Ubiquitous learning analytics in authentic real-world scenarios

点击翻译按钮获取中文摘要

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.