Learning Analytics MOOC – Week 2

Topic of this week is the „Learning Analytics Cycle“ and conducting some basic analytics with our test access to the Tableau software. The YouTube video from George Siemens about the Data/Analytics Cycle was very helpful, also the Google Hangout with Tony Hirst about „Data Wrangling“. I also attended the  Google Hangout on Wednesday and I am very impressed  by the commitment of the course facilitators – thank you!

My interpretation of the Learning Analytics Cycle consists of these steps:
1. Data collection, Data Acquisition and Storage (Data is generated by or about the learners: Sources can be LMS, Student information systems, Social Media… any interaction between Learner & Institution)
2. Dataset Cleaning (missing data, different spelling of names,…)
3. Analysis & Visualization
4. Action (Intervention, Optimization,… and back to the learners)
That means the process starts with the learners and ideally the cycle / loop closes with feedback of the intervention to the learners.
When we look at data, we can do counting, sorting and therefore get different sort of charts with the same data. As to interpretation, theses aspects are relevant: looking for outliers, looking for similarities and differences, looking for trends, looking for patterns & structure.
Certainly, you have to think about what you would like to know when you do the data collection and not only when you do the analytics & visualization.

My tests with the Tableau Software:
After having registered with Tableau a lot of times –  at first to get a test version of the software (thankfully in this MOOC we get an extended test period), then to actually start it after installation and then even to get the video tutorials – I watched the „Getting started“ video (20 minutes) and was really impressed with the variety of functions.

As I don’t have a set of educational data which I could use for testing, I had to be somewhat creative to use a different kind of dataset for testing. At our University (and in Germany) we have very strict regulations for the use of user data and logfiles and so my example won’t have anything to do with educational data but with recreational data… But my goal at the moment was to play around with the Tableau Sofware in order to get used to working with table cells and rows and visualizations and I am satsified with my results:

I spent more time with the MOOC this week than I planned because it was fun and creating artifacts is really very time-consuming. I am looking forward to week 3 and hopefully, I’ll find the time to try Bazaar meetings.

 

Learning Analytics MOOC – Week 1

The Horizon Report Higher Education 2014 sees Learning Analytics in the Time-to-Adoption Horizon as „One Year or Less“ (in the Report 2013 it was „Two to Three Years“), so the topic LA is quite an interesting one for Educators.

However, Learning Analytics (LA) is a term which needs definition – The Society for Learning Analytics Research defines it as „the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs“.

The slide at 3:00 min shows that it’s a good idea to know more about LA: „Data trails reveals our sentiments, our attitudes, our social connections, our intentions, what we know, how we learn and what we might do next“.

I really liked the link to the fulltext article „Educational Data Mining and Learning Analytics“ (Baker & Siemens 2014) as it gives an introduction and overview of the field (graduate programs, journals, conferences, methods & tools, differences between Educational Data Mining, EDM, and LA research communities). The reasons of the growing use of LA are cited as „a substantial increase in data quantity, improved data formats, advances in computing, and increased sophistication of tools available for analytics“.

What about software (analytics / research tools)? I try to remember that for single functionality there is NodeXL and Gephi whereas integrated suites would be SAS, IBM BI Analytics suite and Pentaho. Open Socurce tools are R and Weka and in our course we will focus on Tableau, Gephi, RapidMiner and LightSide. I intentionally skipped doing a tool matrix because at the moment I don’t feel like being competent enough and other things were more important to me (I decided that it’s  the kind of MOOC where I choose my learning goals).

In week 1, I spent about 5 hours with the MOOC: at first looking at the course / resources / activities in edX (plus joining one of the live hangouts until midnight local time on Tuesday) and then signing in ProSolo. My first impression of ProSolo was that is wasn’t very intuitive, so in week 2 I’ll  have a closer look at what the menus „plan, learn“, „goals, competences, activities“ mean.

I look forward to week 2 of DALMOOC and I’m curious what we will do with the Tableau software.

DALMOOC – My first steps

The official start of this MOOC on „Data, Analytics and Learning“ (DALMOOC) is on Monday 20th, but a lot of activity has already taken place, e.g. two Google hangouts – at not such perfect times for Middle Europe… Therefore I watched the archive of the Course Design Explanation session (October 17th) on YouTube http://youtu.be/b2gSd6oxEBM which was quite intereresting.

Why I joined this course

I already looked at the course in edx.org (whose user interface I already know very well) and was surprised that the first thing I saw in the Courseware section was a special DALMOOC Course agreement about participation in a study – I am still not sure what’s the difference if I say yes or just ignore it  (which I did for now). Afterwards I watched the „How DALMOOC works“ video which emphasized on „It’s about connections & creation not content“ and that it might be a little disorienting at the start for someone who has taken MOOCs that were more structured. For DALMOOC in edx.org, 4 points were mentioned to help orientation: the visual syllabus, a daily email, hangouts/recordings and edX forums.

Course Tools
In the course, many tools beyond edX will be used – for my orientation I add these URLs in the blog post:

I am looking forward to the official start of DALMOOC on Monday. I don’t know yet how much time I will spend, because the course is parallel to the busiest time of year with the beginning of the winter semester at our University. Besides the edx.org course portal https://www.edx.org/course/utarlingtonx/utarlingtonx-link5-10x-data-analytics-2186 I will have a look on what happens on Twitter (#dalmooc  https://twitter.com/dalmooc ) and maybe Google+ https://plus.google.com/106806974410074176435/posts