Preparing Students for the Workforce: A Data Wishlist


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From the Penn IUR and Penn GSE sponsored conference:

“Preparing Today’s Students for Tomorrow’s Jobs in Metropolitan America: The Policy, Practice and Research Issues"

May 25-26, 2011

Organized by Laura Perna, a professor in Penn GSE, and Susan Wachter, a professor in Penn’s Wharton School, “Preparing Today’s Students for Tomorrow’s Jobs” explores the most effective institutional and public-policy strategies to be sure high school and college students and adult learners have the knowledge and skills required for future employment.

“The conference addresses such critical questions as: How do we define success with regard to the role of education in preparing students for work?” Perna said. “How well are different educational providers preparing future workers? What is the role of public policy in improving connections between education and work?

“It seeks to improve our understanding of several fundamental dimensions of this issue through insights from federal, state and local policy leaders, college administrators and researchers.”

Guest speakers include Eduardo Ochoa, assistant secretary of the U.S. Department of Education; former Pennsylvania Gov. Edward Rendell; Lori Shorr, chief education officer to Philadelphia Mayor Michael Nutter; Charles Kolb from the Committee for Economic Development in Washington, D.C.; Claudia Neuhauser from the University of Minnesota; Bethany Krom from the Mayo Clinic; and Harry Holzer from Georgetown University.

“Much recent attention focuses on the need to improve high school graduation and college degree completion. But, relatively less attention has focused on whether graduates and degree recipients have the skills and education required by employers,” Perna said.

The event is sponsored by the Penn’s Pre-Doctoral Training Program in Interdisciplinary Methods for Field-Based Research in Education, with funding from the U.S. Department of Education’s Institute for Education Sciences in collaboration with Penn’s Institute for Urban Research.

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Preparing Students for the Workforce: A Data Wishlist

  1. 1. Preparing Students for the Workforce:A Data Wish List<br />Katherine M. Barghaus<br />Eric T. Bradlow<br />Jennifer McMaken<br />Samuel H. Rikoon<br />
  2. 2. A Talk Full of Dreams<br />Federal Funded and Nationally Coordinated<br />Student Preparedness and <br />Measurement Program <br />State-level/Local Municipality<br />Assessment with Little <br />National Coordination<br />Dream<br />Reality<br />Is this the solution?<br />
  3. 3. What Are We Trying to Optimize?<br />20% Students are Very Ready<br />70% Students have Basic Preparation<br />10% Students are Unprepared<br />5% Students are Very Ready<br />95% Students have Basic Preparation<br />0% Students are Unprepared<br />Which of these two scenarios is “societally optimal”?<br />
  4. 4. What is Meant by Preparedness?<br />A<br />B<br />
  5. 5. What Does the Literature Say?<br /><ul><li>Bennett, Dunne and Carré (1999) develop a model of generic skills and classificatory framework of pedagogical approaches for generic skill acquisition.
  6. 6. Generic skills are defined as skills that can support study in any discipline and that may transfer to many contexts and are modeled as 4 broad management skills of one’s self, others, information, and task.
  7. 7. Framework of pedagogical approaches includes: disciplinary content knowledge, disciplinary skills, workplace awareness, workplace experience, and generic skills. </li></li></ul><li>What Does the Literature Say?<br /><ul><li>The Business Higher Education Round Table (2002) defines generic skills as a range of abilities, attitudes, and values important in higher education and the workplace.
  8. 8. Discusses reasons for the growing interest in this topic including,
  9. 9. increasing demand for graduates with such skills, and
  10. 10. economic and technological shifts that make skills necessary.
  11. 11. Provides examples of how colleges in Australia are including generic skills in education by developing statements of graduate attributes.</li></li></ul><li>But, How Do We Get There?<br /><ul><li>Hoachlander (2008) provides a summary of theoretical and empirical motivations for using “multiple pathways” curricula.
  12. 12. Multiple pathways refers to a strategy where students simultaneously enroll in traditional academic coursework along with one or more electives concentrated on the acquisition of career/technical skills.
  13. 13. Based on a review of the literature, found that multiple pathways may:
  14. 14. enable students to connect material learned to the working world
  15. 15. lead to a wider range of possible postsecondary opportunities
  16. 16. lead to higher wages
  17. 17. have a positive impact on academic achievement. </li></li></ul><li>But, Does It Work?<br /><ul><li>Orozco (2010) compares high school students exposed to Pathway Educational (PE) methods with students receiving a traditional education on academic achievement, development of technical skills, and school engagement.
  18. 18. PE methods provide traditional academic coursework along with electives focused on the acquisition of career or technical skills.
  19. 19. Administrative and survey data on approximately 4,000 students was collected. ANCOVA was used to compare mean group outcomes controlling for ethnicity, socio-economic status, gender, and campus.
  20. 20. Students exposed to PE methods had higher achievement, were more engaged in school, and reported having more technical skills.</li></li></ul><li>Data Wish List<br /><ul><li>Generating and collecting readiness data
  21. 21. Randomized field trials as a gold standard
  22. 22. Often impossible given logistic, financial limitations
  23. 23. Rigorous observational studies as next best method
  24. 24. Statewide longitudinal data systems (SLDS) already in development across majority of U.S.
  25. 25. 42 States funded via IES grants
  26. 26. Multifaceted quality controls already in place
  27. 27. Should be augmented to include more workforce readiness / transition to work data</li></li></ul><li>Data Wish List<br />Applying SLDS to Workforce Readiness Research<br />Develop typologies/profiles by career pathway<br />Matched comparisons of curricular interventions<br />Longitudinal studies of readiness skill stability<br />Ability to generalize to statewide population<br />Potentially nationwide also w/ proper alignment of SLDS<br />Generate algorithms warning schools/counselors of negative indicators in near-real time<br />
  28. 28. Summary<br /><ul><li>Field lacks consensus on defining readiness
  29. 29. As a result, there is little to no framing on how to measure readiness
  30. 30. Review of the literature has raised set of questions to be addressed in order for field to progress in this area</li></li></ul><li>Directions for the Field<br /><ul><li>Data driven—draw upon existing data sources to help distill patterns and generate measurement frameworks
  31. 31. Iterative—like all good science, this will be a process of testing, evaluating and rejecting/revising measures
  32. 32. Increased scope—opportunity to shift readiness as solely an outcome to a variable that can be examined in relation to other life course outcomes</li></ul>Post Pre-K-12 Education<br />Income<br />Happiness<br />Societal Outcomes<br />
  33. 33. Thank You<br />Sam<br />Jen<br />Katie<br />