Group items tagged

"Because students come to the course for many different reasons, course designers should make it easier for learners to meet a variety of objectives. Since many participants in online courses may just want to learn a few new things, we can help them by releasing all course content at the outset of the course and enabling them to search for specific topics of interest. as course designers, we should be paying more attention to creating effective, relevant activities than focusing so heavily on course content. We hypothesize that learners also use activities' instant feedback to help them determine whether they should spend time reviewing the associated content  We also believe that we haven't given enough weight to teaching learners how to evaluate their own work. We plan to keep experimenting with self-evaluation in future courses."

"Because students come to the course for many different reasons, course designers should make it easier for learners to meet a variety of objectives. Since many participants in online courses may just want to learn a few new things, we can help them by releasing all course content at the outset of the course and enabling them to search for specific topics of interest. as course designers, we should be paying more attention to creating effective, relevant activities than focusing so heavily on course content. We hypothesize that learners also use activities' instant feedback to help them determine whether they should spend time reviewing the associated content  We also believe that we haven't given enough weight to teaching learners how to evaluate their own work. We plan to keep experimenting with self-evaluation in future courses."

Keith Devlin provides detailed insights into his increasing focus on "learning by evaluation" in the third run of his "Introduction to Mathematical Thinking" Coursera MOOC, which starts on 2 September.

The usual thoughtful stuff from Keith Devlin about learning maths - in this case "Quantitative Reasoning" using MOOCs.

It gets a bit proselytising towards the end but the notion of evaluating proofs could generalise to evaluating other types of mathematical statement so, although we are not interested in mathematical proof in our course, the article could still have some relevance to us.

4 page PDF from a Stanford group including the venerable Roy Pea. Might be relevant to several aspects of our project. Focuses on the question "How can we make a MOOC work for as many of its diverse participants as possible?". Argues for the use of A/B testing to inform MOOC design. Silent on adaptive learning. Still pretty tentative, though.

Several angles of interest on this, from our own perspective (as prospective uses of data) and that of our prospective learners

Useful resources - especially the linked slideshare presentation - from Tony Hirst, providing pointers to tools and techniques for making use of learning analytics