Identifying At-Risk Online Students

An article in Inside Higher Ed featured a community college and a for-profit online university which are both using features of learning management systems to track student engagement data and alert faculty and administrators to online students who may be at risk. This is one of the advantages in online instruction: student engagement in the course can be more thoroughly recorded and documented. We asked Mark Parker, assistant provost at University of Maryland University College, to offer some further advice on using LMS data to identify and respond to at-risk students.

Metrics to Watch

Parker recommends focusing on posting or conferencing as the most critical metric. In the first week of a course, look not only at whether the student has participated but also:

  • Have they met the minimum requirements (for example, word count)
  • How timely are they in submitting assignments?
  • Is the student having difficulty with university-level American English?

"If a student consistently posts her work at 11:59 p.m. Sunday night when the deadline is midnight", Parker advises, "this might be a red flag. It might indicate the student is too busy, or lacks time management skills."

"The first week is critical. If a student fails to engage in the first week in an online course not logging in, not responding to postings, not doing assignments that is absolutely a warning sign for a potential withdrawal or failure. Given the sheer pace and amount of material in an online course, the opportunities to fall behind are greater, and the opportunities to catch up are fewer."
Mark Parker, UMUC

Also, a student's writing skills are an early and important measure of whether the student is likely to succeed in the class. While this may be more of an issue in a writing-intensive course than a more technical course, nevertheless - because online learning is still so heavily text-based, much of the communication from students is written. Also, underdeveloped writing skills may signal difficulties in other courses and programs.

Bill Bloemer, dean of liberal arts and sciences at the University of Illinois at Springfield, adds that it is important to identify metrics related to prior academic performance:

  • Prior GPA
  • Any history of withdrawing or failing past courses

Bloemer also notes that you can track retention rates in particular courses over time. "There are some courses that no one ever drops," he remarks, "and other courses that students drop routinely." Knowing these patterns can help you identify where there is a higher probability that students will be at risk.

Best Practices

First, decide on the metrics you intend to track as early as possible. "It is always better to set up your data collection, your metrics, and your analysis right way, rather than retrofitting it later to a large online program."

"Most of us involved in online instruction have been so busy the past few years that I'm not sure we've stopped to think this all the way through what should we be measuring, and what will these things tell us? The earlier you can address these questions, the better."
Mark Parker, UMUC

Second, Parker suggests, have your faculty be the 'eyes and ears' online - that is key. Ensure that early warning is a core component of training for faculty who will be teaching online. Make sure that faculty understand how critical the first week is, that they know what warning signs to look for, and know how to respond.

"We rely on faculty tremendously for courses that are delivered online. While we have resources available - an online writing center, etc. - the faculty are the key to identifying students who may need assistance."
Mark Parker, UMUC

Finally, "give the faculty an office or an advisor who can handle the outreach to students," Parker advises, "so that the faculty can continue to focus on teaching the course."