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A new certificate course through the College of Professional and Continuing Education helps students master cutting-edge data analytics tools for their practical use in higher education, with relevant, hands-on lessons to prepare them for real-life university research and student success scenarios. 

Through the Applied Data Analytics for Higher Education course, students without a background in advanced mathematics or statistics can gain tools and knowledge for making informed, data-driven decisions in a higher ed setting. It’s one way ɫ��ɫ is expanding access to new opportunities for both traditional and non-traditional students to gain learning and research experience — a university strategic priority. 

The course, for which students will earn a certificate and digital badge upon completion, is designed to impart foundational knowledge of coding tools, like Python, and the ability to apply real-world metrics in solving institutional challenges. Its curricular blend of data analysis and educational applications is unique, said Kagba Suaray, Ph.D., professor in the department of Mathematics and Statistics, who is teaching the course. 

“You could go on the market right now and there are a gazillion coding classes on Python,” he said, “but there isn’t anything that marries [coding and educational application]. And that’s what the certificate is.” 

The course is open to all students, graduates, ɫ��ɫ faculty and staff, and professionals in higher education — as well as anyone looking to transition into the field. What makes this program different from all other available certificates, its instructors say, is its hands-on approach: it uses real data and real code to drive real impact. 

Modernizing its methods

The bedrock of the course curriculum was developed organically — almost unexpectedly — over time, said Juan Apitz, associate director for Academic Planning and Enrollment, who is also teaching in the new program.  

Noticing a trend of new hires in ɫ��ɫ’s Office of Institutional Research and Analytics (IR&A) lacking experience with some of the systems used by the team, Apitz and Mahmoud Albawneh, assistant vice president for the office, started writing down their practices and processes. 

Soon, they realized they’d developed a trove of useful materials outlining various tools and trainings.  

“When we had enough material, it was like, we really should be formalizing this,” Apitz said.  

The duo enlisted Suaray, who teaches in the Master of Science in Applied Statistics program, to help them develop an academic course from the training documents they’d created.  

It was a natural partnership, Suaray said, as the curriculum covered in his master’s program closely mirrored the work that Apitz and Albawneh were steering IR&A toward. 

“As they were applying more advanced methodologies... we were doing the same thing in the applied statistics master’s program,” he said. “This work was being done in parallel.” 

The advancements IR&A were employing were vastly improving the department’s efficiency and ability to apply data in meaningful ways. For example, estimating student yield — the percent of students who enroll after being accepted to ɫ��ɫ — “was a process that when we got here was very archaic,” Apitz said. 

“It used to be [Institutional Research] needed a month to create a yield. Now we can do it in a day,” he said. 

“Those are the kinds of things we want to teach to people.” 

Using Machine Learning to estimate admission yields at the student level also greatly improved accuracy compared to older methods, Apitz said. The office’s use of modern data technologies has supported the enrollment planning process, as well, and the team in 2021 was recognized for its role in virtually achieving ɫ��ɫ's enrollment goal that year. 

Skills to create meaningful impact

Broken into three separate courses, the goal is for students to walk away from the Applied Analytics for Higher Education series with stackable micro-credentials. The program is self-paced, with engaging videos, quizzes, and other activities. And unlike some other asynchronous programs, Apitz, Suaray, and Albawneh — who is also teaching in the program — will also host office hours for students to get additional support.  

With the knowledge they’ve gained, students who complete the course can expect to be able to use higher education metrics to analyze and apply relevant data in impactful ways in higher education. For example, one application of their skills could be performing the critical task of leveraging algorithms to help identify students at risk of failing or dropping out. This process is vital for helping shape student success strategies on campus, Suaray said.  

“Having additional tools to help students along their journey is a game changer,” he said. “These are skills that students taking this course will be able to be proficient in.” 

Tailored to bring these concepts to a wide swath of students, the course is designed to prepare them to be practitioners, able to understand and implement modern data tools and skills, including the use of Generative AI in coding.  

“It's not a replacement for expert knowledge and the ability to make decisions, but it’s a support system,” Apitz said. “And by having better technology, by having a better skillset, this is going to filter up to the leadership, because they are going to have access to better research in a more timely matter. And if leadership can make better decisions, then our mission is enhanced.” 

The first course in the series will launch June 9. Students can