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Off-Campus Recruiting by Public Research Universities
University of Arizona
University of California, Los Angeles
University of California, Los Angeles
This research was made possible by funding from the following sources:
- National Academy of Education/Spencer Foundation (Postdoctoral Fellowship)
- American Educational Research Association (Dissertation Grant)
- UCLA Office of Equity, Diversity, and Inclusion (Faculty Career Development Award)
- Joyce Foundation (Research Grant)
The problem with policy discourse about college access
The 2014 White House "Access Summit"
- The White House (2014a) review of causes of unequal college access
- Highlights "achievement gap", "under-matching"
- Commitments to Action on College Opportunity (The White House, 2014b)
- Universities pledge "action plans" (e.g., holistic admission, need-based aid, "outreach")
Problem with policy discourse
- Place responsibility on students, K-12 schools; assume universities are passive or progressive
Alternative explanation for access inequality
- University enrollment priorities biased against poor students and/or communities of color
Research focus (this paper)
- We argue recruiting behavior is an indicator of enrollment preferences
- Research question: What are the similarities and differences in off-campus recruiting patterns across public research universities?
The enrollment management industry
The enrollment funnel
Interventions along the funnel
- Identify prospects
- Recruit prospects remotely
- Recruit prospects in-person
- Off-campus recruiting visits (e.g., high
school visits, fairs)
- Campus visits
- Other "outreach"
- Solicit inquiries, stealth applicants
- Social media, advertising
- Convert admits to enrollees
Scholarship on the enrollment funnel
Most research analyzes admissions (e.g., Killgore, 2009) or financial aid (e.g., McPherson, Schapiro, 1998)
- Final stages of enrollment funnel
Scholarship on recruiting is sparse
- Audits of university response to inquiries (e.g., Hanson, 2017; Thornhill, forthcoming)
- Off-campus recruiting visits
- From the college perspective (Stevens, 2007)
- Important for relationships with prospects, counselors at "feeder" schools
- From the perspective of high school students (Holland, 2019)
- Which universities visit affects student decisions; especially first-gen, students of color
- We don't know which universities visit which schools and communities
- If poor students, communities of color are not being recruited, then "under-matching" may be due to under-recruiting rather than lack of guidance
Enrollment priorities and recruiting behavior
- Contingency theory (Thompson, 1967)
- Technical level vs. managerial level
- "New" institutional theory (Meyer and Rowan, 1977)
- Publicly adopt goals demanded by environment
- Technical level cannot pursue all goals
- Substantively adopt some goals (technical level)
- Symbolically adopt others (policies, rhetoric)
Application to enrollment management (EM)
- "Iron triangle" of EM highlights three broad enrollment goals: access, academic profile, revenue
- Resources scarce; depending on priorities, some goals receive more resources than others
- Enrollment priorities cannot be discerned by policies, rhetoric
- Recruiting is allocation of resources from technical level
- Knowing which populations targeted by recruiting interventions indicate enrollment priorities
The broader off-campus recruiting research project
- Web-scrape admissions websites
- Criteria to be included in data collection
- Post visits on admissions websites
- Organizational type
- Data collection sample
- 54 public research universities
- 49 private research universities
- 42 selective private liberal arts
- Data collection period
- 1/1/2017 to 12/31/2017
- Ongoing data collection with larger sample
Focus of this research paper
Research question: what are the similarities and differences in off-campus recruiting patterns across public research universities?
- Quantitative multiple case study of 15 public research universities
Why this research question:
- First paper from the larger study
- Explore behavior inductively, rather than test specific hypotheses
- Subsequent papers more focused, thematic (e.g., racial red-lining, international recruiting)
Why focus on public research universities:
- Historic mission of social mobility for state residents
- Decline in state funding, growth in nonresident enrollment (Jaquette and Curs, 2015)
- What are they doing to get all these nonresidents? More effort recruiting nonresidents than residents?
