Collecting, processing and presenting activity data
In order to work with activity data it is necessary to collect the data, it then needs to be processed and this will depend on the types of data being collected and the purposes for which it is being collected. Finally the data is likely to have to be visualised in some way in order to help users to understand the large volumes of data. We look at each of these in turn.
- Collecting activity data Here there are issues to do with the data needed for analysis tasks, its quality and completeness, its formats, and any specialist tools are required to collect it.
- Processing activity data to obtain useful results Two simple topics under this heading are aggregation and filtering of data. A more complex areas is the construction of recommendation algorithms, both to recommend resources and to identify students at risk. There is some other 'catch all' analysis that might be undertaken.
- Presenting the results of activity data use Primarily questions of visualisation of activity data for diverse purposes, including early exploration. There are also questions of optimal user interfaces to recommender systems.