LEARNING ANALYTICS

 

LEARNING ANALYTICS

 

What is learning analytics?

“Learning analytics is 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.”
(Siemens, 2010)


Although there is some disagreement on the finer points of learning analytics, there is a mutual agreement that learning analytics should optimize student learning.

Learning analytics is still a new term in education, although we have always strived to improve learning for our students. With the rise in technology, we have more access to student data than ever before. Millions of student data points come from Learnalytics™ in our solutions alone. The question is, how do we use those millions of data points to optimize our students’ learning?

 

How can I use learning analytics to help my students?

You’re probably familiar with our annual What Kids Are Reading report. The 2017 edition featured 9.9 million students from all over the United States. We used data from all those students to see which books and nonfiction articles were the most popular, along with much, much more. This data can be used to guide your students’ reading choices and, in turn, help you create a more effective reading strategy in your classroom.

Another example is the dashboards in Renaissance Star 360®. The data within the dashboards help guide instruction and allow you to see which of your students are above grade level, which students are at grade level, and which students need additional help. By using the dashboards, you optimize learning for each of your students.

 
 
 
 

Where is the future heading?

As technology advances, learning analytics advances. Of course, nothing will replace teachers and the relationships they have with their students. However, learning analytics will help further your reach and improve instruction. We have a come a long way in the past few years, and will only continue to do so in the coming years. Student data will become more accurate, and we’ll be able to pinpoint obstacles and better predict student growth.

 
 

Why does it matter, anyway?

Learning analytics give you insight into your students’ learning. By using data gleaned from your students, you can optimize your students’ learning environments and encourage a growth mindset.

 
 

Resources and further reading

Little, R., et al. (2015). The Predictive Learning Analytics Revolution. ECAR. Retrieved from: https://library.educause.edu/resources/2015/10/the-predictive-learning-analytics-revolution-leveraging-learning-data-for-student-success.

Siemens, G. (2010). 1st International Conference on Learning Analytics and Knowledge 2011 call for papers. Retrieved from: https://tekri.athabascau.ca/analytics/call-papers.

Stickney, E. (2014). Learnalytics: The promise of learning analytics. Renaissance. Retrived from: http://www.renaissance.com/2014/09/18/learnalytics-the-promise-of-learning-analytics/

 
 

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