Computer generated feedback can support learning in unknown contexts

Simple statistics on our behavior on the web can show us what we are doing, can make us aware of our learning process and can influence our internet and learning behavior. This is one of the conclusions of PhD research of CELSTEC's Christian Glahn. He'll defend his thesis on 18 September 2009 at 13.30 hours at Open Universiteit Nederland in Heerlen.

Visualizing
While we are active on the internet, we leave traces, be it in learning environments, in online communities, or social networks. Based on these traces, the computer can generate simple statistics that visualize our behavior. This feedback makes us aware that we are learning, whether we intended to or not. This awareness can help us to reflect about our activities and to improve them.

Online tools
Christian Glahn developed in his experiments a few online tools. These tools make use of information on our day-to-day activities on the internet that is already available. They generate simple statistics that give a person contextualized feedback on his online activities. This feedback can include interests or behaviour on the internet. The idea is that the visualization of these simple, quantitative figures, raises attention to otherwise unconscious processes. By making these implicit activities and interests explicit, a person becomes more aware of what he is doing. By studying the feedback, a person learns about the own behaviour and becomes aware of hidden learning processes.

Individual bookmarking
One of the tools is based on Delicious.com, a free web-based social bookmarking service. Users of Delicious.com can organize and categorize their bookmarks by using ‘tags’ and allows to share them with other users. The tool developed by Glahn visualizes the Delicious.com tags of a single user in a so called tag-cloud. This tag-cloud shows how often he has used a certain tag in general and which are his newest bookmarks. This way he sees what topics are important for him at a given moment and how his personal interest changes over time. The experiments indicated that this visualization helps Delicious.com users to understand and evaluate how they organize their bookmarks and helps them to identify topics and tasks for optimising their information management of web-favourites.

Group behaviour
A second tool was a group information system (team.sPace). This is a news portal for small groups and communities. The tool generates a score for each user based on his activity within the portal: the number of bookmarks a user has made, how many articles on web-logs he has written, and also the resources of other group members that he has read. The tool shows this score in comparison with the score of others. The visualisation helped the participants to ‘learn’ about the relations in the group and about the relevant topics that are shared among the group members. Furthermore, the participants started more actively contributing valuable resources, compared to a control group.

Although the visualization did not make any reference to content or quality, it increased the awareness of people on implicit group dynamics and motivated them to participate.
However, this effect was not found for all participants, but only with a group of participants that was similar in their participation style. For those who are not very active, the feedback is distracting though it does lead to awareness. For more active participants it did stimulate their participation and collaboration. Therefore, it appears that the supportive benefits of the tool are context dependent. 

Conclusions
Glahn concludes among other things that it is possible to make people aware of implicit behaviour, interests and learning processes by giving them feedback based on purely statistic data. But it is important to consider contrast and perspective that are related to the context in which the feedback is provided. Such feedback leads to self-consciousness in information management, learning, and group work. Depending on the context, the feedback can also motivate to learn.

Knowledge management
The conclusions of this PhD research are important for example for the field of knowledge management. The tools make users aware of their competences and their routines. This can help employees to develop a consistent concept of their competences, interests, and skills. In group situations it makes them also aware of the competencies of others. All this helps them in finding the right person and to better use the social capital that is present in an organization.