If you run a tutoring or learning center, you have probably heard the DFW rate come up in meetings about retention, your budget or gateway courses. Those are the introductory courses students must pass to move on in a program. Provosts and institutional research (IR) offices use it to find the courses where students most often struggle, sometimes called DFW courses. It is also one of the few outcome measures your center can influence, because tutoring and Supplemental Instruction (SI) serve many of the students at risk of earning those Ds, Fs and withdrawals.
The number only helps if your campus calculates it the same way every term and your center keeps visit records that show which course each student came in for.
Key takeaways
- A DFW rate is the percentage of students in a course who earn a D or an F or withdraw, and it shows which courses students struggle with most.
- You calculate it by adding the Ds, Fs and withdrawals in a course and dividing by the number of students enrolled on the census date, just after the drop deadline.
- The highest rates usually sit in large first-year gateway courses, and a D or F in the first term is linked to lower graduation rates.
- To show that tutoring lowers a DFW rate, you need visits recorded against each course and a fair comparison group, not only a visit count.
What is a DFW rate?
A DFW rate is the percentage of students in a course who finish with a grade of D or F or who withdraw after the drop deadline. Campuses calculate it for each course and section to see where students need more help.
An F earns no credit, and neither does a withdrawal, which shows as a W on the transcript. If the course is required, the student has to take it again. A D often earns credit, but at many colleges it does not meet a prerequisite or major requirement that asks for a C or better. A student with a D may therefore still have to repeat the course.
DFW, DFWI and other versions
Campuses do not all count the same grades. Some add incompletes and call the measure a DFWI rate, and some also count grades such as WF (withdrawn while failing) or U (unsatisfactory). Rates built on different definitions cannot be compared, so ask your IR office which version it uses and keep to it every term.
What counts as a high DFW rate
There is no national standard for a high DFW rate, but the best-known cutoff comes from SI. SI is a set of peer-led study sessions attached to a difficult course, and when it was developed at the University of Missouri-Kansas City, its developers targeted “historically difficult” courses. In those courses, more than 30 percent of students earned a D or F or withdrew, semester after semester. Many campuses still use a cutoff of that kind to choose courses for extra support.
Compare a course with its own record over several terms before you compare it with other courses. A small section can swing by several points from one term to the next, but a rate that stays high across terms and instructors points to the course itself.
How to calculate a DFW rate
To calculate a DFW rate, add the Ds, Fs and withdrawals in a course, divide by the number of students enrolled on the census date, and multiply by 100.
DFW rate = (D grades + F grades + withdrawals) ÷ students enrolled on the census date × 100
Who counts as enrolled
The drop deadline ends the add and drop period. The census date usually falls just after it, and that is when your college takes its official enrollment count. A student who drops before the census date leaves no grade and no W, so they are not part of the rate. The withdrawal deadline comes weeks later, and a student who leaves between the census date and that deadline receives a W and counts. Some offices divide by the number of grades given instead, which gives the same result when every enrolled student receives a grade. Decide once, too, how to treat audited and pass/fail enrollments, because counting them differently from term to term changes the rate.
A worked example
Take one section of an introductory course with 120 students on the census date. At the end of the term, 9 students earned a D, 14 earned an F and 7 withdrew. That makes 30 students, and 30 divided by 120 is a DFW rate of 25 percent.
Now split the same section by how often each student used tutoring for that course. The numbers are made up to show the arithmetic. Say 40 students visited the center three or more times for the course, and the other 80 came less often or not at all:
| Group | Students | D | F | W | DFW rate |
|---|---|---|---|---|---|
| Three or more tutoring visits | 40 | 3 | 3 | 2 | 20 percent |
| Fewer visits or none | 80 | 6 | 11 | 5 | 27.5 percent |
| Whole section | 120 | 9 | 14 | 7 | 25 percent |
A gap like this is what a budget committee will want to see, but it does not prove that tutoring caused it. Students who come for help can differ from those who stay away, so the comparison needs a fair method before you report it.
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Why DFW rates matter
DFW rates run highest in large first-year gateway courses, and that matters because an early D or F is linked to a lower chance of graduating on time.
In a 2021 study, eight Big Ten universities, including Indiana, Penn State and Rutgers, found the highest rates in college algebra, precalculus, calculus I and introductory chemistry. They also found that first-generation students (the first in their family to attend college) earned more Ds, Fs and Ws than other students. So did students eligible for Pell Grants (federal grants for students with financial need). Among the students who entered in 2014, those with one D or F in their first term had a four-year graduation rate 24.9 percentage points lower than students with none.
The universities note that this link is not causal, since a D or F can signal problems that would have slowed the student anyway. Those courses are still where your center’s support reaches the most students at the point they are most likely to fall behind.
How to lower DFW rates
You can help lower DFW rates by focusing your center’s support on the few courses where rates stay high, and by reaching students while they can still recover. Course design and grading belong to the faculty, so these are steps your center can take on its own or with a department’s agreement.
Start with the courses that stay high
Ask your IR office for the DFW rates of the courses your center supports, over several terms, with enrollment beside each rate. The courses that combine high rates with large enrollment are where the same tutoring hours reach the most students who need them. Pick a short list of those courses, because a short list is easier to staff and to measure than a promise to cover everything. Then share the rates and your visit data with the instructors who teach them, and agree where tutoring or SI fits their syllabus.
