Applying analytics to elevate the higher education student experience
Part 3 of 3
As we discussed in part one and part two, first-year college or university students are searching for an exceptional experience, but when they don’t find it, many of them leave the school in which they enrolled. For many of these students, attending college or university is the first time they have spent significant amounts of time away from friends and family. Feelings of loneliness and homesickness abound. Students also find the academic environment challenging; students who cruised through high school struggle in the college curriculum and may not feel they belong in the university.
According to Leaving Academia, a website focused on attrition, these are some of the reasons students leave college:
- Too much fun at the expense of classes and grades
- Academically unprepared; burned-out on education
- Financial constraints; low on funds
- Academic climate/fit
- Lack of advising, guidance
- Demands from part-time or full time employment
In this final installment, we’ll focus on two areas: lack of advising/guidance and demands from part-time or full-time employment. Data and analytics can address some of those issues by helping college and universities reduce the likelihood of attrition and to create an exceptional student experience.
Lack of advising/guidance
For many first-year students, the day they enter college or university is the first time many of them have been away from home and the guidance of parents and others. Think back on when you entered university; it was for many of us a daunting experience, especially if you were in a new place and knew no one. Assisting first-year students navigate the complexities of university life can go a long way to help ensure they get an exceptional student experience. By applying data and analytics to the process of advising students on concerns such as academic course load, textbooks, housing amenities, health facilities and other factors, colleges and universities can help ease much of the burden facing students. And by applying “learning” to the types of questions students ask, the system can expand the knowledge base of answers available to students. Sound like science-fiction? Not at Australia’s Deakin University. Learn how the school is using IBM Watson and advanced analytics to help guide students through the rigors of college life.
Demands from part-time or full time employment
Many students today are attending college or university while working part-time or full time. These could be students who are returning to college and university after time away to either finish a degree program or start one. Also, these may be students who need to work because loans, financial aid and other grants are not enough to cover the cost of attaining a degree. In both cases, understanding the pressures these students face is critical, because they have a greater burden to balance both work and academics. If the pressure becomes too great, it is often the academics that are dropped.
How do we know, for example, that a student working the late shift and balancing a full academic load is at risk? By applying analytics capabilities across both academic and non-academic data to fully understand that student. The key is capturing, integrating and aligning that data to get a complete view of that student. By understanding the student as an individual, it is easier to identify whether he or she is at risk, and then intervene appropriately to keep the workload in balance. For students working late shift and taking a full load of courses, analytics can rearrange the course schedule, helping to focus on the right academic mix. Analytics can be used to find the student other employment that is more conducive to the academic load, or to find additional aid to offset reduced work hours. Analytics can help institutions achieve that balance.
An analytics-driven approach can help colleges and universities build an exceptional student experience. To see how, visit IBM Analytics for Education.