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  • 标题:Video-based learning ecosystem to support active learning: application to an introductory computer science course
  • 本地全文:下载
  • 作者:Michail N. Giannakos ; John Krogstie ; Trond Aalberg
  • 期刊名称:Smart Learning Environments
  • 电子版ISSN:2196-7091
  • 出版年度:2016
  • 卷号:3
  • 期号:1
  • 页码:1-13
  • DOI:10.1186/s40561-016-0036-0
  • 出版社:Springer Verlag
  • 摘要:The systematic use of technologies in order to orchestrate learning has become widely used in the past years.Diverse technologies have been applied in a variety of teaching practices; for instance learning tools which allow you to flip the classroom or monitor other active learning practices.However, the developed systems are only a subset of different kinds of learning materials and learning tools that an educator should take into consideration; and most importantly they do not offer an overview of the different learning dynamics.The development of a learning ecosystem framework, which will allow us to describe “the complex of living organisms” as well as their interrelationships, will help us to better understand and further develop our teaching approaches.In this paper, we present a video-based learning ecosystem framework and the first captured results of its application in an introductory computer science course.The framework incorporates basic e-learning tools and traditional learning practices, making it accessible to anyone wanting to implement a video-assisted project-based experience in his/her course.Its application is based on open and easy-to-use tools, allowing for the incorporation of any additional functionalities.This work aims to provide insights for other scholars and practitioners to further validate, examine, and extend the proposed framework.This approach can be used for those interested in incorporating project-based or flipped classroom approaches in their teaching, since it is a flexible procedure that may be adapted to meet their needs.
  • 关键词:Learning ecosystem; Active learning; Project-based learning; Learning environments; Learning dynamics; Video-based learning
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