个性化学习的上下文感知本体:教育技术的普适计算

Tyler Morrow
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引用次数: 2

摘要

普适计算有潜力极大地提高当前教学实践的效率,但它没有得到充分利用。个性化学习被认为是下个世纪的一个重大工程挑战,它可以受益于普适计算透明地收集和利用有关学生背景、兴趣和需求的信息的能力。本文中描述的博士研究的目标是利用普适计算来开发上下文感知本体和个性化学习的推荐算法,扩展、丰富和精炼普适计算,作为PERCEPOLIS(个性化学习和教学支持的普适网络基础设施)的支柱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A context-aware ontology for personalized learning: Pervasive computing for educational technology
Pervasive computing has the potential to dramatically increase the efficacy of current pedagogical practices, but it is sorely underutilized. Personalized learning, which has been identified as an engineering grand challenge for the coming century, can benefit from the ability of pervasive computing to transparently collect and utilize information about a student's background, interests, and needs. The objective of the doctoral research described in this paper is to leverage pervasive computing to develop context-aware ontologies and recommendation algorithms for personalized learning, extending, enriching, and refining the pervasive computing that serves as the backbone of PERCEPOLIS - Pervasive Cyberinfrastructure for Personalized Learning and Instructional Support.
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