the end of the post. (Historical background - if you want to skip, go down 3 paragraphs) The first time I taught this course (Spring 2013), I was a last minute substitution. The course designer, and regular faculty member teaching the course, ...

Value Map Badge It's Saturday, so it must be #OpenBadgesMOOC time :)  The thing that I just noticed about these badges on the #OpenBadgesMOOC is that if you look closely enough they look stitched.  Maybe there is an easter egg hidden somewhere, whereby if you earn all #OpenBadgeMOOC badges they send you a sash with all of them stitched on - LOL :) In any case, it's the end of Week 4 on the MOOC (2 more weeks to go) and this week we are talking about validation.  It's interesting.  One of the things that comes to mind as I progress through these is that the initial "levels" were a little easier to articulate, at least for my #ESLMOOC project, but as the weeks progress it's getting harder since I don't have all of the information. This also draws a parallel to Kirkpatrick's Level's of Evaluation where Levels 1 and 2 are easier to measure, at least in the short term, but Levels 3 and 4 (and if you look at Philip's 5th level ) it gets harder...

Since I returned from vacation I've been catching up on news that happened while I was away, and listening to podcasts from May that I had downloaded to take with me to listen to, but due to the hustle and bustle of vacation, I ended up not listening to anything I downloaded.  I was listening to a podcast from NPR's education feed when they were reporting on MOOCs and certain school's apprehension toward them.  The first thing, right out of the gate, is that somehow MOOCs and Online Education have become synonymous.  While MOOCs are a subset of Online Education, I wouldn't equate one with the other. That said, I put my skepticism aside and listened on.  The first thing that came up, from the critics, was that MOOCs wouldn't be able to replace learning that happens in undergraduate courses, especially those in the 100 level, because students come to college under-prepared, so they don't necessarily know how to learn, in other words they don't have good st...