As our lives continue to change with evolving technology which has become an indispensable part of every field, it is only expected that we make judicious use of technology in the field of education as well. Especially since the onset of the pandemic, when schools and college campuses were shut down, locking millions of students and teachers across the entire nation, out of the classroom, the role of technology in education has shot up drastically. Today, all educational institutions have pivoted to online methods and traditional offline classrooms have been substituted with online teaching apps and platforms. One of many aspects of modern-day technology which shows great promise in being utilized in the field of education is the use of learning analytics in educational institutions to make the classroom experience more refined and rewarding for students.

Learning analytics generally refers to the gathering and analysis of data about students and their learning environments with the intention of gaining insight and understanding the intricacies of classroom teaching, thereafter using gained knowledge to develop methods for improving student learning outcomes. For all educational purposes, there are mainly two categories where data analytics is used, teaching and learning analytics. Where teaching analytics mainly focuses on the analysis of teaching methodology and design by scrutinizing lesson plans, and courses of teachers to ascertain their efficacy in contributing to a positive student learning experience, Learning analytics gathers student data and studies it to come up with options for teachers to explore in order to make the learning experience for the students a more effective and refined one.

Learning analytics provides a better understanding of the level of learning and learning ability of each student, which opens doors for more personalized attention or intervention to each student as and when required.

There are various ways in which a teacher can make use of learning analytics tools to improve student engagement and learning outcomes. In this article, we take a look at some important ways in which these tools can be utilized by the instructor.

Record Student Learning Behaviors-

Learning analytics can be used to gather data generated from various student activities and their interactions with the class, be it with their teachers or their peers. An analysis of this data can provide invaluable insight into the student learning behavior and help the instructor in making a prompt decision about changes required in teaching methodology to boost student engagement and learning outcomes.

Assess Peer-to-Peer Learning

Educators nowadays, encourage group activities in their classrooms. Student study groups and discussion boards are being widely used as learning methods. Learning analytics can also be put to use to look into the student’s activities on study groups and other social learning platforms, to ascertain the benefits of peer-based learning.

Enhance Study Material and Learning Tools-

Whether and how does a student makes use of his study material in learning can be easily monitored by employing the help of learning analytics. The analysis could reveal learning gaps if any, or other potential issues with the study material or student’s usage of study material. By looking at the analysis of combined data of all students, an instructor could easily zone in on ways to refine the student learning process or structure the study material.

Personalized Teaching-

Each student learns in a different way. Some are better visual learners, others learn better when instructions are communicated to them vocally and yet others learn better by reading the study material. Learning analytics can be used to monitor the differences and unique requirements of every student. A large amount of data encompassing even the tiniest of details can be analyzed to provide tailor-made course content suited to the needs of each student.

Predict Student Performance-

Learning analytics with the help of machine learning tools and the application of various statistical models can accurately predict the student performance in the future, based upon the data available regarding his current learning behavior and engagement. This can help in identifying the underperforming students and giving them targeted attention. The idea is to analyze relevant data to advise the teacher into carrying out prompt intervention in the right direction before it is too late for the student.

Therefore, it is evident that learning analytics is a really promising application of technology in the field of education. Learning analytics tools have the power to completely structure and streamline our teaching methodologies based on concrete evidence rather than old-school beliefs.