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Algorithm Visualization (AV) systems make available to learners multiple, dynamic and interactive visualizations of the changes that data sets undergo when some algorithm is applied on them. The main reason for developing AV systems is because there are significant limitations in the representations traditionally used for presenting algorithm operations (Duchowski & Davis, 2007; Khuri, 2001). Reviewing the literature in the field of AV systems has revealed that despite of the initial enthusiasm of the scientific community on the subject, AVs have not managed to deliver as positive results as expected (Hundhausen & Douglas, 2004). Certain impediments appeared on the practice of AV systems, as described in the next section, which prevented to meet the expectations in the teaching of algorithms. The plain involvement of an AV system in algorithm learning does not necessarily empower instructors and learners to overcome the challenges in AV learning (Hundhausen & Brown, 1998). Nevertheless, students who used interactive AV systems in active learning conditions (i.e., with the prospect to interact, predict and create mental models of the algorithms), in general, outperformed students, which simply watched a representation of the algorithm in a computer or a whiteboard (Khuri, 2001).
The focus of our research is to leverage the learning impact of an AV tool when used as support in online learning conditions. To guide students, get actively involved in the use of the AV system, when learning online, we resorted to the theory and practice of collaborative learning (Dillenbourg, 2003). Online collaborative learning activities in the computer science domain have been explored in many situations highlighting the need for group support and guidance to avoid detrimental peer interaction patterns (e.g., Liu & Tsai, 2008). It is strongly suggested that learning conditions can be improved when the collaborative activity is structured and guided by a collaboration script, which is a set of directions prescribing how the group members should interact, how they should collaborate and how they should solve a problem (Kollar, Fischer, & Hesse, 2006).
We expect that a guided collaboration will influence the students’ discourse towards a more substantial use of the AV system for experimentation and reflection, thus increasing the intrinsic feedback that the students get from using the system. Towards this direction we conducted, some initial, small-scale studies to validate our expectations on the impact of the collaboration script. In the following, we present the theoretical background of our work, the research method and results of the two studies. We further discuss our evidence indicating that an appropriate collaboration script can focus student discourse and activity in a way that increases beneficial intrinsic feedback relevant to the use of the AV system.