Although in learner-controlled instruction, learners are given the opportunity to set their own learning trajectory (Corbalan, Kester, & Van Merriënboer, 2006), this leads to no improvement or even hampers performance according to empirical results (e.g., Mihalca, Salden, Corbalan, Paas, & Miclea 2011). A possible explanation for why learners, especially low prior knowledge students, do not benefit from learner control is that they are unable to accurately monitor, and assess their own performance as well as select an appropriate new learning task, in other words, do not possess the necessary self-directed learning (SDL) skills (Knowles, 1975). These skills are important prerequisites for implementing learner-controlled instruction successfully (Kostons, Van Gog, & Paas, 2010).

Accurate monitoring, self-assessment and task selection seem to be especially difficult for novices, presumably not only because of their lack of prior knowledge and additional cognitive demands, but also because of the lack of knowledge about performance criteria and standards (Van Gog & Paas, 2009). However, very little research has been conducted on exploring in-depth how students with different prior knowledge levels self-assess their performance, select new tasks and regulate their own learning in electronic learner-controlled environments. Therefore, the purpose of this study was to provide insight into the differences in self-assessment and task selection processes between low and high prior knowledge students engaged in an electronic learner-controlled environment designed according to the 4C/ID methodology (Van Merriënboer, 1997).

In this electronic environment, students have full control over the whole learning process, including the assessment of their own performance and the selection of learning tasks. Regarding the task selection process, students could select whatever task they want from a database with descriptions of all 45 genetics tasks available, which represent a combination of five difficulty levels (from low to high), three support levels (high, low and no support), and three different surface features (i.e., cover stories).

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