Learning AnaltyicsThe First International Conference on Learning Analytics and Knowledge in 2011 defines learning analytics as "the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs."
Watch the video above to learn more about the application of learning analytics to the practice of teaching. |
Big DataBig data refers to the massive amounts of data produced by our technologies that are often difficult to analyze using traditional tools and methods.
Watch the video above to learn more about Big Data and its history. |
Learning analytics are a way that educators can manage "big data" by gathering insights to inform data-driven decision-making. While previous generations of teachers only had a few data points to work with, such as test performance and grades, new technologies such as learning management systems, educational technologies tools, and other systems are prompting a shift towards data-driven decision-making at all levels of educational practitioners.
To learn more about how Learning Analytics and Big Data are shifting teaching practices, please check out the following articles: The Evolution of Big Data and Learning Analytics Learning Analytics: How to Use Students' Big Data to Improve Teaching |
Activity #1In this next activity, you will be making a general data-driven decision based on analyzing data on different universities and programs. Click on the image to access the activity.
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Educational data mining is another method for improving learning and educational environments. While it is similar to learning analytics, typically it is recognized as a distinct analytical method, prompted by data mining modeling and automated data discovery. As data-mining aims to automate much of the analytics, it is often a controversial topic withing education due to privacy, bias, and ethics.
The table on the right breaks down the differences between learning analytics and educational data-mining. Please note LAK stands for "Learning Analytics" and "EDM" stands for Educational Data-Mining. Table is sourced from Siemens & Baker (2012, p. 2). |
"Simply hiring a data scientist does not create a data-driven organization. Identifying and realizing relevant and measurable goals through a well thought-out data strategy does, and this requires collaboration." (Earls, 2019)