Learning Analytics is the Secret to Strong Retention Rates
August 8th, 2018
Do you lie awake at night wondering how to defeat the trend of student attrition?
You have a great institution. Every year your roster is filled with new students. Yet, when the year closes out, the number of returning students doesn’t match up with the student list from the opening of the school year. It feels like the back door is wide open, as student attrition continues to impact your institution.
Early Warning Systems to Trigger Student Helps
The map of your organization is peopled with individuals from across the board.
First, there are those individuals who are your superstars, succeeding at every opportunity and continually looking for new ways to grow and develop. Your fear of student attrition does not include these students.
Then there are people like Thomas X, a typical maybe even non-descript student who is in the process of upgrading his education to give him a better chance of success in the career world. Thomas doesn’t say much in class, leaves campus quickly after class, turns in assignments on time, and usually receives them back with comments for improvements and a mark of 60%, passing the course, but just barely. How do you help this student when you don’t even know him?
Enter learning analytics.
While you as an administrator may not know Thomas, your learning analytics platform does.
The data collected and then utilized through learning analytics is priceless in this situation.
The data reveals that Thomas quickly whips through his online class material, and often errors out on practice assessments. This information alone will do nothing to retain Thomas X as a student.
However, when this information triggers an early warning for both Thomas X and his facilitators, the tide of student attrition can be changed. When the red light of a student struggling is triggered, extra help can be offered, both digitally and physically. If your higher education administrators are able to see that Thomas X is not comprehending a concept, his facilitators can offer in-person tutoring or targeted supports and Thomas’ chance of academic success and retention skyrockets.
Personalized Learning to Assist in Student Understanding
The days of a rigid, calendar-based system of education are over. With the rise of e-learning and personalized learning, students are able to move through educational concepts at their own pace, either faster or slower depending on their needs.
Utilizing the patterns harvested in Big Data, a learning analytics platform can be used to provide personalized learning for each student. MagicBoxTM’s learning analytics engine can make predictions based on student progress and tailor their education to enhance their learning experience.
Increased Student Satisfaction and Retention
If you Google any college or university, their promotional material is filled with pictures and testimonials of their happy, engaged students.
Why is this important?
Because students that are satisfied, or even better, delighted with their education are more likely to return to finish their program.
So what do you need to do to improve student satisfaction and retain those happy, engaged students?
Resource and equip them.
When students are provided with tools to increase understanding and increase the chances of success, student retention, and overall satisfaction increases.
Through personalized learning and early warning triggers, students are equipped to succeed in real-time, instead of waiting to hear back from a professor days or even weeks later. This is a fantastic strategy to empower students to achieve greatness in their studies and encourage them to return and complete their education.
Forward Thinking for Future Courses
Going back to our hypothetical student Thomas X, utilizing Big Data within a learning analytics engine can predict success for Thomas. Learning analytics can also be used to predict future students’ success and retention rates.
MagicboxTM captures all student activity and allows for learning analytics to break down what is happening to create an overall picture.
Analyzing the data that has been collected may reveal that the majority of students are struggling with a particular concept, and this area needs to be reworked by an educator to make the material accessible.
Or if a particular chapter of an assigned text is repeatedly ignored by students, then educators can delve into the issue to find out why this resource is not helpful to deliver a better product for future students.
The usefulness of Big Data interlaced with a strong learning analytics engine is far-reaching and can be used to ensure the success and retention of your higher education students.
Are you ready to start sleeping better? Let’s solve the problem of student attrition by utilizing our Big Data and Learning Analytics programs for student success. Contact us now to discuss how we can help you succeed today.