By the time a midterm grade tells you a student is struggling, most of the term is already gone. The data an LMS already collects, logins, submissions, time on task, whether the first assignment came in, can surface a drifting student in week two or three, while a short conversation can still change something. The value sits entirely in what happens after the signal: a person reaching out.
Here is how institutions build that well.
The signals that predict something
Not everything on the analytics dashboard is useful. The signals that consistently line up with a student needing help early are simple ones. A first assignment or quiz that is missing or very late is the strongest single early indicator in most courses. No LMS activity in the first week to ten days, in a course that requires regular participation, is another. So is a sharp drop from an established pattern. A student who was logging in daily and suddenly stops. So is a missed first low-stakes checkpoint, in a course designed with one.
Raw “engagement scores” that blend many metrics into a single number are harder to act on and easier to misread. A few clear, course-specific triggers work better than one sophisticated composite.
Route the signal to a person, with real context
An alert that lands in a report nobody reads does nothing at all. What works is routing a flag to a named person, the instructor, an advisor, a success coach, depending on the institution, with enough context to make the contact useful: which course, which signal, and a suggested first message.
Institutions differ on who owns the outreach. Faculty-initiated works well in smaller courses where the instructor already knows the students. A central advising or student-success team works better at scale, and for students flagged across more than one course. Many run both, with a rule for which cases go where.
Keep it supportive, and say so out loud
An early-alert practice is, mechanically, a form of watching students, and it lands very differently depending on how it is framed and run.
Tell students the practice exists and what it is for, in the syllabus and again in the first week: “if it looks like you might be getting behind early, someone may check in. That is us trying to help, not a mark against you.”
Make the first contact a genuine offer, not a warning: “I noticed the first assignment is not in yet. Is everything okay? Here is how to get an extension or catch up.”
Focus on the earliest, lowest-stakes signals, where a nudge is most useful and least alarming to receive.
Do not attach consequences to the flag itself. The flag is a prompt for a conversation. The conversation is where anything gets decided.
Watch for disparate patterns. If outreach is landing disproportionately on one group, that is worth understanding. It may reflect the signal, the courses, or something in how the practice is being run.
Start small
Institutions often begin with one clear trigger, “first assignment not submitted by day 10”, in a set of high-enrollment gateway courses, routed to advisors with a template message, then check whether the students who got a contact did better than a comparable group who did not. That is enough to learn whether the practice helps on your campus, and to refine the triggers before expanding further.
The technology here is mostly already sitting in the LMS or the student-success platform. What makes it work is the human process built around it: the right signals, a person who reaches out, and a framing students experience as support rather than surveillance.
Charlie Wrightmann is a consultant at Wrightmann Education Technologists. Part of the Learning Platforms series.
References
- EDUCAUSE. ECAR research on learning analytics in higher education. https://www.educause.edu/
- Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68