66,291 research outputs found

    Collaborative action research in the chilean EFL classroom

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    Tesis (Profesor de Inglés, Licenciado en Educación)Este estudio discute los resultados obtenidos en una investigación cualitativa que involucra a un docente en formación como profesor-investigador en una Investigación-Acción, en un colegio de Santiago de Chile. El objetivo de este estudio fue explorar los beneficios de la Colaboración en Investigación-Acción como una práctica para promover la inclusión de la expresión oral del idioma inglés en las aulas chilenas. El profesor-investigador utilizó un diario como un instrumento para reflexionar sobre sus clases y actividades orales, las cuales fueron aplicadas en el colegio. Esas actividades orales fueron obtenidas de dos entrevistas grupales con docentes en formación de una universidad chilena, quienes fueron los colaboradores de este estudio, así como también la profesora mentora del colegio en el cual el profesor-investigador estaba haciendo su práctica. Los resultados mostraron que algunas de las actividades obtenidas en las entrevistas grupales promovieron la participación e interacción de los estudiantes durante las clases. Además, el profesor-investigador fue capaz de percibir la importancia de la reflexión de las actividades con el fin de hacer cambios y mejoras en su docencia. Asimismo, la colaboración entre pares, la cual fue representada en las entrevistas grupales, nos permitió reconocer nuestras fortalezas y mejorar nuestras debilidades cuando enseñamos. Finalmente, este estudio sugiere que todos los docentes deberían compartir sus experiencias, opiniones, sentimientos o pensamientos con sus colegas para así implementar colaboración, y también hacer de la reflexión un método habitual en su enseñanza para prevenir errores comunes representados por profesores en la sala de clases.This study discusses the outcomes of a qualitative research, which engaged a pre-service teacher as the teacher-researcher (T-R) in an Action Research (AR) design at a school in Santiago, Chile. The aim of this study was to explore the benefits of Collaborative Action Research (CAR) as a practice to foster the inclusion of speaking skills in Chilean EFL classrooms. The T-R used journals as an instrument to reflect on his teaching and speaking practices which were applied at the school. Those speaking practices were obtained from two group interviews with pre-service teachers from a Chilean university, who were the collaborators of this study, as well as the mentor teacher (M-T) from the school where the T-R was doing his practicum. The findings showed that the practices obtained in the group interviews encouraged students’ participation and interaction during classes. In addition, the T-R was able to perceive the importance of reflection on the practices in order to make changes and improvements in his teaching. Collaboration among peers, which was represented in the group interviews, allowed us to recognize our strengths and improve our weaknesses when teaching. Finally, this study suggests that all teachers should share their experiences, opinions, feelings, or thoughts with their colleagues in order to implement collaboration, and make reflection a common method in their teaching to prevent common errors committed by teachers in the classroom

    Identifying First-person Camera Wearers in Third-person Videos

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    We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wearing body-worn cameras while a third-person static camera also captures the scene. To do this, we need to establish person-level correspondences across first- and third-person videos, which is challenging because the camera wearer is not visible from his/her own egocentric video, preventing the use of direct feature matching. In this paper, we propose a new semi-Siamese Convolutional Neural Network architecture to address this novel challenge. We formulate the problem as learning a joint embedding space for first- and third-person videos that considers both spatial- and motion-domain cues. A new triplet loss function is designed to minimize the distance between correct first- and third-person matches while maximizing the distance between incorrect ones. This end-to-end approach performs significantly better than several baselines, in part by learning the first- and third-person features optimized for matching jointly with the distance measure itself

    Our Space: Being a Responsible Citizen of the Digital World

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    Our Space is a set of curricular materials designed to encourage high school students to reflect on the ethical dimensions of their participation in new media environments. Through role-playing activities and reflective exercises, students are asked to consider the ethical responsibilities of other people, and whether and how they behave ethically themselves online. These issues are raised in relation to five core themes that are highly relevant online: identity, privacy, authorship and ownership, credibility, and participation.Our Space was co-developed by The Good Play Project and Project New Media Literacies (established at MIT and now housed at University of Southern California's Annenberg School for Communications and Journalism). The Our Space collaboration grew out of a shared interest in fostering ethical thinking and conduct among young people when exercising new media skills

    A Generalized Recurrent Neural Architecture for Text Classification with Multi-Task Learning

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    Multi-task learning leverages potential correlations among related tasks to extract common features and yield performance gains. However, most previous works only consider simple or weak interactions, thereby failing to model complex correlations among three or more tasks. In this paper, we propose a multi-task learning architecture with four types of recurrent neural layers to fuse information across multiple related tasks. The architecture is structurally flexible and considers various interactions among tasks, which can be regarded as a generalized case of many previous works. Extensive experiments on five benchmark datasets for text classification show that our model can significantly improve performances of related tasks with additional information from others
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