It has gone a bit quiet around Learning Objects recently. Now there is a good chance that they’ll make a comeback with new learning recommender technologies and methodologies.
It’s to do with recommending appropriate and relevant learning materials to learners as part of a remedial or supportive action. This requires two things: (1) knowing the text and (2) knowing the learner. The first bit may be by far the easier and currently there are good efforts underway to undertake qualitative text analyses with a view to recommend the best suited supportive materials for the purpose to the learner.
Several methodologies to identify the relevance of text with regards to specific learning domains are under development. Latent semantic analysis (LSA) is one of those, that together with ontologies, domain mapping, and corpora will be tested to see what can be achieved.
The idea is that, together with sophisticated learner positioning methods, a semantically driven system would pick the right needle from the learning material haystack and recommend this to the learner.