Last month I posted on my own blog about listening to Dr. Catherine Pareonseault, Senior Education Specialist - Academic Programs in the Academic
Affairs and Research Division of the Texas Higher Education Coordinating
Board (THECB) talk about
the terrific data sharing that was going on between K-12, higher education, and
the Texas Workforce Commission (TWC) in Texas.
I was intrigued (and jealous!) hearing her talk about how
they were able to track people from high school through multiple stops in two
and four year institutions, then several years out into the
workplace. Determined to learn
more, I followed up and a few days ago had a chance to speak with Dr. Gabriela
Borcoman, one of the lead staff in the THECB Division of Planning and
Accountability and integral in the development of the Automated Student and Adult Learner Follow-Up System (ASALFS).
Most basically, I was curious about the architecture of this
multi-system data integration. In
essence, THECB collects data from the various post-secondary systems in the
state (public and private). They also collect data from K-12 schools, and they collect data from the TWC on their participants. Dr. Borcoman explained how this model –
everything funneling up to the THECB – was critical because
FERPA rules make it
difficult for educational institutions to share data with workforce boards or other government agencies. Then she and her staff do the data
matching and analysis, all based on social security number.
Their analysis and reports are made available to institutions across the systems. All of the agencies share the cost of the data analysis
efforts by contributing funds based on the number of enrollments (and because
this reporting is mandated by the State legislature, there is limited griping I
am told).
So what kind of reports and analysis are they working
on? More than I can write about
here. Most of it has to do
with where enrolled students end up 1, 2, and 5 years after enrollment. Do they transfer? How well do they do when they transfer?
Complete a degree or certificate? What is their GPA?
Do they get jobs? In what industry? At what salary? In what zip code? In what occupation? For their annual reports they are able
to report on 75% of enrollees (they can’t track individuals who leave the state,
people who end up in prison, or otherwise disappear). When I asked about surprises in the data, Dr. Borcoman had
many. A few for you:
- In North Texas, the match between what local workforce boards identified as high-growth occupations had hardly any overlap with the most common occupations for very recent
graduates in the region. Time to
look critically at how those high-growth occupations were being forecast.
- Even when policymakers are right about certain
things – e.g. oil and gas industries are going to be a key driver of job growth
in Texas – there is risk of missing nuance. Do you know what occupation a recent graduate is most likely
to get when he/she joins the oil and gas industry in Texas? Accounting. Yes, I see the irony in that, but as workforce professionals
let’s focus on what this means programmatically – train more accountants.
- There were significant gaps between the average
starting salaries reported by post-secondary institutions (especially private
institutions) and the actual average salaries of graduates at 1, 2, and 5 years
out. This is important data for a number
of reasons, not the least of which is incoming students taking out large loans
anticipating large post-graduation salaries.
- Low transfer rates are a problem in Texas as
they are in much of the country. Many two-year institutions in Texas thought that their low transfer
rates were due to the fact that previous tracking only counted whether students
who had more than 30 credits moved on to a four-year institution whereas
anecdotally, they believed they were actually transferring many students who
had accumulated just a few credits. With this improved data integration, they were able to count more
carefully. It turns out that even when accounting for all those students who
move from two-year to four-year institutions with fewer than 30 credits, the
transfer rate barely inched up 2%.
- Finally, some of the cohort tracking is
great. For instance, a cohort of
1998 7th graders found that while the African American males struggle to
complete high school (of 21,000 African American 7th graders,
less than 13,000 completed high school by 2004), roughly 75% of those who do
complete high school enroll in post-secondary institutions. But then they struggle to finish, with only
about 1,500 earning any type of degree or certificate by 2009.
And more. If
you want to dive in, see ASALFS,
High School to College Linkages, and Community College Transfers.
The point here is that as cliché as it is, information is
power. This kind of information
enables administrators and policymakers to better understand what is happening
as individuals move through our educational and workforce systems and into
their careers. Dr. Borcoman says progress
is slow, but institutions in Texas are beginning to take note of this
information and think about how to scale up programs and practices that are
working and re-focus initiatives that aren't.
She talked about a culture shift – a move towards
data-driven decision-making and away from anecdotal and status quo-driven decision-making. The data certainly doesn't provide all
the answers, and it doesn't explain how to navigate the political and budget
intricacies of cross-system actions, but it can help focus the conversation on
tackling the right issues.
In my home state of California I suspect our state fiscal
crisis, higher education furloughs, and unemployment above 12% make investment
in such cross-system data integration unlikely in the near-term. Yet, I am hopeful that as progress is
made in clearing the logisitical hurdles of cross-system data integration, and
as decision-makers realize the value of such data, we will see such ambitious
efforts spread across the nation. And I hope that as workforce development professionals, we are among the
loudest champions.
Erica Bouris, Ph.D. is the Principal of B Square Impact.
