AOU wanted to identify the key factors behind student progression and retention rates, so that it could help struggling students and boost numbers. Could analytics help make sense of the complex data?
By harnessing IBM Watson Analytics, AOU can pinpoint key drivers of student progression and retention, and develop targeted initiatives to help struggling students get back on track for success.
Deliversinsight that empowers AOU to develop initiatives that help students succeed
Helpsboost student retention and progression rates, creating stable revenue
Up to 11%revenue loss avoided by redesigning core courses
Business challenge story
Identifying struggling students
With independent campuses across eight countries, the Arab Open University (AOU) is a very diverse organization. It faces the same challenges as any modern university, anywhere in the world: attracting and retaining students, maintaining high academic standards, and preserving financial sustainability. At the same time, its international scope means that its top-level strategies also need to respect the unique cultural, legal, academic and financial situation of each national campus.
Professor Ashraf Hussein, Dean of the Faculty of Computing and Engineering and Vice President for Information and Education Technology at AOU, explains: “Each campus is governed by its local Ministry of Higher Education (MoHE) requirements and affected by different socio-economic conditions and school education standards. This means that it’s challenging to obtain a comprehensive analysis of students’ academic performance and achievements.”
Professor Hussein continues: “We were struggling to really separate the drivers that contribute to student performance. This made it a challenge to know where to start when devising strategies to help failing students, and therefore boost progression and retention rates. The data is simply too complicated to understand using only spreadsheets—you need to be able to see not only the data itself, but the relationships between different areas, how it’s trending, and what’s going on behind the scenes.”
Professor Hussein recognized that an analytics solution could help: “I decided to do a study to investigate contributory factors behind student retention and progression rates—but first I needed the right tools for the job.”
As part of its strategy to double student numbers over five years, AOU set out to improve student progression and retention rates. However, the organization’s complexity made it difficult to identify key factors related to student progression and retention.
Implementing an analytics solution
Professor Hussein began looking for an analytics solution that could provide instant insight, and was easy enough to use that it could potentially be made available to AOU students in the future.
He notes: “As a former IBM employee, I already had a good understanding of IBM technology and culture—so when I heard about IBM Watson Analytics, I saw that it would fit the bill. Its point-and-click format is much simpler to use than the other solutions we considered, and it has built-in predictive analytics capabilities that others don’t. What’s more, I tested the accuracy of the predictive analytics and it scored very highly. It was an easy decision to implement it.”
IBM Watson Analytics is a smart data discovery service that guides data exploration, automates predictive analytics, and enables easy dashboard and infographic creation, empowering users to effortlessly gain insight and share findings.
“IBM Watson Analytics gives you a host of capabilities in a single place, whereas most other solutions are more like a set of separate tools that you have to keep switching between,” notes Professor Hussein. “It’s also very easy to collaborate and share data on the platform; for example, we use the ‘Expert Storybooks’ feature to quickly build interactive presentations to share findings.”
With the IBM solution in place, Professor Hussein had the tools to study the drivers behind student retention and progression rates (the progression rate being defined as how quickly a student completes their course).
“To start with, we conducted a study over several years to see how progression and dropout rates trended over time for the Information Technology and Computing Program (ITC),” says Professor Hussein. “We found that the semester-to-semester dropout rate fell over the course of the study, demonstrating that our efforts to improve quality standards across the university have been effective. We also discovered that students doing lower-level courses have a much higher dropout rate than those doing more advanced courses, a finding that warrants further exploration.
“Analytics has revealed that enhancing the quality assurance and standards within the Faculty of Computing and Engineering improves the overall dropout rate by an average of 18 percent, while also enhancing the relative efficiency of each branch in administering the ITC program by an average of 10 percent, throughout the considered duration from Fall 2013 to Fall 2017. In addition, we’ve confirmed that Kuwait, Bahrain and Egypt are working close to the optimum staff (full and part-time) to student ratio.”
“In the second phase of the study, we developed key academic performance indicators [KAPIs] for ITC Program courses, and then monitored trends and investigated contributing factors. For example, one important KAPI was the percentage of withdrawn students; that is, the percentage of students who drop out of a course. We saw that the standard deviation of a student’s course results was an important driver behind this KAPI, along with their country of origin, and their course level—again, those studying lower-level courses were more likely to drop out.”
He adds: “The IBM analytics solution is vital in enabling us to run these studies, and identify the contributing factors and warning signs for struggling students.”
Boosting student retention rates
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.”
About Arab Open University
The Arab Open University (AOU) is a sustainable development and educational non-profit project established in 2002 by HRH Prince Talal Bin Abdul-Aziz, the Chairman of the AOU Board of Trustees. AOU is headquartered in Kuwait and has a further seven country campuses in Lebanon, Jordan, Saudi Arabia, Egypt, Bahrain, Oman and Sudan. Under a partnership agreement with the Open University in the UK, AOU offers a range of undergraduate and postgraduate academic programs taught in English.
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