Whether they’re driven by commercial interests or not, most developers and companies care about positive impact. Of course, impact helps in selling products, but it’s also a key motivation in why people develop and refine technologies: they care about supporting learning.
Learning Analytics (LA) is a new promising field that is attracting the attention of education providers, including teachers, learning designers and academic directors. Researchers and practitioners are interested in learning analytics as it can provide insights from student data, for example, students’ learning processes, automatically identifying learners in need and visualising learners’ behaviour.
It never bodes well to dive into the unknown without preparation. To define, design and enable learning analytics, it’s essential to have a clear strategy in place. Prep yourself with these evaluation questions before you dive into learning analytics.
Learning analytics (LA) is a technology for enabling better decision-making by teachers, students, and other educational stakeholders by providing them with timely and actionable information about learning-in-process on an ongoing basis.
At the 2019 Enterprise Summit, higher education IT, business and finance, and institutional research professionals gathered to explore the future and the promise of analytics. This third in a series of three blog posts discusses the importance of governance, collaboration, and communication to an analytics future.
The emerging configuration of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
Today, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners' interactions on online learning platforms.