Quote from Steve Jackobs on October 1, 2026, 3:55 pm

Thank you for the September 22 discussion and subsequent comments. They are beginning to shape a proposal. A close tracking of student progress semester by semester toward the North Star of 70 percent completion will be important – not least for a decision on the sustainability of free tuition. Students’ choices and behaviors will drive the cost structure of free tuition. On the one hand, new high school grads may start ACC with substantial credits from dual credit programs, polish off their core classes in a year or so, and transfer to Texas State quickly. That will imply one cost structure. On the other hand, young students might find the financial, academic, and social value of ACC so high that they stretch out their time at ACC to the full three years and maximal credits. That will be a much different cost structure.

Given the different endowments and challenges of our 40,000 credit students, we need to disaggregate the student body into a limited number of high-level, meaningful profiles.

I propose that starting positions be the differentiating factor among four profiles.

1. “Direct-to College-Plus-One students with credits.” This comprises high school graduates with dual credits who enroll immediately after high school graduation or within one year. My assumption, to be tested by data, is that their academic readiness remains fresh even after a gap year.
2. “Direct-to College-Plus-One students without credits.” Similarly, these are high school graduates within a year of their graduation but without any credits.
3. “Later Young Learners.” These are students younger than 25 who enroll more than a year after high school graduation and consequently have experienced learning loss and other factors which inhibit their potential performance. Family responsibilities and work responsibilities are two examples.
4. “Adult Learners” (Age 25+) This is Ashley and her fellows. As we have seen, the free tuition pilot students’ levels of persistence and full-time enrollment have raised average performance. It is important that the free tuition pilot students’ good performance does not mask Ashley’s continuing struggles.

Given the HB8 funding 25% premium for three categories of students, it will also be important to track the percentages of each profile who are economically disadvantaged and/or academically disadvantaged. (Adult Learners is the third category and already awarded a 25% premium.)

Second, the report would establish for each category a “Future State” defining what a 70 percent completion would look like. The graphic format on page 8 of the September 22 deep data dive’s slide deck is brilliant and works for me. Undoubtedly a table presenting the same data in lines and columns will better communicate the information to other readers.  Still others may better follow trend lines.

See Graphic 1 on attached file. (The message board apparently cannot handle graphics.)

I expect the “Future State” of each profile would look different – dramatically so. For example, I could imagine that:

• The DTC students with credits might look like the Future State, Graphic 1 with a lot of transfers in the first year. Their cumulative “Stop Out” would be low relative to others.
• The DTC students without credits would not have as many transfers in the first year but might reach the same state by their third year.
• The Adult Learners would not have many transfers at all in the first year and not have many other completions until the third year.

I propose that the Trustees receive a high-level report shortly after semester end on the progress of students grouped by their profiles of starting positions. The report would track semester-by-semester the performance of a cohort and compare it to its projection toward its specific “Future State.” 

For example, the presentation of Fall 2022 sample data from page 8 (again brilliant!) gives onea sense of the scope, tasks, and priorities of work to be done.

See Graphic 2 of attached file.

Note that the Stop Out percentage of 31% After 1 Year is way higher than the 15% of the optimal Future State Stop Out percentage. Even if every other student had completed or transferred, the highest possible performance for this group could have been 69% and it could not mathematically reach the North Star. In fact, the completion of this cohort is 44%.

Given this large fraction of stop-outs, reaching a 70 percent completion in a cohort with so many first-year stop-outs would depend upon an aggressive dropout recovery strategy in Year 2, as well as extra efforts on persistence and academic progress.

Note also that the growth in Stop Outs between After 2 Years and After 3 Years is negligible – only 1 percent point increase from 38% to 39%. This suggests that students are seasoned after two years. The proper focus, tasks and priority between Year 2 and Year 3 would then be academic progress and completion more so than persistence.

Again, tables of lines and columns and/or trend lines may communicate this better to other readers. Thank you all for the discussion to this point. I look forward to further discussion.