Combining User Profiling and Context Modelling to Provide Advanced Adaptivity and Personalization

结合用户分析和上下文建模以提供高级适应性和个性化

• 批准号: 402053-2012
• 负责人: Graf, Sabine
• 金额: $ 1.38万
• 依托单位: Athabasca University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=676995
• 关键词: Combining; User; Profiling; Context; Modelling

Information systems are prevalent in daily life activities, and past research showed that making such systems more adaptive and personalized in terms of enabling them to automatically consider users' current situations, characteristics and preferences has high potential in making these systems more effective and easier to use. My long-term research program focuses on advancing research in user adaptive systems, especially learning systems, with the aim to make such systems more adaptive, intelligent and personalized. Research on adaptive and personalized learning systems has focused on designing and evaluating stand-alone learning systems, mostly used as research prototypes, which consider only one or few aspects of a learner's profile (e.g., cognitive abilities, motivational aspects, etc.). Besides the information in a learner profile, nowadays the context/situation in which a learner learns becomes more and more important due to the recent advances in mobile technologies, which allow learners to learn anywhere and anytime using different devices such as mobile phones and tablets. An open challenge in the research area of adaptive systems is therefore not only to combine multiple aspects of a learner profile but also to combine information from the learner profile with information from the learner's context/situation in order to provide rich and comprehensive adaptivity. Furthermore, another challenge is to design adaptive systems/mechanisms that can be used in large-scale, such as for entire educational institutions. The primary goal of this research program is to advance research in user adaptive systems through designing and evaluating mechanisms and algorithms (implemented as web services of an open-source tool suite) that consider information from learners' profiles as well as context information, and respectively extend existing learning systems with adaptive and intelligent capabilities. The developed tool suite will be highly useful for both researchers who can integrate the web services in their research prototypes and practitioners who will be able to use them in their learning systems, leading to far-reaching benefits for Canadian research and education.

信息系统在日常生活活动中普遍存在，过去的研究表明，使此类系统更具适应性和个性化，使其能够自动考虑用户的当前情况、特征和偏好，有很大潜力使这些系统更有效、更易于使用。我的长期研究计划侧重于推进用户自适应系统，特别是学习系统的研究，旨在使此类系统更具适应性、智能性和个性化。 自适应和个性化学习系统的研究重点是设计和评估独立的学习系统，主要用作研究原型，仅考虑学习者概况的一个或几个方面（例如认知能力、动机方面等）。除了学习者档案中的信息之外，如今，由于移动技术的最新发展，学习者学习的背景/情境变得越来越重要，这使得学习者可以使用手机和平板电脑等不同设备随时随地学习。因此，自适应系统研究领域的一个开放挑战不仅是结合学习者概况的多个方面，而且是将来自学习者概况的信息与来自学习者背景/情况的信息结合起来，以提供丰富且全面的适应性。此外，另一个挑战是设计可大规模使用的自适应系统/机制，例如用于整个教育机构。 该研究计划的主要目标是通过设计和评估机制和算法（作为开源工具套件的 Web 服务实现）来推进用户自适应系统的研究，这些机制和算法分别考虑来自学习者个人资料和上下文信息的信息，以及通过自适应和智能功能扩展现有的学习系统。开发的工具套件对于可以将网络服务集成到其研究原型中的研究人员和能够在其学习系统中使用它们的从业者来说都非常有用，从而为加拿大的研究和教育带来深远的好处。