Ubiquitous learning analytics in authentic real-world scenarios

真实场景中无处不在的学习分析

• 批准号: DDG-2015-00027
• 负责人: Kinshuk, K
• 金额: $ 0.73万
• 依托单位: Athabasca University
• 依托单位国家: 加拿大
• 项目类别: Discovery Development Grant
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=612431
• 关键词: Ubiquitous; learning; analytics; authentic; real

Recent advances in mobile and sensor technologies have started to give rise to a lot of research that takes advantage of learners' location, environment, proximity and situation to contextualize the learning process. The adaptivity and personalization in these ubiquitous scenarios have taken a new meaning by bringing authenticity through seamless integration of physical objects available in the learner's vicinity with virtual information in real-time. Such environments not only break the barriers for education by widening the access to those who cannot come to a physical classroom but also increase the richness of the instruction by integrating multiple sources of instruction, contextualization and real-time location-aware learning, hence overcoming the limitations of classroom learning. The approaches for typical learning analytics, that analyse learning patterns in various yet related levels of granularity, have very restricted use in such ubiquitous environments. The technologies and methodologies that currently exists for learning analytics to track the study processes learners undertake to achieve their learning goals and outcomes, particularly in online learning environments, fall short in ubiquitous environments where the data about the learners and their environment comes from disparate sources, with varying levels of reliability and precision, and require synthesis of real-time data with the historical datasets in order to identify contextually meaningful patterns. Ubiquitous learning analytics fills this gap by taking learning analytics to the next stage where learning is not restricted to formal environments; rather it integrates formal environments with the benefits of just-in-time opportunities in authentic environments and the informal social interaction learners engage in. Primary goal of this research is to provide rich learning experiences to the learners by exploring various ways to observe and analyse learning process in ubiquitous environments, and create ubiquitous learning analytics models and modules that exploit the benefits of location, device and user model parameters, and combine them with real-time authentic context of learning to achieve adaptive delivery of just-in-time multimedia-rich combination of physical and virtual learning content.

移动的和传感器技术的最新进展已经开始引起许多研究，这些研究利用学习者的位置、环境、邻近度和情境来情境化学习过程。这些无处不在的场景中的适应性和个性化具有新的含义，通过将学习者附近的物理对象与实时虚拟信息无缝集成来实现真实性。这种环境不仅通过扩大无法进入教室的人的机会来打破教育障碍，而且通过整合多种教学来源、情境化和实时位置感知学习来增加教学的丰富性，从而克服课堂学习的局限性。典型的学习分析的方法，分析学习模式在各种相关的粒度级别，在这种无处不在的环境中使用非常有限。当前存在的用于学习分析以跟踪学习者为实现其学习目标和结果而进行的学习过程的技术和方法，特别是在在线学习环境中，在无处不在的环境中，关于学习者及其环境的数据来自不同的来源，具有不同的可靠性和精确度水平，并且需要实时数据与历史数据集的合成，以便识别上下文有意义的模式。无处不在的学习分析填补了这一空白，将学习分析带入下一个阶段，在这个阶段，学习不限于正式环境;相反，它将正式环境与真实环境中的即时机会和学习者参与的非正式社交互动的好处相结合。本研究的主要目标是通过探索在普适环境中观察和分析学习过程的各种方法，为学习者提供丰富的学习体验，并创建普适学习分析模型和模块，利用位置，设备和用户模型参数的好处，并将其与实时真实的学习环境相结合，以实现实时多媒体的自适应交付-物理和虚拟学习内容的丰富组合。