With the insights unveiled by analytics, AOU can now identify vulnerable students and devise more targeted initiatives to help them—increasing retention and progression rates, and boosting student numbers.
Professor Hussein comments: “Thanks to IBM Watson Analytics, we’ve been able to pinpoint key factors that help us understand why students drop out of university, and take steps to boost retention rates.
“For example, students’ country of origin was a strong indicator of drop-out rates. We realized that because our learners come from a range of different countries, the quality and scope of their high school education can vary considerably. This meant that some students struggled to keep up even on a low-level program’s core courses. As a result, we decided to examine the effect of offering the introductory zero-credit math courses IT100, IT101 and MA100 in our Oman country campus as a mandatory requirement from the MoHE.
“The experiment has been monitored throughout the considered duration from Fall 2013 to Fall 2017. The analytics has revealed that offering the aforementioned introductory courses resulted in reducing the percentage of withdrawn students from level-one core math courses relatively by an average of 34 percent while relatively increasing the pass rate by an average of 12 percent.”
“The results suggest that these introductory courses have been successful in giving students the baseline they need to succeed in the AOU system. We’re now building on that success by implementing similar courses in other topics and/or countries.”
As well as looking at KAPIs across courses, it was also desired to gain insight into the academic performance of individual students. The AOU designed a “Student Risk Factor” (SRF) score, which is composed of the student’s current GPA, progression rate, and the number of warnings received.
Professor Hussein notes: “This SRF score can be used to identify students who are struggling and need support, so that the university can intervene before they stop progressing and drop out. We discovered that one key factor behind SRF scores was the student’s academic seniority: junior students tend to struggle in the early part of their studies due to their unfamiliarity with the Open Education System.
“High school GPA also plays a crucial part in determining the SRF, since students with average and low performance in high school find their undergraduate studies more challenging. Additionally, an important factor affecting the SRF is the country people were studying in, due to the fact that students in different countries have differences in academic background and various socio-economic situations, along with diversity in physical resources and infrastructure.”
“For example, our campuses in Kuwait, Egypt, Jordan, Bahrain, and Riyadh are more modern and have ‘smart buildings’, while the ones in Lebanon and Oman are older and less well-equipped. We’re now working on upgrading our older buildings to provide an excellent learning environment for all our students, whichever campus they’re based at.
“The political situations in different countries also plays a role in students’ academic success—in Jordan and Lebanon for instance, there are a lot of Syrian refugees, whose financial situation can often make it very difficult for them to commit to their studies. We’re now working to provide funds to assist these students and help reduce their SRF scores, boosting their chances of completing a university education.”
By enabling AOU to provide targeted help to struggling students and increase retention rates, the IBM solution also helps create a more stable revenue stream for the university.
“When students drop out, it has a financial impact on the university,” remarks Professor Hussein. “By boosting retention rates, we have greater financial security and the ability to continue investing in even better educational resources. It’s a win-win.
“Aside from tracking and analyzing students’ academic performance, IBM Watson Analytics has helped us update the new ITC Program, which was revalidated in last April, 2017. Our analysis revealed that offering core courses that comprise only three or five credit-hours of study leads to losses in revenue of 6 to 11 percent. Therefore, we have updated the program to offer only four and eight credit-hour core courses, increasing our revenue and providing even better program learning outcomes.”
He concludes: “IBM Watson Analytics has been vital in enabling us to unpick a mass of previously impenetrable data and uncover valuable insights. By using this knowledge to boost progression and retention rates, we’re not only providing vulnerable students with the support they need—we’re also ensuring a stable revenue stream that can go back into the university to further enhance the educational experience—it’s a positive cycle that wouldn’t be possible without harnessing analytics.
“Data analytics is becoming crucial for fact-based decision-making in all areas of university life. I see IBM Watson Analytics as a decision-making companion to help AOU achieve even greater academic, administrative and financial success.”