Metacognitive Development and Conceptual Change in Children

There has been little investigation to date of the way metacognition is involved in conceptual change. It has been recognised that analytic metacognition is important to the way older children acquire more sophisticated scientific and mathematical concepts at school. But there has been barely any examination of the role of metacognition in earlier stages of concept acquisition, at the ages that have been the major focus of the developmental psychology of concepts. The growing evidence that even young children have a capacity for procedural metacognition raises the question of whether and how these abilities are involved in conceptual development. More specifically, are there developmental changes in metacognitive abilities that have a wholescale effect on the way children acquire new concepts and replace existing concepts? We show that there is already evidence of at least one plausible example of such a link and argue that these connections deserve to be investigated systematically

Metacognition and Reflection by Interdisciplinary Experts: Insights from Cognitive Science and Philosophy

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article

A holistic model to infer mathematics performance: the interrelated impact of student, family and school context variables

The present study aims at exploring predictors influencing mathematics performance. In particular, the study focuses on internal students' characteristics (gender, age, metacognitive experience, mathematics self-efficacy) and external contextual factors (GDP of school location, parents' educational level, teachers' educational level, and teacher beliefs). A sample of 1749 students and 91 teachers from Chinese primary schools were involved in the study. Path analysis was used to test the direct and indirect relations between the predictors and mathematics performance. Results reveal that a large proportion of mathematics performance can be directly predicted from students' metacognitive experiences. In addition, other student characteristics and contextual variables influence mathematics performance in direct or indirect ways

How might teachers enable self-confidence? A review study

In the context of learner-centred learning and curricular reform, self-confidence is invoked as an important construct. However, there is no easily available research-informed guidance on what self-confidence means for the professional teacher. This study uses the analytic technique of Concept Analysis to review psychology and education literatures to provide a 'take-home' message for teachers. The review identifies conceptual artefacts (ideas, theories, concepts which explain, connect, predict or apply knowledge) that the teacher can appropriate in order to enable learner self-confidence. These conceptual artefacts are classified in three groups: characterising self-confidence; self-judgements of confidence; and factors that influence the development of self-confidence. The review finds self-confidence to be a robust and stable psychological construct, best promoted through teachers' attention to learners' development of knowledge and engagement in socially designed learning activities. It further finds that teachers' attention to activities which involve learners' self-regulation are of importance

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Socialising Epistemic Cognition

We draw on recent accounts of social epistemology to present a novel account of epistemic cognition that is ‘socialised’. In developing this account we foreground the: normative and pragmatic nature of knowledge claims; functional role that ‘to know’ plays when agents say they ‘know x’; the social context in which such claims occur at a macro level, including disciplinary and cultural context; and the communicative context in which such claims occur, the ways in which individuals and small groups express and construct (or co-construct) their knowledge claims. We frame prior research in terms of this new approach to provide an exemplification of its application. Practical implications for research and learning contexts are highlighted, suggesting a re-focussing of analysis on the collective level, and the ways knowledge-standards emerge from group-activity, as a communicative property of that activity

Metacognition and transfer within a course or instructional design rules and metacognition

A metacognitive strategy for doing research, included transfer, was taught in a course of nine afternoons. The success of this course raised some questions. How do the students learn? How does metacognition play a role? The course was designed in accordance with several instructional principles. The course was divided into three domains in which the strategy was introduced, practised, and applied respectively. Literature research revealed four possible metacognitive variants that correlate so it was supposed that implementing them all helped to reach the objectives of the course. The relation of the metacognitive variants with the instructional principles is described. To study learning the students were divided into three groups (weak, moderate, good) by their marks for other courses. The performance of the groups in each domain was monitored by their marks, scoring of metacognitive skills, questionnaires, observations, and time keeping. The moderate students scored as high as the good ones for the strategy in the last domain, a unique result. The metacognitive development of the other metacognitive skills was not linear. The conclusions are that the success of this course can be explained by a system of double sequencing and an interaction of all metacognitive variants, and that instructional design rules for metacognitive and cognitive objectives are differen