Scott points at an interesting online document from Utah State’s Reusability, Collaboration, and Learning Troupe, on an issue troubling lots of folks trying to implement LOs here at UBC, and hones in on the key insight… (emphases mine)
The purpose of learning objects and their reality seem to be at odds with one another. On the one hand, the smaller designers create their learning objects, the more reusable those objects will be. On the other hand, the smaller learning objects are, the more likely it is that only humans will be able to assemble them into meaningful instruction. From the traditional instruction point of view, the higher-level reusability of small objects does not scale well to large numbers of students (i.e., it requires teachers or instructional designers to intervene), meaning that the supposed economic advantage of reusable learning objects has evaporated.
…it would seem that there are only two options: throw out the learning objects notion altogether, or encourage the development and use of only large objects, settling for their limited reusability. There is, however, another option.
The only quantity certain to scale with large numbers of students is the number of students. If a more constructivist view of learning is admitted, small, highly reusable objects can be brought to bear on instructional problems without suffering from scalability issues. This could be accomplished by creating learning environments in which learners interact directly with the small objects, manipulating and combining them to construct meaning for themselves.
That last bit a nod presumably to David Wiley’s work on Online self-organizing social systems, though it can easily apply to any number of constructivist models.
I love this bit from “The Reusability Paradox’s” conclusion:
the method learning object proponents have evangelized as facilitating reusability of instructional resources may in fact make them more expensive to use than traditional resources. We have demonstrated that the automated combination of certain types of learning objects can in fact be automated. However, it would appear that the least desirable relationship possible exists between the potential for learning object reuse and the ease with which that reuse can be automated: the more reusable a learning object is, the harder its use is to automate.