Bring structured support into those courses
Drop-in tutoring waits for students to decide they need help, and the students heading for a D, F or W may never decide to come. SI goes to them instead, because its sessions are scheduled for one course and led by a student who did well in it. Embedded tutoring places a tutor inside the class itself.
A 2014 systematic review in the Review of Educational Research found that students who attend SI earn higher grades and fail or withdraw less often, which matches what the U.S. Department of Education reported in the 1990s. That is a correlation, so it cannot say whether the students who attend were already stronger, and you will meet the same question when you measure your own program.
Reach students before the withdrawal deadline
A faculty referral early in the term can lead to tutoring, while the same referral after the withdrawal deadline leaves the student few options. Time your early alerts so faculty raise concerns while students can still recover, and send every referral to a named person who contacts the student. Our guide to identifying at-risk students early in the term covers that route, from the referral form to the reply faculty receive. A withdrawal is sometimes the right call, for example after a family emergency, but even then the student should decide with an advisor.
How to show your center’s effect on DFW rates
To show your center’s effect, compare the DFW rate of students who used the center with similar students in the same courses who did not, and repeat it every term. A course’s rate can fall for reasons that have nothing to do with tutoring, such as easier grading, so the course rate alone proves little. Finding similar students is the difficult part. Students who choose to come may be more motivated than those who stay away, which makes tutoring look better than it is. They may also be the ones already struggling, which hides its effect.
Build a fair comparison
These steps give you a comparison a budget committee can trust:
- Record the course at every visit, so a visit to the math lab counts toward the right course.
- Get the course rosters and final grades from your IR office or the registrar. Agree who sees student-level results under your campus’s FERPA policy (FERPA is the federal law that protects student records).
- Group students by how often they visited for that course, such as none, one or two, and three or more, and set those cutoffs before you see the results.
- Count visits only up to a fixed point, such as the withdrawal deadline, because students who withdraw early have less time to visit.
- Compare students within the same course and, where you can, the same instructor.
- Ask your IR office to match students on prior preparation, such as high school GPA or placement scores.
- Repeat the comparison for groups such as first-generation and Pell-eligible students, and pool sections or terms when a group has only a few dozen students.
Match students on prior preparation
Matching pairs each student who came with a similar student who did not, based on records such as GPA, so the gap stops reflecting only two different kinds of students. It cannot account for what no record shows, such as motivation, but it makes a gap more convincing. A study in the Journal of Experimental Education matched students this way across 21 courses. It found that SI participation was linked to higher course grades and retention, most strongly for students who attended at least five sessions. Because the students were matched first, that finding is stronger than a plain correlation.
Compare a course with its own past
When a new program starts in a course, its earlier terms make a natural comparison group. In one of our keynote webinars, the director of Ball State University’s learning center describes judging an embedded tutoring pilot against earlier semesters of the same courses taught by the same instructors. Whichever comparison you use, report it course by course with the number of students in each group, because a campus-wide average blends courses tutoring reaches with courses it barely touches.
What your tracking system needs to do
The comparison works only if every visit records the course it was for. A paper sheet with a course column can do that, but someone has to type every line before your IR office can use it. Your system also needs course rosters from your student information system (SIS) and an easy way to send visit data to IR.
Accudemia, the academic center management software we make, imports enrollment but not final grades, so it does not calculate a DFW rate by itself. What it gives you is the visit side of the comparison. At sign-in, you can ask students which service, course and professor the visit was for. If you make the course step required and limit the list to each student’s own classes, every visit arrives tied to a course. Scheduled imports keep those course lists current from your SIS, and they accept the single-file extracts that systems such as Banner and PeopleSoft produce, so nobody has to retype rosters.
Reports and exports for the comparison
You can break visits down by student, course, instructor or class, with each student’s total for each course, which gives you the comparison groups. The Zero Visits report adds the students your center never saw at all in a period.
For the rest of the comparison, you can build student groups such as first-generation students from demographic fields in your import. Session logs and enrollment can be exported by semester as CSV files that your IR office joins with final grades. SI sessions belong to class sections, so their attendance fits the same comparison, as our page on running SI programs in Accudemia shows. The full list of reports is on our reporting and analytics page.
How campuses use the data
Santa Barbara City College’s IR office uses the center’s Accudemia data to show the services’ effect on retention and success each semester, as a staff member explains in the college’s user spotlight. The Community College of Denver’s tutoring center designed its session questions with its IR office. The center credits the impact data it kept in Accudemia with saving it from closure in 2020.
What the system leaves to IR
Because final grades stay in your SIS, the DFW calculation happens where the grades are, usually in your IR office, using the visit export. Accudemia shows who came for help with which course, and the matching above is still what lets you judge whether that help moved the rate.
If you also want faculty referrals for early alerts, or more than one center, you need the full Accudemia License. Accudemia Light, the single-center edition, covers visit tracking, SI attendance, imports, exports and scheduled reports.
If your sign-in records who came but not which course they came for, request a demo of Accudemia and see visits, course rosters and term reports set up around your own courses.
Your first DFW report
A first comparison takes one full term of visits recorded by course, plus the weeks your IR office needs once grades are final:
- Ask your IR office for several terms of DFW rates for the courses your center supports, and which definition it uses.
- Choose about five courses with large enrollment and rates that stay high from term to term.
- Make the course a required step at sign-in before that term begins.
- At the end of the term, send your IR office the visit export and ask for DFW rates by number of visits, matched on prior preparation.
- Share the results with those courses’ instructors before the following term, and agree where tutoring or SI fits.
