Abstract
Monitoring and guiding multiple groups of students in face-to-face collaborative work is a demanding task which could possibly be alleviated with the use of a technological assistant in the form of learning analytics. However, it is still unclear whether teachers would indeed trust, understand, and use such analytics in their classroom practice and how they would interact with such an assistant. The present research aimed to find out what the perception of in-service secondary school teachers is when provided with a dashboard based on audio and digital trace data when monitoring a collaborative learning activity. In a vignette study, we presented twenty-one in-service teachers with videos from an authentic collaborative activity, together with visualizations of simple collaboration analytics of those activities. The teachers perceived the dashboards as providers of useful information for their everyday work. In addition to assisting in monitoring collaboration, the involved teachers imagined using it for picking out students in need, getting information about the individual contribution of each collaborator, or even as a basis for assessment. Our results highlight the need for guiding dashboards as only providing new information to teachers did not compel them to intervene and additionally, a guiding dashboard could possibly help less experienced teachers with data-informed assessment.
Highlights
Collaborative learning (CL) shows many benefits, having students work in a group does not automatically result in students’ deep learning and construction of knowledge (Stover & Holland, 2018)
We focused on studying relevance from the viewpoint of the decision-maker; Gill et al (2014) proposed diagnosticity as another important factor when looking into data-driven decision making. Would it possibly help the students in collaborative learning (CL) settings if teachers were to understand how they are currently making decisions based on nondiagnostic data every day? Our implication for further studies is testing the hypothesis that using technological assistants in the form of collaboration analytics helps teachers monitor and support students much more efficiently and effectively
As the results of our study revealed that gaining new information from the dashboard might decrease actionability, the system should be ready to provide some hints for intervention during the collaboration
Summary
Collaborative learning (CL) shows many benefits, having students work in a group does not automatically result in students’ deep learning and construction of knowledge (Stover & Holland, 2018). Even if teachers are in the same classroom as the students during a CL activity, they still have little to no information about what is happening. It is known that one teacher can moderate about four groups of three to four students in a face-to-face CL setting. If we go above those numbers, teachers may not be able to monitor and take into consideration the full complexity of group and individual functioning at the same time (Schwarz & Asterhan, 2011). The average class size according to the OECD in 2017 ranged from 15 to 33, meaning that one teacher would need to monitor and guide four to eight groups of quartets on average in a CL scenario. We should not expect teachers to be able to monitor the progress of each student
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