Presentation on theme: "Kansas Math and Science Teacher Mobility, 2006-2012 KU Center for STEM Learning Steven Obenhaus"— Presentation transcript:
Kansas Math and Science Teacher Mobility, 2006-2012 KU Center for STEM Learning Steven Obenhaus email@example.com
“The challenge to our schools is not just a looming teacher shortage, but rather a shortage of great teachers in the schools and communities where they are needed most” -- Education Secretary Arne Duncan, 2009
Kansas Numbers for 2012-2013 480,149 total student enrollment 209,209 secondary students 286 school districts Total math teachers: 3028 Total science teachers: 2878 Math teachers per district: mean—10.6, mode—3, median—4, max—306 Science teachers per district: mean—10.1, mode—3, median—4, max—206
Teacher Workforce is Aging Nationwide — »In 1976 the average teacher was 36 years old. »In 2008 the average age was 42. »Teachers age 50 years or older increased from 530,000 in 1988 to 1.3 million in 2008. »Modal age for retirement: 59 years. Why is this important? »When high-quality teachers leave the classroom there is a deleterious effect on student performance and the cost to schools and districts to replace the teachers is significant. (Watlington, et.al., 2009) Source: original analyses of the Schools and Staffing Survey by Richard Ingersoll and Lisa Merrill
1988 Age Distribution Source: original analyses of the Schools and Staffing Survey by Richard Ingersoll and Lisa Merrill
2008 Age Distribution Source: original analyses of the Schools and Staffing Survey by Richard Ingersoll and Lisa Merrill
Kansas Teacher Demographics 2009-2010 school year Math »Age Range: 22-71 »1 st quartile: 32, median: 42, 3 rd quartile: 52 Science »Age Range: 21-75 »1 st quartile: 34, median: 43, 3 rd quartile: 53
The surge of teacher retirements has prompted some researchers to estimate a need to hire between 2.9 and 5.1 million full-time teachers between 2008 and 2020 (Aaronson & Meckel, 2008). This echoes earlier calls for recruitment, such as Secretary Richard Riley’s appeal in 1994 for 2 million new teachers. In response to his challenge, the U.S. hired approximately 2.25 million teachers over the next decade. Between 1995 and 2005, schools and districts lost 2.7 million teachers due to steadily increasing attrition among beginning teachers and normal retirements. (Carroll, 2007) Now we are facing an unprecedented wave of retirements, on top of beginning teacher attrition that has grown worse over the past 15 years. There is no way that current recruiting strategies – even in hyper drive – can meet this challenge. Carroll & Foster, 2010
While young teachers and the fresh ideas they can bring are essential to improve teaching effectiveness, experience always matters in teaching. Research clearly shows that with each year of experience, teachers improve their proficiency and effectiveness during the first seven years.” -- Carroll & Foster, Who Will Teach? Experience Matters, 2010
Retirement Eligibility Data Eligible to retire in 2012 »Math: 8.6% »Science: 11.4% »Both: 8.1% Eligible to retire by 2017 »Math: 18.7% »Science: 23.0% »Both: 18.3%
Of all those who were teaching anytime from 2006 to 2012 each fell into one of six categories. Leaver – taught prior to 2012 but not in 2012. Mover – changed school districts without a year or more break. Returner – took a year or more off then returned to same district. Returner_mover – took a year or more break and returned to a different district. Starter – 2012 was the teacher’s first year teaching (some may have taught prior to 2006 and would be categorized as returners if we had the data) Stayer – taught prior to 2012 and taught continuously for at least two years in same district through 2012.
All teachers by status in 2012 Status in 2012 CountPercent Average points Median points leaver300232.9360.256 mover5185.6850.453 returner4084.4860.964 returner/ mover 1842.0253.469.5 starter139715.3249.669 stayer360839.5761.448 9117100
The 12 urban-centric locale code categories 11 = City, Large: population of 250,000 or more. 12 = City, Midsize: population less than 250,000 and greater than or equal to 100,000. 13 = City, Small: population less than 100,000. 21 = Suburb, Large: territory outside a principal city and inside an urbanized area with population of 250,000 or more. 22 = Suburb, Midsize: Territory outside a principal city and inside an urbanized area with population less than 250,000 and greater than or equal to 100,000. 23 = Suburb, Small: Territory outside a principal city and inside an urbanized area with population less than 100,000. 31 = Town, Fringe: less than 10 miles from an urbanized area. 32 = Town, Distant: less than 35 miles from an urbanized area. 33 = Town, Remote: more than 35 miles from an urbanized area. 41 = Rural, Fringe: less than or equal to 5 miles from an urbanized area. 42 = Rural, Distant: less than 25 miles from an urbanized area. 43 = Rural, Remote: more than 25 miles from an urbanized area.
7 city, 9 suburban, 65 town, 209 rural districts
Research on STEM teacher turnover “The schools do seem to lose more experienced teachers and teachers with high-demand science and math degrees” “a science or math undergraduate degree was associated with odds of attrition approximately twice those for teachers with other undergraduate degrees.” “Harrington (2001) blames specific shortages of math and science teachers on a dysfunctional labor market held hostage by poor allocation of resources, disincentives to productivity, and, ironically, inequity. Equal pay for all teachers, he argues, distorts the market for teachers in these technical subject areas.” Teacher Attrition and Retention: A Meta-Analytic and Narrative Review of the Research, Geoffrey D. Borman and N. Maritza Dowling, Review of Educational Research, Vol. 78, No. 3 (Sep., 2008), pp. 367-409.
