When it comes to continuing education and skills-based learning, one of the biggest challenges that universities face is ensuring quality and uniformity of results.
Students trust universities to deliver on the promise that every topic taught is relevant, marketable, and will lead to clear returns on their investments (ROIs). But how do universities respond to changing market demands and variable classroom profiles, while also administering to the needs of thousands of students each year? How can institutions create a responsive classroom?
This is where data analytics comes in. By building infrastructures for data analysis, universities can more readily glean insights from the classroom and more quickly respond to the needs of students and employers alike.
In our own university-partnered web development program, we make use of a range of data analysis tools to create the responsive classroom, such as those for tracking everything from student sentiment and GPA distribution, to curriculum pacing and difficulty level, to market demand and requirements for job opportunities.
Strong Programs and Student Perception
The outcome of this responsive classroom investment has been an enduring ability to create strong programs with a highly consistent student experience across our programs in various markets.
As an example of our data-driven approach to program management, we’ve long invested in regular monitoring of student perception. As any struggling student in web development will say, part of the barrier to success lies in the challenge of maintaining motivation and confidence against increasingly difficult subjects. For this reason, we conduct frequent “check-ins” to quantify students’ perception of soft-factors like pace, self-mastery, instructor engagement, and more. This feedback, when coupled to student data on performance and grades, allow us to identify trends, remedy early situations, trigger curriculum changes, and compare classrooms for consistency and accountability.
Since our programs first began, we’ve collected over 4,500 student feedback reports and counting.
Yet, as important as data analysis has been to our understanding of the responsive classroom, it has been even more important to understanding the market conditions outside. In the fast-changing world of technical trades and digital skills, now more than ever is it necessary to rely on market data in curriculum design. For this reason, we constantly benchmark our programs against real-world feedback from employer partners, regional job data, and validated market trends.
This is a trajectory we expect will continue across continuing education programs, both inside and outside of technical fields.
Quality assurance has always been a top of the mind concern for continuing education. Based upon everything we’ve learned from our university-partnered programs, we believe better data analysis is a critical key in delivering true ROI to students.