IT Forum Perspectives

Help show faculty the return on effort for student success initiatives

by Kevin Danchisko

Helping students find success is considered everyone’s problem, but no one’s job. Although everyone on campus has a role to play in student success, it is also larger than any one person’s contribution. A disconnect between individuals’ efforts and students’ success can lead to frustration and disengagement. Faculty may ask themselves: "Does anything happen if I alert advising of a struggling student?" "What actually happens with the attendance data I collect?"

Faculty who can identify the relationship between their efforts and the success of their students are more likely to engage in ongoing student success efforts. This is why leaders at progressive institutions are leveraging results data to show the ROI of faculty time spent on student success.

Low adoption of technologies hampering student success efforts

Unfortunately, faculty adoption of technologies that collect data for student success purposes remains low across higher education. Data from Inside Higher Ed's "Survey of Faculty Attitudes on Technology" shows that over the last three years, the proportion of faculty using the LMS to track attendance has remained fixed at a low rate. In 2015, just 22% of faculty used the LMS to track all attendance, and 52% of faculty did not use the functionality at all.

Percentage of faculty tracking course attendance using LMS

While these trends can appear discouraging, low adoption may also reflect the central administration’s failure to demonstrate the return on investment (ROI) of these tools to faculty, who care deeply about student outcomes but have limited time to devote to new projects.

Creating a 'closed loop' for advising data at the University of Kentucky

Facing a similar disconnect between faculty activities in support of retention and student outcomes, leaders at the University of Kentucky decided to improve transparency through a ”closed loop” process. The University of Kentucky business intelligence (BI) team obtains faculty assistance to create optimal course-specific risk flags for students. When the BI team meets with faculty to establish automated risk flags, the team tests those flags in the moment against historical data and refines the suggestion using real student records.

The team then works with faculty to set the appropriate level of communication for different student risk profiles; for example, a low-risk student who received one low quiz score may receive a single alert, while a high-risk student may see more urgent, targeted outreach. These alerts are delivered through the University of Kentucky’s mobile app to reach on-the-go students.

See how your your institution's infrastructure could be a barrier to student success

Engaging Faculty Through 'Simple Triggers'

Engaging Faculty Through Simple Triggers

Most universities that establish risk markers stop at the creation process. The BI team at University of Kentucky, however, goes one step further by updating faculty members on student responses and actions taken, which enables faculty to understand what’s working. This allows faculty an opportunity to make real-time changes in their approach, content, and messaging. Aligning faculty efforts and student outcomes has shifted student success awareness from no one’s job to everyone’s responsibility.

What's the next step in data-informed decision making?

Institutions across higher education are striving to become more data-informed, but most still lack the data and resources they need to answer critical questions. In part one of our "Dean's Dashboard" series, you'll discover how progressive schools are using data to make critical decisions, and how it can work on your campus.

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