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Higher education, a field that gathers an astonishing array of data about its "customers," has traditionally been inefficient in its data use, often operating with substantial delays in analyzing readily evident data and feedback. Evaluating student dropouts on an annual basis leaves gaping holes of delayed action and opportunities for intervention. Organizational processes-such as planning and resource allocation-often fail to utilize large amounts of data on effective learning practices, student profiles, and needed interventions.

I have to admit that it was very hard to put into a few short words my thoughts on adaptive learning. I didn't really intend for it to center on the testing piece but I guess that is what the editors thought hadn't already been covered, although I do agree with everything I said on it. Of course, many will say we need much more than testing but I think the big point is that pencil and paper don't cut it. We are wasting time with how we test now and can be much more targeted in terms of what students know and how we can teach. Your thoughts? The biggest thing that bothers me about all these apps is that we have no learning analytics - no feedback loop at all to parents or teachers. I literally have to watch my son play his ipad learning games to really understand where he is and what I need to do to fill things in. 

Learning analytics are underused but will be one of the most important tools in our online toolbox. Once we grasp the importance of these, we will be demanding more and more intelligence on behalf of the learning analytics that we use to support elearning, apps, and all of the things our students use as part of their learning toolbox. Reports from Educause