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

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

A Multilevel Analysis of the Effect of Prompting Self-Regulation in Technology-Delivered Instruction

We used a within-subjects design and multilevel modeling in two studies to examine the effect of prompting self-regulation, an intervention designed to improve learning from technology-delivered instruction. The results of two studies indicate trainees who were prompted to self-regulate gradually improved their knowledge and performance over time, relative to the control condition. In addition, Study 2 demonstrated that trainees’ cognitive ability and self-efficacy moderated the effect of the prompts. Prompting self-regulation resulted in stronger learning gains over time for trainees with higher ability or higher self-efficacy. Overall, the two studies demonstrate that prompting self-regulation had a gradual, positive effect on learning, and the strength of the effect increased as trainees progressed through training. The results are consistent with theory suggesting self-regulation is a cyclical process that has a gradual effect on learning and highlight the importance of using a within-subjects design in self-regulation. research

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

The psychological dimension of transformation in teacher learning

Against a background which recognises pedagogical content knowledge as the distinctive element of teacher competence/expertise, this theoretical essay argues for its central construct - that of transformation – to be understood by teachers and teacher-educators in psychological terms (as was originally proposed by Dewey). Transformation requires teachers to fashion disciplinary knowledge such that it is accessible to the learner. It is argued that for transformation to happen, teacher thinking must include a sophisticated grasp of cognition and metacognition if teachers are to be characterised as competent, let alone expert. This article is written within a context of considerable social and academic scrutiny in the United Kingdom of the form and content of professional teacher preparation and development. In recent years the contribution of psychological knowledge to teacher-education has been filtered through procedural lenses of how best to 'manage classrooms', 'assess learning', 'build confidence' or whatever without a matched concern for psychological constructs through which such issues might be interpreted; thus leaving teachers vulnerable in their professional understandings of learning and its complexities. That society now requires high-level cognitive engagement amongst its participants places cognitive and metacognitive demands on teachers which can only be met if they themselves are conceptually equipped

Making sense: dopamine activates conscious self-monitoring through medial prefrontal cortex

When experiences become meaningful to the self, they are linked to synchronous activity in a paralimbic network of self-awareness and dopaminergic activity. This network includes medial prefrontal and medial parietal/posterior cingulate cortices, where transcranial magnetic stimulation may transiently impair self-awareness. Conversely, we hypothesize that dopaminergic stimulation may improve self-awareness and metacognition (i.e., the ability of the brain to consciously monitor its own cognitive processes). Here, we demonstrate improved noetic (conscious) metacognition by oral administration of 100 mg dopamine in minimal self-awareness. In a separate experiment with extended self-awareness dopamine improved the retrieval accuracy of memories of self-judgment (autonoetic, i.e., explicitly self-conscious) metacognition. Concomitantly, magnetoencephalography (MEG) showed increased amplitudes of oscillations (power) preferentially in the medial prefrontal cortex. Given that electromagnetic activity in this region is instrumental in self-awareness, this explains the specific effect of dopamine on explicit self-awareness and autonoetic metacognition

Toward a Theory of Learner-Centered Training Design: An Integrative Framework of Active Learning

[Excerpt] The goal of this chapter, therefore, is to develop an integrative conceptual framework of active learning, and we do this by focusing on three primary issues. First, we define the active learning approach and contrast it to more traditional, passive instructional approaches. We argue that the active learning approach can be distinguished from not only more passive approaches to instruction but also other forms of experiential learning based on its use of formal training components to systematically influence trainees\u27 cognitive, motivational, and emotion self-regulatory processes. Second, we examine how specific training components can be used to influence each of these process domains. Through a review of prior research, we extract core training components that cut across different active learning interventions, map these components onto specific process domains, and consider the role of individual differences in shaping the effects of these components (aptitude-treatment interactions [ATIs]). A final issue examined in this chapter concerns the outcomes associated with the active learning approach. Despite its considerable versatility, the active learning approach is not the most efficient or effective means of responding to all training needs. Thus, we discuss the impact of the active learning approach on different types of learning outcomes in order to identify the situations under which it is likely to demonstrate the greatest utility. We conclude the chapter by highlighting research and practical implications of our integrated framework, and we outline an agenda for future research on active learning