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

Aceitabilidade de extratos de soja obtidos a partir de 13 cultivares desenvolvidas pela embrapa soja.

O extrato de soja está presente em grande parte das bebidas à base de soja, cujo mercado vem crescendo a taxas elevadas em todo o mundo, devido a características de conveniência (pronto para beber), saudabilidade (sem lactose e gorduras saturadas) e diversificação (multiplicidade de sabores) do produto. Os fabricantes de extrato de soja necessitam de cultivares cujos grãos resultem em bebidas de boa aceitação sensorial. Neste trabalho, 13 cultivares desenvolvidas pela Embrapa Soja foram avaliadas quanto à aceitação sensorial de seus extratos, por meio de uma equipe de 60 consumidores. As cultivares BRS 212, 215, 230 e 231, seja por sua nota média de aceitação e/ou por preferência, distinguiram se das demais cultivares testadas em relação ao potencial para a produção de extrato de soja. Assim, constituem-se em boas opções de matéria prima para os fabricantes de extrato, podendo atender diferentes segmentos de consumidores

State-owned enterprises as knowledge-explorer agents

This paper deals with the role of the State Owned enterprises (SOEs) in innovation processes. Only a few studies focus on the contribution SOEs as companies might give to produce new knowledge and technological innovation. We argue, however, that SOEs are a pillar of the innovation process and we explore conditions that can make SOEs very effective. Through two in-depth case studies in two different industries (STMicroelectronics in the semiconductor and Thales Alenia Space in the space industry) we illustrate how SOEs can contribute to innovation by exploring new opportunities and recombining different sources of knowledge. We highlight the conditions that can make exploration and recombination possible. We also highlight the ability of the two companies to change their boundaries through a continuous wave of agreements, mergers and acquisitions. This way, they were able to expand beyond their domains in a way that matched the evolution of their original industries

Abstract, emotional and concrete concepts and the activation of mouth-hand effectors

According to embodied and grounded theories, concepts are grounded in sensorimotor systems. The majority of evidence supporting these views concerns concepts referring to objects or actions, while evidence on abstract concepts is more scarce. Explaining how abstract concepts such as ‘‘freedom’’ are represented would thus be pivotal for grounded theories. According to some recent proposals, abstract concepts are grounded in both sensorimotor and linguistic experience, thus they activate the mouth motor system more than concrete concepts. Two experiments are reported, aimed at verifying whether abstract, concrete and emotional words activate the mouth and the hand effectors. In both experiments participants performed first a lexical decision, then a recognition task. In Experiment 1 participants responded by pressing a button either with the mouth or with the hand, in Experiment 2 responses were given with the foot, while a button held either in the mouth or in the hand was used to respond to catch-trials. Abstract words were slower to process in both tasks (concreteness effect). Across the tasks and experiments, emotional concepts had instead a fluctuating pattern, different from those of both concrete and abstract concepts, suggesting that they cannot be considered as a subset of abstract concepts. The interaction between type of concept (abstract, concrete and emotional) and effector (mouth, hand) was not significant in the lexical decision task, likely because it emerged only with tasks implying a deeper processing level. It reached significance, instead, in the recognition tasks. In both experiments abstract concepts were facilitated in the mouth condition compared to the hand condition, supporting our main prediction. Emotional concepts instead had a more variable pattern. Overall, our findings indicate that various kinds of concepts differently activate the mouth and hand effectors, but they also suggest that concepts activate effectors in a flexible and task-dependent wa

ORIGIN OF LIGHT SCATTERING FROM DISORDERED SYSTEMS

Anelastic light scattering is computed numerically for model disordered systems (linear chains and 2-dimensional site and bond percolators), with and without electrical disorder. A detailed analysis of the vibrational modes and of their Raman activity evidences that two extreme mechanisms for scattering may be singled out. One of these resembles scattering from finite size systems, while the other mechanisms originates from spatial fluctuations of the polarizability and is such that modes in even small frequency intervals may have very different Raman activities. As a consequence, the average coupling coefficient $C(\omega)$ is the variance of a zero-average quantity. Our analysis shows that for both linear chains and 2-dimensional percolators the second mechanism dominates over the first, and therefore Raman scattering from disordered systems is essentially due to spatial fluctuations.Comment: 12 pages, Latex, 7 figures available on request

USP2a alters chemotherapeutic response by modulating redox

Cancer cells are characterized by altered ubiquitination of many proteins. The ubiquitin-specific protease 2a (USP2a) is a deubiquitinating enzyme overexpressed in prostate adenocarcinomas, where it exhibits oncogenic behavior in a variety of ways including targeting c-Myc via the miR-34b/c cluster. Here we demonstrate that USP2a induces drug resistance in both immortalized and transformed prostate cells. Specifically, it confers resistance to typically pro-oxidant agents, such as cisplatin (CDDP) and doxorubicin (Doxo), and to taxanes. USP2a overexpression protects from drug-induced oxidative stress by reducing reactive oxygen species (ROS) production and stabilizing the mitochondrial membrane potential (ΔΨ), thus impairing downstream p38 activation and triggering of apoptosis. The molecular mediator of the USP2a protective function is the glutathione (GSH). Through miR-34b/c-driven c-Myc regulation, USP2a increases intracellular GSH content, thus interfering with the oxidative cascade triggered by chemotherapeutic agents. In light of these findings, targeting Myc and/or miR-34b/c might revert chemo-resistance

Validation of a multi-scale simulation strategy based on the Pointwise Strain Superposition Method

This paper details the experimental validation of a multi-scale simulation strategy that we developed for predicting the stresses and distortions induced by Powder Bed Fusion processes. The strategy comprises a meso-scale model, a macro-scale model, and a scaling method named Pointwise Strain Superposition. The first model evaluates the temperature, stress, and strain fields produced by a single scan line. The scaling method transfers the meso-scale results to the macro-scale model, which is then able to simulate the entire manufacturing process with a reasonable computational cost. The simulation strategy was validated by comparing its results with the stresses and distortions measured on several specimens made of selective laser melted Inconel 718. Stresses were measured through the blind hole drilling method on a cylindrical specimen printed with two different scanning strategies, while distortions were measured on a hollow cylinder and on a cantilever-shaped specimen after removing its supports. In both cases, the simulation showed first- or higher-order accuracy despite the significant uncertainties regarding the input parameters and material properties. This robustness, coupled with its computational efficiency, leads us to believe that our simulation strategy could enhance the process optimization and provide a better understanding of the underlying physical phenomena along with their effects on the manufactured parts