Student Retention Improvement with IBM SPSS

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Student retention is one of the most increasing challenges of higher education administrators as they always struggle to improve graduation rates and reduce the loss of tuition revenue.

Understanding why students leave is essential to stop further withdrawals. Research shows that there is a disconnect between the real reason why students withdraw and why education administrators think they withdrawal. In this scenario, collecting data and analyzing information can be critical to improve student retention rate.

One of the most famous universities in Australia, University of Western Sydney, applied IBM SPSS to uncover the secret of student retention. “At the time, we were working on a data collection project, but our vision for the future involved using the predictive analytics capabilities of SPSS too,” says Neil Durrant. “Student retention is an area where this investment can really pay off.”

“While we were working on the models, we found some other correlations that were quite unexpected,” says Neil Durrant. “For example, students who make a lot of changes to the course units they select are at very high risk of dropping out. For the moment, we’re putting these students in a separate, fourth category so that we can research why this happens.”

Cresco International helps universities to better understand and improve student retention. In our previous projects, historical data, including students’ demographics, academic performance, course evaluation and other information, were used for analysis. Based on the data, we were able to identify different types of student withdrawals, reasons for withdrawals, and several key features that related to student retention.

Moving from historical to predictive analysis, IBM SPSS modeler can be employed for further exploration on text-mining and predictive modeling. Several critical variables, which were found in previous steps, were incorporated in the model building process.

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With IBM SPSS modeler, higher education institutions would be able to track student’s behavior patterns and predict their retention rate based on collected data. In this way, the university mitigates potential losses from students leaving.

For more information on how your University can use IBM SPSS, connect with us today at crescointl.com.

2 replies
  1. martin davies says:

    curious to know if there are different retention rates based on the nature and difficulty of courses.. example science vs liberal arts… also interested to learn can we use predictive analytics to improve student intake and offer places to those potential students that bring characteristics/attributes that indicate a high probability of their completing the courses they embark on. also what ratios of those attending with student loans vs grants vs self-financed vs corporate sponsorship… etc.

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