Trends are not forecasts
A trend is something that has been measured over time. A prediction is a claim about what happens next. The gap between them is where most mistakes occur. This article looks at the kinds of measurable trends that bear on open higher education, and then at how far each can reasonably be projected. It deliberately gives no specific figures, because numbers vary by country and year and should be taken from current official sources for the place you care about.
Enrollment patterns
Enrollment is the headline measure for universities. The numbers rise or fall because of many causes that have little to do with openness: the size of the age group leaving school, the state of the economy, immigration rules, fees and public funding. Countries differ markedly, and the pattern in one is a poor guide to another.
Two structural shifts are often discussed. One is the growing share of older and part-time students who study alongside work or family. The other is the gradual change in what students expect from a degree, including flexibility. Both are visible in many places but not everywhere.
How far can enrollment trends be extended? Short-term projections of the school-leaving population are usually more reliable than anything else, since the people involved have already been born. Beyond a few years, forecasts depend on policy and economic assumptions that can change quickly. Treat long-range enrollment predictions as scenarios.
Online and blended delivery
Online delivery grew in many systems well before recent years, and then rose sharply when in-person teaching was disrupted. The more useful question now is what stayed. Many institutions kept elements of blended learning, and learning management systems became standard infrastructure. Online degree programs exist in large numbers in some countries and remain rare in others.
A caution applies to extrapolation here. A jump caused by a one-off event does not tell you the long-run slope. Some students returned eagerly to campus, and others kept the flexibility they discovered. The honest conclusion is that online delivery is now a durable part of higher education, with its share uncertain and likely to differ by subject, level and student group.
It is also important not to confuse “online” with “open”. A course can be online and fully paid, restricted and copyrighted. A course can also be on campus and built on openly licensed materials. The two trends overlap but are distinct.
Costs and what students pay
Cost trends include tuition, living expenses, debt levels and the price of course materials. Textbook costs are only one component, and data on them depends on survey methods that vary between studies. Open materials affect that component directly, but their reach depends on how many courses switch and how many students would otherwise have paid full price.
It is reasonable to say that interest in lower-cost materials has grown, and that many institutions now have programs to encourage them. Extrapolating that into a claim that costs will fall overall is not justified: tuition and living costs are driven by quite different forces.
Adoption of open practices
Adoption can be measured in several ways: the number of courses listing openly licensed texts, the number of institutions with an open education policy, or the quantity of materials in public repositories. These measures often show gradual growth, but they are uneven. Counting resources says nothing about quality or use, and counting courses may miss partial adoption.
Credentials and employer behavior
Growth in micro-credentials and other short awards is another observed trend, though it is harder to measure than enrollment because definitions and recording practices vary. Whether employers value these awards is the crucial unknown. Surveys of employers exist, but their questions and samples differ, so a single reported figure should be treated cautiously.
A short checklist for reading predictions
- What is the base? A percentage rise from a small number can be a small absolute change.
- How long is the window? Three years of data rarely supports a twenty-year projection.
- What caused the change? If the cause was temporary, the trend probably will not continue in a straight line.
- Who is making the prediction? Vendors, advocates and critics each have reasons to emphasize certain data.
- Is it a forecast or a hope? Wording like “will inevitably” is a warning sign.
Predictions in this area also have a mixed record: many confident forecasts about technology transforming universities have proved overstated in pace, even where the direction was broadly right.
A cautious summary
On the evidence available, it is safe to say that online and blended delivery are established, that interest in lower-cost materials has grown, and that credentials are diversifying. It is not safe to say how fast any of these will move, whether they will reduce overall costs for students, or whether they will improve results such as graduation rates. Anyone planning should use local data, look for several years of history, and revisit assumptions as new numbers appear.