远距离教育:以亚马逊地区为例

Elaine H. T. Oliveira, Erika H. Nozawa, K. T. Lucena, Walfredo Lucena Filho
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引用次数: 5

摘要

亚马逊地区的特点是人口密度低,只有一个大城市,即首都玛瑙斯,其余的人口分布在经济不发达的小城镇。这些城镇大多受到地理隔离的影响,因为它们分散在森林中,只能通过河流进入。面对所有这些困难,向这些人提供教育是一项现实和日常的挑战。为了给该地区的学生提供进入高级课程的机会,亚马逊联邦大学通过其远程教育中心(CDE)设计的解决方案之一是创建非面对面模式的本科课程。CDE项目包括组织总部,称为极点,接受行政管理,公共管理,美术,生物,农业科学和体育等课程。本文描述了这一教育经验,并提出了技术支持的教学模式结构(PMT),使这一场景成为现实。这种模式的创新之处在于,在CDE的协助下,分布在17个不同极点的1,618名学生可以通过适应他们实际情况的后勤和技术支持结构跟上课程的步伐。课程管理系统(CMS)提供的资源、导师和其他支持离线活动的专业工具,使高等教育能够到达亚马逊最偏远的地区。
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Distance education with remote poles: An example from the Amazon region
The Amazon region is characterized by its low population density, with one large city, the capital Manaus, and the remainder of its population distributed in small and less economically developed towns. Most of these towns suffer from huge geographic isolation, as these are scattered in the forest and their access are only through rivers. With all these difficulties, taking education to this population consists of a real and daily challenge. To provide an opportunity for students of this region to enter into an upper-level course, one of the solutions devised by the Federal University of Amazonas, through its Center for Distance Education (CDE) was the creation of undergraduate courses in non-face mode. CDE project consisted of organizing headquarters, called poles, to receive courses in Administration, Public Administration, Fine Arts, Biology, Agricultural Sciences and Physical Education. This paper describes this educational experience and presents the structure of the pedagogical model supported by technology (PMT) which allows this scenario to become reality. The innovation of this model is to allow the 1,618 students, distributed in 17 different poles, assisted by CDE, to keep pace with their course through a structure of logistical and technological support adapted to their reality. Resources offered by a Course Management System (CMS), tutors and other specialized tools that support off-line activities make it possible for higher education to reach the most remote regions of Amazon.
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