The purpose of Learning Analytics, simply put, is to improve the quality of education. By analyzing students' preferences, behavior, and assessment results, teachers will have an easier time differentiating instruction to determine what their students need.
Learning analytics is a way for teachers and administrators to give and receive instant feedback, using technology as a tool.
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In the following video, Steve Schoettler, the founder and CEO of a learning analytics company, describes what learning analytics is and how it can improve education in the United States.
Using online programs, students can be provided with what they specifically need, meaning struggling students can receive support while advanced students can be provided with more in-depth activities. Teachers can also decide if other information is relevant - for example, if they discover that certain students are taking little time to complete online quizzes and subsequently failing them, they can determine how to proceed.
In their report "Penetrating the Fog: Analytics in Learning and Education," Professors Siemens and Long provide a list of ways that Learning Analytics can help in higher education. Though they specifically discuss the benefits for colleges and universities, some of the items can potentially apply to primary or secondary schools as well. Their list reads as follows:
How do big data and analytics generate value for higher education?
They can improve administrative decision-making and organizational resource
They can identify at-risk learners and provide intervention to assist learners in
achieving success. By analyzing discussion messages posted, assignments
completed, and messages read in LMSs such as Moodle and Desire2Learn,
educators can identify students who are at risk of dropping out.
They can create, through transparent data and analysis, a shared understanding
of the institution’s successes and challenges.
They can innovate and transform the college/university system, as well as
academic models and pedagogical approaches.
They can assist in making sense of complex topics through the combination of
social networks and technical and information networks: that is, algorithms can
recognize and provide insight into data and at-risk challenges.
They can help leaders transition to holistic decision-making through analyses of
what-if scenarios and experimentation to explore how various elements within a
complex discipline (e.g., retaining students, reducing costs) connect and to
explore the impact of changing core elements.
They can increase organizational productivity and effectiveness by providing up-
to-date information and allowing rapid response to challenges.
They can help institutional leaders determine the hard (e.g., patents, research)
and soft (e.g., reputation, profile, quality of teaching) value generated by faculty
They can provide learners with insight into their own learning habits and can give
recommendations for improvement. Learning-facing analytics, such as the
University of Maryland, Baltimore County (UMBC) Check My Activity tool, allows
learners to “compare their own activity . . . against an anonymous summary of
their course peers.”
To read the report in its entirety, click here.
Because Learning Analytics - and Big Data in general - are fairly new concepts, there are many questions that have arisen about their use in education and other fields. The following infographic discusses the definition of Learning Analyitcs and addresses a number of questions.
One of the major concerns about Learning Analytics involves privacy. Companies like Google and Facebook have already come under fire for tracking and using user data for profit; Learning Analytics may experience similar pushback. Learners may feel intimidated knowing that their online behavior is being tracked. On another note, it may be challenging to incorporate Learning Analytics into elementary and secondary classrooms if students lack the necessary technology. Still, if the overall goal of learning analytics is to help both individual instructors and institutions as a whole better serve their students, answers to these questions to be found.
To learn more about the history of learning analytics, click here.