I have been pondering the last couple of weeks what type of data or patterns might one look for from learning analytics. There are lots of different projects I have seen or been involved in that are emerging:
- Retention focused – identifying learners at-risk of drop-out from the course;
- Performance focused – predicting final exam success;
- Activity focused – quantitative views of activity;
- Course focused – usually linked to a bench-marking of staff performance;
- Engagement focused – what types of things are people doing;
A further idea emerged for me when reading the NY Times article: ‘How Companies Learn Your Secrets‘. The article details how supermarkets might gather information about you. The main goal for shopper analytics is to identify approaching periods when consumer’s patterns are subject to change. For example the number one period for this is when a new baby is born, or in marketing terms when parents are ‘exhausted, overwhelmed and their shopping patterns and brand loyalties are up for grabs’. The approaching aspect is crucial here as the earlier an intervention occurs the more likely it is to beat other interventions, or in other words they more likely they are to switch to your store.
A similar model emerges in Vygotksy’s (1978) concept of the Zone of Proximal Development. Vygotsky proposes that for effective pedagogical interventions one must calculate at least two development levels: actual development – that which the learner can achieve unaided (e.g. tests) and potential development – that which the learner can achieve with support. The zone of proximal development is the difference between the two. Vygotsky argues that ‘by using this method we can take account of not only the cycles and maturation processes that have already been completed but also those processes that are currently in a state of formation, that are just beginning to mature and develop‘ (pg. 87).
The zone of proximal development refers to the maturing functions that are relevant for the next development period, and Chaiklin (2003) further clarifies that social interaction does not create these functions but provides conditions for identifying their existence and the extent they are developed. Interaction and social network analysis alongside behavioural psychology may offer insights while prompting some further thought on the design of interactions.
Vygotsky further suggests this requires a re-examination of formal subject disciplines and their relation to overall development. For Vygotsky this cannot be solved in a single formula and diverse research around the zone of proximal development is required. Fortunately learner analytics isn’t about a single formula either (despite its philosopher stone appeal) – semantically linked data allows diverse sets to be explored and may be directed at revealing the ‘ripeness’ of maturing functions. It seems such an approach to learning analytics (one focused on development) may require new approaches to designing learning environments, in which analytics are an integral tool rather than a retrospective analysis of existing data.
Chaiklin, S. (2003). The Zone of Proximal Development in Vygotsky’s Analysis of Learning and Instruction. In A. Kozulin, B. Gindis, V. S. Ageyev, & S. M. Miller (Eds.), Vygotsky’s Educational Theory in Cultural Context (pp. 39-64). Cambridge: Cambridge University Press.
Vygotsky, L. (1978). Mind in Society. Cambridge, MA and London: Harvard University Press.