NY State New York state study Understanding Rural Teacher Retention, Luke Miller, http://curry.virginia.edu/research/centers/cepwc/publications http://curry.virginia.edu/research/centers/cepwc/publications
NC study “Finally, teachers who majored in mathematics and science, and especially secondary teachers, are more likely to attrite. Scholars hypothesize that the high exit rates of these teachers are due to the increased alternative opportunities available to people with math and science knowledge and skills.” Kukla-Acevedo, S. (2009). Leavers, Movers, and Stayers: The Role of Workplace Conditions in Teacher Mobility Decisions. Journal of Educational Research, 102(6), 443-452.
Central US study “In this sample of schools successful in recruiting, all of the vacancies were filled, although three principals reported that mathematics and science vacancies were the most difficult to fill.” Beesley, A., Atwill, K., Blair, P., & Barley, Z. (2008). Strategies for recruitment and retention of secondary teachers in Central Region schools. Denver, CO: Mid-continent Research for Education and Learning.
Rural studies “Schools in rural areas and small towns are more likely to deal with vacancies by cancelling planned course offerings and assigning an administrator or counselor to teach those classes (NCES, 2006). This solution to rural teacher shortages presents dire consequences for rural science, technology, engineering, and mathematics (STEM) instruction in particular. Due to teacher shortages, teachers specializing in other fields are sometimes required to teach STEM courses even if they are underprepared and uncomfortable with teaching these subjects. Ultimately, student science achievement suffers when there is a STEM teacher shortage and when the available teachers are underqualified for the subjects they teach.” Goodpaster, K. P. S., Adedokun, O. A., & Weaver, G. C. (2012). Teachers' Perceptions of Rural STEM Teaching: Implications for Rural Teacher Retention. Rural Educator, 33(3), 9-22.
Rural studies “The areas of certification that districts reported as being the most difficult to fill were Math, Science, and Special Education. Over 50% of responding districts reported math as being particularly difficult to fill Over 50 % reported science as being difficult to fill Approximately 43% reported special education as being particularly difficult to fill” “Rural Teacher Retention Study” National Research Center on Rural Education Support policy brief
Lit Review “Below, we summarize the findings that have emerged in the research literature. Teachers in the fields of science and mathematics were more likely to leave teaching than teachers in other fields. Science and math teachers were less likely to return than other teachers, whereas elementary teachers and teachers with more prior experience were more likely to return.” Teacher Recruitment and Retention: A Review of the Recent Empirical Literature. Cassandra M. Guarino, Lucrecia Santibañez and Glenn A. Daley. Review of Educational Research, Vol. 76, No. 2 (Summer, 2006), pp. 173-208.
Disproportionate Effects “The net result is a large annual asymmetric reshuffling within the school system of a significant portion (about 25,000 math/science migrants in 2004–2005) of the math/science teaching force, with a net loss on the part of poor, minority, and urban schools and a net gain to nonpoor, nonminority, and suburban schools.” Ingersoll & May, The Magnitude, Destinations, and Determinants of Mathematics and Science Teacher Turnover. Educational Evaluation and Policy Analysis, December 2012, Vol. 34, No. 4, pp. 435–464.
Disproportionate Effects “For example, in the shortage areas of science and math, we found that there was more tolerance and leeway among school administrators regarding quality of practice, including allowing weaker teachers to stay on or switch into high-need subject areas despite weak practice and lack of content knowledge. This study also reveals, however, that the recruitment problem in science and other shortage areas was also a retention problem because strong teachers in high- need subject areas could more easily move from one school to another, having the luxury of searching for a culture that was a good fit.” Cochran-Smith, M., McQuillan, P., Mitchell, K., Terrell, D. G., Barnatt, J., D’Souza, L.,... Gleeson, A. M. (2012). A Longitudinal Study of Teaching Practice and Early Career Decisions: A Cautionary Tale. American Educational Research Journal, 49(5), 844-880.
Cost per Leaver Granville County Schools – over $9,000. Milwaukee Public Schools – over$8,000. Chicago Public Schools –over $8,000 in professional development resources alone. District-level cost per leaver was $13,650. When school costs were added to the district-level costs, the Chicago Public Schools cost of teacher turnover was estimated to be between $76 and $128 million per year.” Policy Brief --The High Cost of Teacher Turnover, National Commission on Teaching & America's Future (NCTAF)
Cost per Leaver In Milwaukee low-performing schools have double the teacher turnover of high performing schools. With an average school faculty of 55 and an average school cost of $8,300 per leaver, a typical low-performing school in MPS spends $67,000 more to deal with the consequences of teacher turnover every year. If saved, this sum would allow the same school to provide additional support for new teachers or pay the salary of a reading specialist. These costs do not include what may in fact be the largest cost of teacher turnover: lost teaching quality and effectiveness. Policy Brief --The High Cost of Teacher Turnover, National Commission on Teaching & America's Future (NCTAF)