1. What Placement Means,
How to Claim it with Integrity,
and Build Metrics to
Support Your Work
September 13, 2013
Valparasio, Indiana
Linda Gross, Ph.D
© 2013

2. A little self assessment
1. Data
a.
b.
c.
d.
Downer
Dread
Distress
Delight
2. Placement
a.
b.
c.
d.
Panic
Phobia
Paranoia
Pleasure
3. Statistics
a.
b.
c.
d.
Stress
Suffering
Sweat
Sensational
4. Annual Report
a.
b.
c.
d.
Angst
Anxiety
Apprehension
Amusement

3. An Ostrich Lesson

4. Contexts & Challenges

5. Complaints about college ROI rise
as a YouTube genre

6. What is driving the
placement data obsession?
• Return on investment (ROI) concerns
– How can we measure the value of a college education?
• Economic pressures
–
–
–
–
Rapid tuition and fee inflation
Erosion of public funding for state institutions
Rising institutional costs (health care)
Market competitiveness
• Increased need for public accountability
–
–
–
–
Student debt load and loan default
Completion rates
Gainful employment
High profile scandals both public, private and for profit

7. Are college graduates more likely to be
unemployed?
New York Times, May 3, 2013

8. Is placement data Voodoo Science?
What may begin as an
honest error, however, has a
way of evolving through
almost imperceptible steps
from self-delusion to fraud.
The line between foolishness
and fraud is thin. Because it
is not always easy to tell
when that line is crossed, I
use the term voodoo
science to cover them all…
(Page 10)

9. The Problems with “Placement”
• Antiquated Terminology
• Methodology
– Contrived formulas designed to yield the highest placement
rate
– No consistency between institutions
– Even the NCES has been reluctant to define a universal
methodology
• Fraud
– Career Education Corporation $10.3 million fraud settlement
for inflating job placement data
– ATI Enterprises (a career training company) will pay the federal
government $3.7 million to resolve compliance issues with
federal aid and job placement data

10. Toward a Better Paradigm

11. The Power of Transparency
• Methodology
• Clear definition of the
survey population
• Response rates
• Practicality
– data mining and ethical
judgment
• Timing
• Clear definition of terms
– What is placed?
– What is unplaced?
– What about those we can’t
resolve

12. A Case Example
Michigan State University
Destination Survey

13. Owning our knowledge
What goes into a student’s
post-graduation destination?

14. What counts with employers?
Internships
Leadership in
a professional
organization
Study
Abroad
Supervised
civic
engagement
Leadership in a
nonprofessional
organization
Scholarly
research
with
faculty
Internationa
Internship
Faculty
supervised
applied
research
project with
company
Gardner, P. (2011) Recruiting Trends, Collegiate Employment Research Institute, Michigan State University

15. Student Activities
Academics
Internships
Service
Work
Family
Study Abroad
Daily
living
stuff
Finances
Social life

16. Reflective Learning Model
• Academic courses
• Internships, co-ops,
practica, service
• Leadership experiences
• Study abroad
• Life events &
relationships
LEARNING
CATALYSTS
REFLECTION
• Self awareness
• Skill identification
• Critical thinking
• Decision-making
• Learning
• Articulating growth &
skill development
• Boundary spanning
problem solving
• Ability to contribute
• Transition awareness
INTEGRATION
Gross, L. (2000) Michigan State University

17. We are stewards of student experiences

18. Passionate people take risks.
Spanning boundaries with purpose and integrity

19. We have unique assets to integrate,
innovate and advance higher education
• Insight into what
students find meaningful
• Working knowledge of
employer expectations
for new graduates
• Ability to identify gaps in
student preparation for
their destination upon
graduation

20. Harnessing the Power of Big Data

21. What kind of data are you sitting on?
• Student usage of career
services
–
–
–
–
–
–
Counseling
Workshops
Career fair attendance
Interviews
Information sessions
Job applications
• Student employment data
–
–
–
–
–
Hours worked
Level of responsibility
Pay rates
Work study
Internships
• Student destination data

22. Practical Accountability – Real Time
College or
Department
Arts
Business
Education
Engineering
Health
Sciences
Social
Sciences
Career
Counseling
Career
Assessment
Workshops
Career Fairs
Job Listings
Job
Applications
Interviews

23. What data do you have/need access to?
• Institutional student
information systems
–
–
–
–
–
Student demographics
Academic data
Retention data
Financial need
Academic internship
courses
– Civic engagement
participation
– Study abroad
participation
– Undergraduate research

24. A Model for Multidimensional Measures
Student Interactions
Counseling, Workshops, Career
Fairs, Interviews, Career
Assessments
Student Experiences
Student Employment,
Leadership, Civic Engagement,
Research, Internships, Co-ops,
Study Abroad
Aggregate
Student Data Warehouse
Multidimensional Measures
for College Outcomes
Student Learning Outcomes
Curricular , Co-Curricular and
support services
Student Destination Data
Follow up Alumni Data
Student Academic and
Demographic Data
(Institutional Student
Information Systems)
© Gross, L. (2013)

25. ADVOCATE!
Colleges and universities MUST be
more explicit about co-curricular
learning expectations

26. The Ostrich Revisited

27. Discussion
Linda Gross, Ph.D.
Career Services Network
Michigan State University
GrossL@msu.edu

28. Resources
• MSU Destination Survey online:
– http://careernetwork.msu.edu/exploringoptions/destination-survey.html
– Includes latest full report as .pdf and links to sections of
the report including methodology, survey pool, timing,
and terms definitions.
• MSU Collegiate Employment Research Institute
– http://www.ceri.msu.edu/
– Publications include the “high states internship” and
“unpacking” http://www.ceri.msu.edu/ceri-publications/