Can questioning induce forgetting?:Retrieval-induced forgetting of eyewitness information

In eyewitness situations, questioning can be seen as a form of retrieval practice that may have detrimental effects on eyewitness memory. Memory research has demonstrated that retrieval practice may not only enhance memory for practiced information but also induce forgetting of related information. The present study examined the effect of retrieval practice on forgetting in eyewitness memory. First, we investigated whether asking questions about particular offender characteristics can induce forgetting of other offender characteristics. Second, we examined whether this forgetting effect is limited to information from the practiced offender or may also influence memory for characteristics of others present in the crime scene. Third, we studied whether forgetting of eyewitness information occurs in the absence of output interference effects. We found that questioning induced forgetting of offender characteristics. Moreover, the forgetting effect was not limited to information about the practiced offender. Finally, forgetting was found even when output order was experimentally controlled

Fostering expert learning strategies in novices

The studies reported in this dissertation were undertaken to shed light on some important issues that currently prevail in research on the development of expertise, and in research on fostering metacognitive processes in learners in particular. In general, the studies reported here were develo

Generating Keywords Improves Metacomprehension and Self-Regulation in Elementary and Middle School Children

Metacomprehension accuracy is typically quite poor; 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 for the delayed-keyword condition than for a control group. By contrast, for fourth graders, accuracy did not differ across conditions. Improved metacomprehension accuracy led to improved regulation of study

Приближенное решение нелинейной системы уравнений для двухфазных сред

Research on expository text has shown that the accuracy of students' judgments of learning (JOLs) can be improved by instructional interventions that allow students to test their knowledge of the text. The present study extends this research, investigating whether allowing students to test the knowledge they acquired from studying a worked example by means of solving an identical problem, either immediately or delayed, would enhance JOL accuracy. Fifth grade children (i) gave an immediate JOL, (ii) a delayed JOL, (iii) solved a problem immediately and then gave a JOL, (iv) solved a problem immediately and gave a delayed JOL, or (v) solved a problem at a delay and then gave a JOL. Results show that problem solving after example study improved children's JOL accuracy (i.e., overestimation decreased). However, no differences in the accuracy of restudy indications were found. Results are discussed in relation to cue utilization when making JOLs

Checklists improve experts' diagnostic decisions

Context Checklists are commonly proposed tools to reduce error. However, when applied by experts, checklists have the potential to increase cognitive load and result in expertise reversal'. One potential solution is to use checklists in the verification stage, rather than in the initial interpretation stage of diagnostic decisions. This may avoid expertise reversal by preserving the experts' initial approach. Whether checklist use during the verification stage of diagnostic decision making improves experts' diagnostic decisions is unknown. Methods Fifteen experts interpreted 18 electrocardiograms (ECGs) in four different conditions: undirected interpretation; verification without a checklist; verification with a checklist, and interpretation combined with verification with a checklist. Outcomes included the number of errors, cognitive load, interpretation time and interpretation length. Outcomes were compared in two analyses: (i) a comparison of verification conditions with and without a checklist, and (ii) a comparison of all four conditions. Standardised scores for each outcome were used to calculate the efficiency of a checklist and to weigh its relative benefit against its relative cost in terms of cognitive load imposed, interpretation time and interpretation length. Results In both analyses, checklist use was found to reduce error (more errors were corrected in verification conditions with checklists [0.29 +/- 0.77 versus 0.03 +/- 0.61 errors per ECG], and fewer net errors occurred in all conditions with checklists [0.39 +/- 1.14 versus 1.04 +/- 1.49 errors per ECG];

Synthesizing cognitive load and self-regulation theory: a theoretical framework and research agenda

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 selfregulated 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