Big Data in Higher Ed
The last couple of years have witnessed a surge of interest in Big Data. In our case, when thinking of Big Data in Higher Education a few questions cross our minds. What is Big Data? And what is its role in Higher Education? Should it be an operational part of the institution?
We had previously given you a glimpse of how big data can be used for student recruitment. What else can it be used for?
Big Data and Retention
With big data, universities and colleges can now know, on one hand, who to target, and on the other hand, what are the tools needed for current students to graduate.
In an era where university enrollment rates are decreasing and retention rates are extremely low, schools are bound to find the right match to avoid dropouts. Universities are evaluated based on the curriculums they offer, research, and faculty to student ratio among other things when being considered for rankings by organizations. From a student’s point of view, they are also assessed based on the campus and student’s life, the extracurricular activities, from varsity teams, to sororities, and clubs, and their administrative processes.
Big data now allows universities to predict who from the students will succeed and who will drop out. The latter can inflict big losses on universities. The data universities have on past students helps study their path: whether they have succeeded or failed and what were the reasons behind each path. This information gives valuable insight on current students’ expected path and allows universities to expand their reach with look-alike audience.
For instance, universities should leverage Big Data to finetune their curriculums and offer optimized journeys for students. The latter will guarantee higher retention rates among students in the different degrees offered. These results are achievable if universities set the right queries for themselves: what is the feedback from orientation day? How did the orientation affect the student’s journey? How does the average grade in mathematics affect the educational journey of a student majoring in engineering? How are elective choices affecting graduation time for students?
Additionally, Big Data enables universities to assess their administrative processes and see whether students render it effective or challenging to deal with the administration.
Big Data and Alumni
As mentioned by many before us, alumni are the biggest donor body of any university. Being able to reach this audience with the right content and at the right time is crucial to collect its generosity.
Firstly, universities can use data they already have on their alumni to know basic information about them like their place of residence, occupation, etc. Secondly, Big Data can help universities study the donation patterns of alumni. Are they first generation college students? Or are they part of a legacy family?
Finally, Big data can highlight the different subjects and areas of interest of high profile alumni to know what content to target them with, rendering the process more personal yet automated. Social listening gives universities a more insightful view of their alumni personal life and their interest that they can act on.
Big Data Flaws
So far, many have been inclined to rely solely on big data to take decisions rendering many processes left to the hands of technology rather than human perspective. However, many processes and decisions could use human intelligence.
While Big Data algorithms can select promising candidates with impressive SAT scores and high school grades, many other criteria should be taken into consideration while considering a candidate’s application for example.
As many things in life technology is an added value and not a replacement. Higher Education Institutions should find the right balance when implementing technology in their processes and aim to make the latter better and not rendering things more complicated and at some point inefficient.