63,735 research outputs found

    Animated pedagogical agents effects on enhancing student motivation and learning in a science inquiry learning environment

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    This study focuses on the design and testing of a motivational animated pedagogical agent (APA) in an inquiry learning environment on kinematics. The aim of including the APA was to enhance students’ perceptions of task relevance and self-efficacy. Given the under-representation of girls in science classrooms, special attention was given to designing an APA that would appeal to the female students. A review of the literature suggested that the best design solution would be an agent who was female, young, attractive, and “cool”. An experiment compared three conditions: agent (image and voice), voice (no image), and control (no image and no voice). The research question was whether students’ motivation and knowledge changed over time as they worked in the inquiry learning environment, and whether condition and gender affected such changes. Participants were 61 third-year students (mean age 14.7 years) from a secondary school. Gender was distributed evenly within and across conditions. A significant main effect of time on self-efficacy was found, with self-efficacy beliefs increasing significantly for both boys and girls. In addition, there was a significant interaction between time, condition, and gender for self-efficacy. About halfway during training, girls’ self-efficacy beliefs significantly increased in both experimental conditions and decreased in the control condition. For boys the opposite pattern was found. Girls also gave higher appraisals for the agent. Students in all three conditions realized significant knowledge gains, which did not differ by gender. The discussion critically considers the need for, and design of motivational scaffolding in inquiry learning environment

    Classrooms as Learning Communities

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

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    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

    Neuroeducation: Learning, Arts, and the Brain

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    Excerpts presentations and discussions from a May 2009 conference on the intersection of cognitive neuroscience, the arts, and learning -- the effects of early arts education on other aspects of cognition and implications for policy and practice

    Applying self-processing biases in education:improving learning through ownership

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    Accepting ownership of an item is an effective way of associating it with self, evoking self-processing biases that enhance memory. This memory advantage occurs even in ownership games, where items are arbitrarily divided between participants to temporarily ‘own’. The current study tested the educational applications of ownership games across two experiments. In Experiment 1, 7 to 9-year-old children were asked to choose three novel, labelled shapes from an array of nine. The experimenter chose three shapes and three remained ‘un-owned’. A subsequent free-recall test showed that children reliably learned more self-owned than other-owned or un-owned shapes. Experiment 2 replicated this finding for shapes that were assigned to owners rather than chosen, and showed that ownership enhanced memory more effectively than a control game with no ownership manipulation. Together, these experiments show that ownership games can evoke self-processing biases in children’s memory, enhancing learning. Implications for education strategies are discussed
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