Learning Analytics

Prior to this module, I was not familiar with the term "learning analytics." I was, however, familiar with the concept of collecting data to understand student learning. For example, I use an online game-based reading program called "Headsprout" with my students. When I log into the teacher side of this program, I can see charts that how my students are progressing, what content they are focusing on, what skills they are struggling with, etc. I can use this data to make changes when it comes to teaching.

This module illustrated that learning analytics is more than simply collecting data; it is the process of observing learning behaviors and using observations to make changes or interventions. Working in a school for children with special needs, I am familiar with the process of learning analytics. I found myself making connections to my job in the classroom as I read and watched the materials in this module. I also found myself making comparisons to behavior analysis, a field of psychology. I work with behavior analysts whose job is to collect and analyze data and make appropriate interventions. Reading "Learning Analytics: The Coming Third Wave" helped me understand the difference between what I know as behavior analysis and the process of learning analytics. The difference lies in the "student learning" element of learning analytics. Focusing on learning behaviors, content, progression, etc. is a crucial aspect of learning analytics.

Perhaps I am biased, but I think learning analytics is most beneficial in special education. In special education, it is very important to observe learning behaviors, collect data, and develop interventions. I work with children on the Autism spectrum. Daily, I make observations and interventions to determine "what works and what does not" (Brown, 2011). This is already a regular part of working with learners who do not benefit from cookie-cutter instruction and methods. Adjusting and modifying teaching based on learning behaviors is essential. Also, learning analytics focuses on the learning aspect of analytics, rather than the big-picture numbers (finances, etc.). I think this is exactly what is needed in special education.

Because learning analytics already plays a role in my current job, I expect that it will continue to be significant in my career as a teacher. As a future curriculum developer, I am excited to use learning analytics to understand how learners progress and behave as a result of the curricula that I design and develop. I can use learning analytics to determine what changes need to be made to the instructional materials themselves. Basically, I predict that I will be using learning analytics for the rest of my career.

xApis are used in learning analytics to collect data from several sources. The collected data is compiled to create a complete and thorough picture that fully illustrates the learners' experiences. xApis are important because data from several sources can be used to improve student performance and help students reach learning goals.