Students tackle the tasks on Learning in the Digital World (LDW), specifically the sub-area of Computational Problem Solving, in an interactive, digital environment in which they must carry out various activities. As students have varying levels of prior knowledge, each task consists of several phases.
During the Introduction phase, students learn what the objectives of the task are. It explains the subject area and the nature of the problem to be solved. In this phase, the virtual tutors who guide the students through the tasks introduce themselves.
In the Show phase, pupils are presented with tasks designed to assess their prior knowledge. It is only once their prior knowledge is known that it is possible to assess the extent to which the pupils’ learning has progressed.
During the Learn phase, students complete practice exercises which closely resemble the actual test questions. By doing so, they become familiar with the thematic context of the tasks, such as the various factors that influence an ecosystem. At the same time, they practise the specific skills that they will need in the subsequent application phase. One example of this is the ability to relate different factors to one another in order to understand their collective effect on an ecosystem.
The Apply phase constitutes the actual testing phase. Here, the students apply the skills they have practised to new scenarios. For example, different factors may be selected for a given ecosystem in the application phase than in the learning phase, in order to examine their combined influence. Further information is available to them within the system during this phase.
After the learning and application phases, students complete a brief Reflect phase, answering questions about how they assess their own performance, effort and feelings while completing the task. This allows self-regulated learning to be assessed.