The debate around Learning Analytics seems to be opening up. And although there is little sign of agreement over future directions, the terms of discussion seem both broader and more nuanced than previously. I think some of this is in response to the disillusionment of early researchers and adopters.
In yesterdays OLDaily, Stephen Downes pointed to an excellent article by Bodong Chen. Bodong points to the surge of interest in Learning Analytics but cautions that: "The surge of this nascent field rests on a promise--and also a premise--that digital traces of learning could be turned into actionable knowledge to promote learning and teaching.
He suggests that: "One approach to understanding learning analytics is to recognize what are not learning analytics” including academic analytics and educational data mining. Instead, he says "learning analytics is more directly concerned with teachers and learners by attending to micro-patterns of learning."
Bodong draws attention to a tension between learning and analytics "as two pivotal concepts of the field” He points out that "learning analytics deals with educational phenomena at multiple levels”. As an example he says: "collaborative knowledge building as a group phenomenon depends on contributions from individuals, but cannot be reliably inferred from individual learning."
Understanding and accepting that "the meaning of learning analytics as a term is plural and multifaceted” is an important basis for future research. Within the only just emerging field of workplace Learning Analytics, not only is there the issue of individual and collaborative learning and knowledge development but also issues around proxies for learning. Whilst performance in practice might be seen as a possible proxy, performance may also be seen to involve a wider range of factors, including the working environment, the division of work and opportunities for practice. And the already established field of Performance Analytics seems at considerable tension to learning.