What retention means
Retention is usually defined as the share of students who remain enrolled from one point to the next, such as from one term to the next or from the first year to the second. It is related to, but not the same as, completion of a single course or graduation from a program. Different studies use different definitions, which is the first reason their numbers cannot always be compared.
A hypothetical example: if 500 students start a term and 400 are enrolled the following term, retention is 400 divided by 500, which is 80%. Whether that is good or poor depends on the type of institution, the students and what counts as leaving. Students who transfer elsewhere, pause study or finish early may be counted as leavers in some datasets and not in others.
Why open materials might plausibly matter
The argument connecting openness with retention is mostly indirect. It runs roughly as follows.
- Course materials add to students’ costs, and cost pressures are one of several factors associated with why students leave. A financial barrier may lead some students to delay purchases or drop a course.
- When required materials are free and available from the first day, some students may be less likely to fall behind early.
- Reducing the number of courses a student has to drop, retake or abandon could, over time, support staying enrolled.
This is a plausible chain of reasoning, not a proven one. Each link depends on circumstances: many students leave for reasons that have nothing to do with materials, including work, family, health, academic difficulty and loss of motivation.
What studies tend to report
Researchers have generally approached the question in a few ways. Many compare course-level outcomes, such as whether students stay until the end of a course or the next term, between sections using open materials and sections using conventional ones. Reviews of that kind of work commonly report results that are neutral or modestly positive, with some studies reporting no difference. The differences reported tend to be small and are sometimes concentrated in particular groups, such as students with lower incomes, although the evidence for such targeted effects is limited and mixed.
It is worth being careful here. A study that reports a modest improvement in staying enrolled in one subject at one institution does not show the same effect elsewhere. Likewise, absence of a measured effect may reflect a study too small to detect one.
Why retention studies have limits
Selection. Instructors or departments that adopt open materials are often unusually engaged. Students may also pick sections for reasons that affect their persistence. Both can produce differences that have nothing to do with the materials. This is the familiar problem of correlation causation.
Confounding changes. If an institution adopts open materials as part of a wider student success push, with tutoring, advising or schedule changes, it is difficult to separate the effect of the materials from the rest.
Time horizon. Retention across years needs long follow-up. Many studies look only at one term, which says little about staying enrolled over a degree.
Small differences, large noise. Suppose a hypothetical group of 600 students using open materials has 450 return, which is 75%, and a comparison group of 500 has 365 return, which is 73%. The gap of two percentage points could easily be due to chance or to differences between the groups. A stated gap needs a sense of its uncertainty.
Missing denominators. If a study counts only students who finished the first week, early leavers vanish from the data.
Interpreting percentage changes
Percentage points and percentages are different things. In the hypothetical figures above, moving from 73% to 75% is a rise of two percentage points, which is a relative rise of about 2.7% (2 divided by 73). Both descriptions are correct, but they sound very different, and headlines sometimes pick whichever sounds more impressive. The basics of percentage calculations and thoughtful reading of misleading charts help here, particularly when a bar chart’s axis starts above zero and makes small gaps look large.
What a good retention evaluation looks like
- It defines retention, including the starting group and the time window.
- It compares similar groups, adjusting for prior attainment and other known differences.
- It reports the number who started, the number who stayed and how leavers were counted.
- It follows students long enough to be meaningful.
- It acknowledges other changes made at the same time.
- It reports uncertainty rather than a single number.
Institutions that want to understand their own situation can use retention evidence from their own records, ideally with a baseline from before the change, while remembering that results from one setting do not automatically transfer to another.
A measured conclusion
Open materials may help some students stay enrolled, mainly by removing a cost barrier early in a course, and the research that exists is mostly consistent with neutral-to-modest effects. It does not support the claim that open education on its own solves retention. Treat any strong promise with caution, look at how retention was counted, and expect results to vary with the students, subjects and supports involved.