Metacognition comprises both the ability to be aware of one’s cognitive processes (metacognitive knowledge) and to regulate them (metacognitive control). Research in educational sciences has amassed a large body of evidence on the importance of metacognition in learning and academic achievement. More recently, metacognition has been studied from experimental and cognitive neuroscience perspectives. This research has started to identify brain regions that encode metacognitive processes. However, the educational and neuroscience disciplines have largely developed separately with little exchange and communication. In this article, we review the literature on metacognition in educational and cognitive neuroscience and identify entry points for synthesis. We argue that to improve our understanding of metacognition, future research needs to (i) investigate the degree to which different protocols relate to the similar or different metacognitive constructs and processes, (ii) implement experiments to identify neural substrates necessary for metacognition based on protocols used in educational sciences, (iii) study the effects of training metacognitive knowledge in the brain, and (iv) perform developmental research in the metacognitive brain and compare it with the existing developmental literature from educational sciences regarding the domain-generality of metacognition.

The present study examines the effectiveness of an online standardized treatment of posttraumatic stress and pathological grief administered through the Internet. Twenty students who had experienced traumatic life events and showed the symptoms of posttraumatic stress participated in the study. They received credit course points for inclusion in the research. Treatment consisted of 10 writing sessions (45 minutes each) during a period of 5 weeks. Participants were assessed at pretreatment, posttreatment, and after six weeks (follow-up). The participants improved strongly from pre- to post-treatment on posttraumatic stress and pathological grief symptoms and in psychological functioning. These improvements were sustained during the follow-up period. Moreover, 19 of the 20 participants were clinically recovered after treatment. The changes in posttraumatic stress symptomatology were compared post hoc to changes in control and experimental groups from trials on similarly protocolled but face-to-face treatment of posttraumatic stress.

a b s t r a c t a r t i c l e i n f oEasy to use workbenches for Qualitative Reasoning and modelling have been virtually nonexistent. This has a limiting effect on the use of this Artificial Intelligence technology and its uptake by a larger audience. We present Garp3, a user-friendly workbench that allows modellers to build, simulate, and inspect qualitative models of system behaviour. The workbench employs diagrammatic representations for users to interact with model content and simulation results, and provides seamless interoperability between the different modes of use. Domain experts can use Garp3 to create conceptual models in situations where numerical information is sparse or unavailable, or when they want to formalise their conceptual understanding of how systems behave. Garp3 can be applied to stakeholder management or dissemination activities to illustrate and explain phenomena, and facilitate discussion among participants. The workbench can also be used in formal education to have learners express concepts, or interact with existing models, and support them in developing their understanding of 'how things work'. Garp3 incorporates a range of techniques from Artificial Intelligence known as knowledge-based techniques. The main goal of this paper is to present the representation and reasoning methods of these techniques as they have been developed and fine-tuned within the Garp3 workbench. The focus hereby is on the symbolic, non-numerical calculations that are required to generate the state-graph of a system's behaviour efficiently, while taking into account that users need to be able to track and understand this reasoning, both in terms of the end result and the intermediate results it delivers.

No abstract