An exponential increase in the availability of information over the last two decades has asked for novel theoretical frameworks to examine how students optimally learn under these new learning conditions, given the limitations of human processing ability. In this special issue and in the current editorial introduction, we argue that such a novel theoretical framework should integrate (aspects of) cognitive load theory and self-regulated learning theory. We describe the effort monitoring and regulation (EMR) framework, which outlines how monitoring and regulation of effort are neglected but essential aspects of self-regulated learning. Moreover, the EMR framework emphasizes the importance of optimizing cognitive load during self-regulated learning by reducing the unnecessary load on the primary task or distributing load optimally between the primary learning task and metacognitive aspects of the learning task. Three directions for future research that derive from the EMR framework and that are discussed in this editorial introduction are: (1) How do students monitor effort? (2) How do students regulate effort? and (3) How do we optimize cognitive load during self-regulated learning tasks (during and after the primary task)? Finally, the contributions to the current special issue are introduced.

The ability to monitor understanding of texts, usually referred to as metacomprehension accuracy, is typically quite poor in adult learners; however, recently interventions have been developed to improve accuracy. In two experiments, we evaluated whether generating delayed keywords prior to judging comprehension improved metacomprehension accuracy for children. For sixth and seventh graders, metacomprehension accuracy was greater when generating keywords. By contrast, for fourth graders, metacomprehension accuracy did not differ across conditions. Improved metacomprehension accuracy led to improved regulation of study. The delayed keyword effect in children reported here is discussed in terms of situation model activation.

To examine four theories on the role of basic science knowledge and clinical knowledge in diagnostic reasoning. In 2000–01, the authors tested the basic science and clinical knowledge and diagnostic performances of 59 family physicians and 184 second- to sixth-year medical students at Maastricht University, The Netherlands. Structural equation modeling was used to analyze the data. Four theoretical models were tested. In the first model only basic science knowledge is involved in diagnostic reasoning; in the second model only clinical knowledge is related to diagnostic reasoning; in the third model, clinical knowledge is related to diagnostic reasoning, but basic science knowledge is integrated in clinical knowledge; and in the fourth model, both basic science knowledge and clinical knowledge independently influence diagnostic reasoning. Forty-four (75%) of the family physicians and 184 (100%) of the students responded. The results indicated that the third model, which is based on the knowledge encapsulation theory, provided the best fit to the data, whereas the models that had directly related basic science knowledge with diagnostic performance did not fit the data adequately. The results generally supported the third model by Schmidt and Boshuizen of knowledge encapsulation theory suggesting that basic science knowledge is activated in expert diagnostic reasoning through its relation with clinical knowledge.