Title: Extracting Useful and Targeted StateLevel Data from IPEDS
1Extracting Useful and Targeted State-Level Data
from IPEDS
- Experiences from the Land of 10,000 Lakes
2Minnesota Measures
- First of a planned annual series of reports
related to accountability - Timeline
- May 2005 (initial charge to work on project)
- August 2005 (appropriations, NCHEMS contract,
initial meetings) - November 2005 (discussion of goals and
indicators) - January 2006 (statewide meetings)
- March 2006 (review of goals and indicators)
- June 2006 (NCHEMS final report)
- September 2006 (meetings with systems)
3Indicators Goal 1Improve success of all
students, particularly students from groups
traditionally underrepresented in higher
education.
- College participation rates
- IPEDS data
- First to second year retention
- 3-, 4-, and 6-year graduation rates
- Degrees awarded as a proportion of total
headcount enrollment - Degrees awarded in critical fields (STEM and
healthcare), disaggregated by race/ethnicity - Proportion of young adults (25-34) in the state
holding a postsecondary degree
4Indicators Goal 2Create a responsive system
that produces graduates at all levels who meet
the demands of the economy.
- Credentials awarded at each level (IPEDS), per
1000 people 20 and older in the states
population (ACS). - Proportion of credentials awarded at each level
in STEM fields and number awarded (IPEDS) per
1000 people 20 and older (ACS). - Proportion of credentials awarded at each level
in healthcare fields and number awarded (IPEDS)
per 1000 people 20 and older (ACS).
5Indicators Goal 3Increase student learning and
improve skill levels of students so they can
compete effectively in the global marketplace.
- Did not gather data in this area for the initial
report. - Currently looking into a variety of assessment
instruments. - Aware that IPEDS COOL will incorporate assessment
results in the future.
6Indicators Goal 4Contribute to the development
of a state economy that is competitive in the
global market through research, workforce
training and other appropriate means.
- The share of national academic research being
done in Minnesota - The ranking of the University of Minnesota on
various studies of research activity (University
of Florida report, London Times, Shanghai study,
and Newsweek) - Total research expenditures in the state as a
proportion of gross state profit
7Indicators Goal 5Provide access, affordability
and choice for all students.
- Proportion of residents aged 18-24 and 25-44
participating in postsecondary education (ACS) - Assigned family expectation (OHE data)
- Using NPSAS data
- Net tuition (after grants and scholarships)
- Average borrowing and rate at which students
borrowed
8Some Findings
- In general, Minnesota does not consistently rank
among the top states. More often, were near the
national average. - The degree attainment of our citizens is high,
but that is due in part to in-migration of
college-educated citizens from other states. - Native American, Black, and Hispanic students in
Minnesota do not do well in college compared to
their white and Asian counterparts.
9Using the Dataset Cutting Tool (DCT) to get
State-Level Data
- Create a custom dataset
- Advantages
- Web-based interface
- Very customizable, can get data from multiple
files over multiple years - Can create a file that you can download
- Disadvantages
- Interface can be cumbersome
- Time-out issues
- Limited to 1,000 institutions in creating the file
10Using the Dataset Cutting Tool (DCT) to get
State-Level Data
- Download entire data file
- Advantages
- Very straightforward
- You get all of the data for all institutions
- Can be imported into a program like SPSS, SAS or
Access for report generation - Disadvantages
- You get all of the data for all institutions,
which includes a lot of imputation fields - Data dictionaries are cumbersome
11What We Did
- Download entire data files
- Import into an Access table, to provide control
over - Which fields were brought in
- The data type of those fields
- The names of the fields
- Consider a sample
- Building queries helps a great deal, as results
can be copied/pasted into Excel for easy
manipulation - Why not just take data directly to Excel?
- Limits on Excel table size
12Successes
- Getting state-level data is reasonably easy
- Crosstab queries
- Reports
- State and national averages
- Beware of averages of averages
- Actual averages reasonably easy
13What We Will Do Differently (regarding our use of
IPEDS data)
- Degrees awarded as a proportion of total
headcount enrollment will be rethought - Goal incorporate part-time students into a
degree completion measure - Needs more context
- May talk more about and give more detail about
transfers out - No more mixing of IPEDS and ACS data
- May look more deeply into the use of DAS
14Observations
- Data dictionaries (e.g., imputation variables)
- Variable names in general
- Lack of retention data by race
- Which is being addressed in part by new IPEDS
data collection procedures - But only for SMART grant fields
- Loss of transfer students and part-time students
in computation of graduation rates
15For More Information
- On Minnesota Measures
- The on-line version is available at
- http//www.ohe.state.mn.us/mPg.cfm?pageID1733
- You can also download a .pdf version of the
entire report from this page. - On the Office of Higher Education
- http//www.ohe.state.mn.us
- jim.bohy_at_state.mn.us