When estimating the returns to education, you can measure education by adding a quantitative variable school years, or as a set of indicator variables representing the different levels of education. What are the advantages and disadvantages of either approach?
The advantage of years of education over educational levels is that you just get one effect of education; it is a more parsimonious model. Moreover, in some educational systems you could argue that it represents the "investment" in time the respondent made.
However, this won't work in all educational systems. In many European ones students need to choose early on (e.g. age 10 in Germany) between different tracks. In those tracked systems having the same number of years of education correspond to very different levels of education.
If you have the real years of education, then does someone that had to repeat a year have more education than someone who attained the same level in one go?
If you are measuring education within a specific country, then I encourage you to throw in as many variables as you have to account for quality of education. I am sure everyone who's been to school (of course that is everyone here!) remembers that we don't all come out equally educated after 12 years of grade school. Across states/provinces, even within classrooms, this gap may be huge. Also different universities produce different levels of education. E.g. an Ivy League university, on average, produces better alumni than a community college.
If you are doing a cross-country analysis, then you will probably only have years of schooling from Human Development Indicators available to you. But there Kazakhstan will come out on the same level as Singapore. No offense to the post-soviet state, just making a point.
In any case you would have to control for a lot of different variables to reflect the quality of education. I would make your decision whether to use categorical or continuous variables based on what goes better with the other variables available to you. In fact, I would do both ways and check which one produces more convincing and statistically significant results and pick the best one. There is no crime in looking for good data.