There is no proven direct effect between the availability of this form of learning analytics and learning outcomes. Leeuwen, A. van, Janssen, J., Erkens, G. (2014) Effecten van learning analytics bij computer ondersteund samenwerkend leren, Kennisnet, 4W Issue 4-2014
4W Issue 4-2014
When students work together in a computer-assisted learning environment, it is difficult to get a good picture of the progress of the groups. Learning analytics, where data on the learning activities of students are displayed graphically, helps teachers to better guide the groups and make students aware of the cooperation process. The expectation is that insight into the course of the cooperation process contributes not only to better cooperation, but also results in better educational results.
It is of all times: in a group assignment one of the group members is taking the task not serious and as a result a part of the assignment stagnates and / or more work ends up on the shoulders of others. As a teacher you hear this often afterwards, when the assignment has already been submitted. In group assignments in a computer-assisted learning environment these kind of obstacles already should have come to light in an earlier stage as the teacher can watch the cooperation process, thanks to the information gathered by the computer system on activities of students. In practice, however, the amount of information collected is so large that teachers cannot see the trees from the forest. By visualizing relevant data, the information is much more manageable: students see from each other how much everyone contributes and the teacher understands the process. This graphical representation of student activities is a form of learning analytics.
Effect of learning analytics on guidance by the teacher
Teachers can get feed back from the system on the activities of the students in the form of visualizations as well. Can they can better assist students with this information (arrow 3 -> 4 in Figure 1)? Our research on the Participation Tool (Van Leeuwen et al.) shows that teachers, thanks to information of the individual contributions of group members, can better detect imbalances in the groups and act on them. Then they seem to send relatively more messages to groups where participation is problematic then to groups in which this is not the case. In addition, their assessment of the participation is more specific because they can accurately identify which group member does not participate proportionally.
In a study completed at the time, teachers were given information about which task-relevant key words students use in their discussions (Draft Trail Tool) and to which extent they made progress on the task. The result was that teachers in general were sending more messages, and again often to groups with task problems, for instance, when there was discussions about things other than the subject of the task.
The presence of learning analytics not only seems to assist teachers in keeping an eye on the problems, but also to activate them to provide help to groups with problems.
Effect of learning analytics on learning outcomes
In summary, we can conclude that learning analytics have beneficial effects on the course of collaboration. Understanding participation ensures that the attitude of students changes and becomes more active, as well as the guidance by the teachers. Reasoning back, it was expected that this would also lead to better learning outcomes (arrow 5 in Figure 1). Is that the case? No, this expectation is to date not supported by research: there is no proven direct effect between the availability of this form of learning analytics and learning outcomes. All students have a better understanding of the participation of their group members, and although teachers can guide the groups better on the basis of learning analytics, it does not provide better group outcomes, nor a better individual performance. Therewith the added value of learning analytics is demonstrable for the cooperation process, but not for the learning outcomes.