Cdpi keynote
- 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
- 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
- 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
- 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/