907 resultados para applied learning educators


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This research investigated pedagogical approaches required for the successful inclusion of children and young people living with Fetal Alcohol Spectrum Disorders. The research applied an Indigenist constructivist qualitative method working with one school community. The development of a National Framework for Achieving Inclusion for Australian Students with FASD demands urgent policy and support for educators to meet the complex learning needs of students with FASD.

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This thesis advances the area of applied machine learning, sentiment and psycholinguistic analysis in social media for health analytics. In particular, the thesis views social media as a gigantic form of 'sensor' to inform about mental health community and related topics.

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This research applied qualitative and narrative methodology to investigate police officers' professional practice and learning. Analysis of the data revealed three thematic frameworks of power-knowledge relations, practice and knowledge, and gender and (dis)embodied practice that harboured doubtful matters (aporias) and blind spots (lacunae). The potential for change and the possibility of different perspectives and new learning was evident. Paradigmatic shifts in thinking, learning and practice are needed for police officers to develop reflexive practice that is social, relational, agential, and embodied, however, limitations and constraints exist based on the strength and resilience of dominant pedagogies influenced by social, cultural, institutional and occupational practices and discourses.

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The growth of interest in virtual worlds and other online spaces for children and young people raises important issues for literacy educators and researchers. This book is a timely and much-needed collection of current research in the area. It provides a synthesis of knowledge and understanding and will be a key resource for scholars, students and teachers, particularly those interested in digital literacies. The work presents a coherent vision of current knowledge, and some of the most engaging, empirical research being undertaken on virtual worlds and online spaces in and beyond educational institutions. It contains international studies from the UK, North America and Australasia.This is an important time for those researching virtual worlds, videogaming and Web 2.0 technologies, since there is growing professional interest in their significance in the education and development of children and young people. Whether these technologies are solely associated with informal learning or whether they should be incorporated into classroom contexts is hotly debated. This book provides a principled evaluation and appreciation of the learning, teaching and instruction that can occur in digital environments, showing children, young people and those who work with them as active agents with possibilities to navigate new paths.

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BACKGROUND: As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs.

OBJECTIVE: To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence.

METHODS: A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method.

RESULTS: The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models.

CONCLUSIONS: A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community.

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The purpose of this article is to present the results obtained from a questionnaire applied to Costa Rican high school students, in order to know their perspectives about geometry teaching and learning. The results show that geometry classes in high school education have been based on a traditional system of teaching, where the teacher presents the theory; he presents examples and exercises that should be solved by students, which emphasize in the application and memorization of formulas. As a consequence, visualization processes, argumentation and justification don’t have a preponderant role. Geometry is presented to students like a group of definitions, formulas, and theorems completely far from their reality and, where the examples and exercises don’t possess any relationship with their context. As a result, it is considered not important, because it is not applicable to real life situations. Also, the students consider that, to be successful in geometry, it is necessary to know how to use the calculator, to carry out calculations, to have capacity to memorize definitions, formulas and theorems, to possess capacity to understand the geometric drawings and to carry out clever exercises to develop a practical ability.