Dashboards for Discovery and Learning Applications

Catalog description

As online learning tools have become more prominent, dashboards have emerged as a way for helping students, teachers, and other stakeholders in navigating learning data. They can provide both formative and summative information about a wide range of data and a wide range of stakeholders. However, learning can take many forms and does not always require (or result from) a linear path. Successful learning often requires persevering in the face of obstacles, but allowing learners to stagnate in such a space for too long can be demotivating. Likewise, we have also seen research that suggests that results in short term learning gains do not always lead to long term success. Even digital learning systems with substantial automation require data to be presented in a way that is relevant for the given stakeholders. This course explores starts with an overview of the kinds of digital learning systems currently available and a high-level view of the kinds of measurement constructs that have been modeled using their data. It then covers the kinds of motivational principles, cognitive biases, and other data visualization principles that are important to communicating different kinds of data. Finally, it culminates in the development of a novel dashboard system, the design of which students will justify both with a review of the literature and with a mini-usability study.