"Off-campus recruiting events" defined as off-campus events hosted by paid staff/consultants focused on soliciting applications
- Event type
- Include: college fairs, high school visits, community college visits,
- Exclude: admitted or committed student events, interviews
- Event host
- Include: paid admissions staff or consultants (e.g. regional recruiters)
- Exclude: alumni, student volunteers
- Event location
- Any off-campus location
- e.g., high school, community college, hotel, convention center, cafe, etc.
Data collection, data processing, data quality
- University website checked four times per year by two staff for URLs with recruiting events
- Web-scraping scripts run once per week
- "Parsing": transform HTML text into tabular data
- "Geocoding": use Google Maps API to obtain detailed location data based on limited data
- Merge recruiting data to secondary data (e.g., schools, communities)
Data quality (are these data any good?)
- Concern 1: are scraped events properly classified and merged to secondary data?
- Solution: manually check each scraped event
- 8 of 15 universities checked thus far
- Concern 2: are all events posted on admissions website?
- Solution: issue public records requests for all off-campus recruiting events
- Received data from 7 of 15 universities; not yet incorporated
Secondary data Sources:
- NCES Common Core of Data (public high schools)
- NCES Private School University Survey (private high schools)
- U.S. Census American Community Survey (community characteristics)
- IPEDS (community colleges)
- EdFacts Initiative (public high school academic achievement)
- Equality of Opportunity Project (university income
Research design for analyses
Quantitative multiple case study design
- "Quantitative case study" uses quantitative data as sole source of evidence (Korzilius, 2010)
- "Within-case" analyses of recruiting patterns
- Situate within local context; national overview; "deep dive" of in-state and out-of-state patterns
- Simple descriptive statistics (e.g., counts), static visualizations, interactive maps
- "Cross-case" analyses
- Descriptive statistics and qualitative coding methods
Comparison to alternative research designs
- Large-N, random sample design
- Not possible because recruiting data unavailable for random sample
- Not desirable for present research because large-N designs pool results across cases
- Qualitative case study (usually collect data from multiple sources)
- Our design is narrowly focused, systematic analysis of particular phenomena
- Unlike Stevens (2007), we do not develop a holistic understanding of recruiting behavior
Analysis sample consists of 15 public research universities
- Chosen from larger data collection sample (N=54) based on "completeness" of recruiting event data
- Subsequent drafts may reduce sample size based on principles of purposeful sampling (Patton, 2002)
Click on a university to take a closer look at the results
N refers to total number of off-campus recruiting visits
Summary of results and next steps for this paper
Summary of results
- Majority of universities in our sample hosted twice as many out-of-state events as in-state events
- Out-of-state events focus on affluent public schools and private schools
- Several universities focus more on in-state recruiting (e.g., U. Nebraska, North Carolina State)
- In-state visits tend to show little evidence of income or racial bias
- Some universities (e.g., Rutgers) show income/racial bias even in in-state visits
- Must investigate whether bias persists after controlling for academic achievement, etc.
- Complete data quality checks (e.g., incorporate data from public records requests)
- Conduct "deep dive" for all universities
- Compare results across universities
- Quantitative descriptive analyses; qualitative coding
- Develop broad categories of recruiting "types" and categorize universities
Using "data science" and public records requests to study recruiting
Off-campus recruiting project
- Expand data collection (e.g., regional public universities); publicly release all data
- Develop manuscripts with more narrow focus (e.g., nexus between state/local politics and visits)
Student list project (collected pilot data)
- Which student characteristics do universities prioritize when purchasing prospect lists from College Board/ACT?
- Data collection: Public records requests
Experimental audits of university responses to "inquiries" (pre-pilot stage)
- More favorable response to inquiries with certain characteristics (e.g., affluence of zip-code/school, evidence of third-party grant/loan)?
- Data collection: Automate emails; auto-fill "inquiry forms"
- Change national policy discourse on access inequality
- Empower local actors to hold universities accountable for access commitments (example HERE)
- Unless we document enrollment management behavior, we invite symbolic responses
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