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

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

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

Metacognition for spelling in higher etudents with dyslexia: is there evidence for the dual burden hypothesis?

We examined whether academic and professional bachelor students with dyslexia are able to compensate for their spelling deficits with metacognitive experience. Previous research suggested that students with dyslexia may suffer from a dual burden. Not only do they perform worse on spelling but in addition they are not as fully aware of their difficulties as their peers without dyslexia. According to some authors, this is the result of a worse feeling of confidence, which can be considered as a form of metacognition (metacognitive experience). We tried to isolate this metacognitive experience by asking 100 students with dyslexia and 100 matched control students to rate their feeling of confidence in a word spelling task and a proofreading task. Next, we used Signal Detection Analysis to disentangle the effects of proficiency and criterion setting. We found that students with dyslexia showed lower proficiencies but not suboptimal response biases. They were as good at deciding when they could be confident or not as their peers without dyslexia. They just had more cases in which their spelling was wrong. We conclude that the feeling of confidence in our students with dyslexia is as good as in their peers without dyslexia. These findings go against the Dual Burden theory (Kruger & Dunning, 1999), which assumes that people with a skills problem suffer twice as a result of insufficiently developed metacognitive competence. As a result, there is no gain to be expected from extra training of this metacognitive experience in higher education students with dyslexia

Do Metacognitive Strategies Improve Student Achievement in Secondary Science Classrooms?

Increasing prevalence of high-stakes testing calls for focus on value-added teaching and learning practices. Following is an inquiry regarding metacognitive teaching and learning practices as it pertains to secondary science classrooms. Research shows that the orchestration and inclusion of metacognitive strategies in the science classroom improve achievement under the following preconditions: (1) are pervasively embedded in the educational structure; (2) are part of appropriately rigorous and relevant curriculum; (3) are supported by ‘metacognitive friendly’ teaching strategies; (4) are explicitly practiced by students and teachers; and (5) enable students to take responsibility for their own learning

Higher-order thoughts in action : Consciousness as an unconscious re-description process

Peer reviewedPostprin

Active Learning: Effects of Core Training Design Elements on Self-Regulatory Processes, Learning, and Adaptability

This research describes a comprehensive examination of the cognitive, motivational, and emotional processes underlying active learning approaches, their effects on learning and transfer, and the core training design elements (exploration, training frame, emotion-control) and individual differences (cognitive ability, trait goal orientation, trait anxiety) that shape these processes. Participants (N = 350) were trained to operate a complex computer-based simulation. Exploratory learning and error-encouragement framing had a positive effect on adaptive transfer performance and interacted with cognitive ability and dispositional goal orientation to influence trainees’ metacognition and state goal orientation. Trainees who received the emotion-control strategy had lower levels of state anxiety. Implications for developing an integrated theory of active learning, learner-centered design, and research extensions are discussed

Towards a quantitative evaluation of the relationship between the domain knowledge and the ability to assess peer work

In this work we present the preliminary results provided by the statistical modeling of the cognitive relationship between the knowledge about a topic a the ability to assess peer achievements on the same topic. Our starting point is Bloom's taxonomy of educational objectives in the cognitive domain, and our outcomes confirm the hypothesized ranking. A further consideration that can be derived is that meta-cognitive abilities (e.g., assessment) require deeper domain knowledge

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

Self-regulated learning in higher education : identifying key component processes

The concept of self-regulated learning is becoming increasingly relevant in the study of learning and academic achievement, especially in higher education, where quite distinctive demands are placed on students. Though several key theoretical perspectives have been advanced for self-regulated learning, there is consensus regarding the central role played by student perceptions of themselves as learners. There are two general aims of this positional article. The first is to emphasise self-regulated learning as a relevant and valuable concept in higher education. The second is to promote the study of those constituent elements considered most likely to develop our understanding beyond a mere description of those processes thought to be involved in self-regulated learning. A case is presented for learning style, academic control beliefs and student self-evaluation as key constructs which contribute to an increased understanding of student self-regulated learning and which facilitate the application of self-regulated learning in pedagogy by enhancing its tangibility and utility