The first week of MOOC-type of LAK12 course is over. It is strange that in theory I have been strong when talking how informal learning should take place and how learning communities influence our development. Now when I should motivate myself to participate in informal course and find some time for learning, it is not that easy anymore.
I wanted to participate LAK12 course for two reasons. First the concept of learning analytics is gaining more and more importance in the context of (educational) research. Lot of people are talking about it and I just wanted to be sure what is it exactly in order to participate in discussions. But even more important is the fact that I should teach in next autumn the basics of learning analytics in Tallinn University master program “Educational technology” and I should expand my own knowledge before that.
LAK12 course defines learning analytics as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs”.
When I’ll try to put in my educational technology context, it means that we analyze different learning patterns in learning environments (open learning environments that are usually blog-based courses and closed LMS like IVA or Moodle). Such analyses may illustrate if the current learning activities, learning environment and materials support learners’ learning process. That is not the only potential of learning analytics, sure.
I have wondered, what is the difference or what is the relationship between data-mining and learning analytics. I read from the reading material that The Educational Data Mining community has defined educational data mining as 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.” The implementation areas of educational data mining and learning analytics are similar. I have to still work with this thought as currently I can’t perceive the thorough difference.
I liked the idea that I read from this material, said by Donald Norris, president and founder of Strategic Initiatives, Inc:
“Online learning without embedded analytics is like a car without wheels,” says Norris, who has written many white papers on the subject. “Embedded analytics turns online learning into an engine for both scaling access and improving retention, persistence, and completion.” Online learning courses are my area and so far no element of analytics I have used. Sure, my courses are small and just about 10 students are participating so I am not sure how efficiently the learning analytics could be used there. That takes me to my second hesitation, what is the real practice that can be studied with learning analytics. On one hand I can analyze the community aspect – how communicates with whom and do students comment each other. Maybe I could study if the learning materials are considered important – how many clicks on materials, comments and ping-backs. I could study the presence of student – how often does she visit the learning environment at all and posts assignments. But what else..? I hope to find an answer to it.