MMOC LAK12 ending

Well, the MOOC Learning Analytics and Knowledge 2012 course has just ended. I would love to have an ongoing weekly list of readings and interactive session of interesting participants and presenters. What a treat it has been.

The course did a good job (thank you George Siemens!) in introducing learning analytics, differentiating from big data and academic analytics, and giving up-to-the-minute information on different types of LA deployments in the education field.

Analytics in education has a diverse background and is now invovlving computer scientists, psychologists, statisticians, and psychologists working closely on various projects. These stages of implementation were all discussed:
*Extracting and analyzing data from learning management systems
*Building an analytics matrix that incorporates data from multiple sources (social media, LMS, student information systems, etc).
*Profile or model development of individual learners (across the analytics matrix)
*Predictive analytics: determining at-risk learner
*Automated intervention and adaptive analytics: i.e. the learner model should be updated rapidly to reflect near real-time learner success and activity so that decisions are not made on out-dated models
*Development of "intelligent curriculum" where learning content is semantically defined
*Personalization and adaptation of learning based on intelligent curriculum where content, activities, and socia connections can be presented to each learner based on her profile or existing knowledge
*Advanced assessment: comparing learner profile with architecture of knowledge in a domain for grading or assessment (see the image below taken from the article previously discussed, Penetrating the Fog).

Assessment through analytics in the article is presented this way:

This is an exciting concept: visualizing the data -- about what is learned and how, about the learner -- and using this data to enrich the teaching and learning process. LA seems to be being used a lot for assessing and helping at-risk students in traditional course settings in high school or college. Although this may be useful, I see the power of LA to give the interested learner data about self and others and the learning s/he wishes to accomplish. Learning how to learn, strengthening one's awareness of and one's own learning dimensions, as well as making recommendations for ways to interact with knowledge and experts in your field, may be fine tuned to learner preferences and learning goals. This is especially interesting for the field sometimes referred to as "life long learning". This is what we are doing all of our lives, but many times school may not address how to learn. This is unfortunate, because that is the most useful skill. Once one knows how to learn, one can learn what is needed for new jobs, new opportunities, new hobbies or interests, when one needs it (just in time learning). We know this is the way of the world now and in the future, and we need to prepare our learners not to be spoon fed by traditional classroom settings.