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Preliminary Analyses of a Nationwide STEM Teacher Recruitment & Retention Program Marjorie Bullitt Bequette Frances Lawrenz Deena Wassenburg Jim Appleton.

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Presentation on theme: "Preliminary Analyses of a Nationwide STEM Teacher Recruitment & Retention Program Marjorie Bullitt Bequette Frances Lawrenz Deena Wassenburg Jim Appleton."— Presentation transcript:

1 Preliminary Analyses of a Nationwide STEM Teacher Recruitment & Retention Program Marjorie Bullitt Bequette Frances Lawrenz Deena Wassenburg Jim Appleton Pey-yan Liou Catherine Wanjugi University of Minnesota

2 Preliminary Analyses of a Nationwide STEM Teacher Recruitment & Retention Program Marjorie Bullitt Bequette Frances Lawrenz Deena Wassenburg Jim Appleton Pey-yan Liou Catherine Wanjugi University of Minnesota

3 Noyce program overview Research shows persistent correlations between student performance and teacher quality in science and mathematics (Sanders and Rivers, 1996; Jordan, Mendro, and Weerasinghe, 1997; Goldhaber and Brewer, 1996; National Research Council, 2000). Recent studies (Ingersoll 1999; Ingersoll, 2002) show that 56% of secondary students in physical science are being taught by teachers without a major or minor in physical science, and that students in high-poverty schools are 77% more likely to be taught by an out-of-field teacher. The Robert Noyce Scholarship Program is an NSF program, designed to “encourage talented science, technology, engineering, and mathematics majors and professionals to become K-12 mathematics and science teachers” by providing stipends and scholarships to qualified individuals who are training to become teachers (p. 1, NSF solicitation).

4 Methodology Data sources: Monitoring data collected for NSF Online descriptions of teacher education programs. Review of data by two thirds of PIs Analyses: Analyses were generally descriptive: frequencies, percentages, and cross tabs. Some data were combined into new categories on basis of team review.

5 Results: Noyce projects Noyce funds have been provided to 75 programs at 74 sites across the country.

6 Program features

7 Types of certification This chart must be interpreted carefully every state defines alternative and traditional certification differently what counts as alternative in one state may be more similar to a traditional path to certification in another state numbers show how projects fit into their state’s arrangements for teacher education

8 Who is being recruited?

9 What settings are teachers being prepared for?

10 Results: Noyce scholars Information on 618 Noyce scholars was analyzed.

11 Gender: more male teachers than in the larger population Noyce numbers Noyce %All public school teachers % Male23338%25% Female38562%75%

12 Noyce numbers Noyce %All public school teachers % White, non-Hispanic or not reported* Black, non-Hispanic or not reported American Indian or Alaskan Native, non- Hispanic or not reported Asian, non-Hispanic or not reported Native Hawaiian or other Pacific Islander, non-Hispanic or not reported 10.2 Hispanic, single or multiple races Multiple Races, non-Hispanic or not reported 40.7 Unidentified/insufficient data 172.8N/A *The Noyce survey asked about race (first five options in the chart) and ethnicity (Hispanic) in separate questions, making a comparison with numbers from NCES challenging. In this table, individuals who selected a race but not an ethnicity (e.g., race=white, ethnicity=not reported) are included in the race they selected. Of this group, 57 reported their race to be white, 12 black, 5 Asian, 1 multiple races. Individuals who reported their ethnicity but not their race are included in the Hispanic category. (Numbers are from nces.ed.gov, Characteristics of Schools, Districts, Teachers, Principals, and School Libraries in the United States Schools and Staffing Survey.)nces.ed.gov Race/ethnicity: fewer white teachers than in the larger population

13 Noyce recipients are mostly younger adults, though there are some more mature individuals. The mean year of births is 1974, the median is 1978, and the mode is There is a 40-year spread of birth years, from 1945 to The bar chart below shows the distribution of birth years. Note that the scale changes in Age: mostly young; 40-year spread

14 Results: scholarship and stipend recipients Scholarships are intended for undergraduates majoring in a STEM discipline (58% of total); they can receive up to two years of funding. Stipends are intended for STEM professionals with an undergraduate and/or graduate degree in a STEM discipline(42% of total); they can receive one year of support for a teacher certification program. Both scholarship and stipend recipients commit to teaching for two years in a high needs school district for every year of support they receive.

15 Differences between scholarship recipients, stipend recipients who have worked, and stipend recipients who have never worked These groups differ in their age, gender balance, race/ethnicity, and previous experience. Stipend recipients were further subdivided to separate those who had worked from those who had not because there were significant differences in some areas between these groups.

16 Gender: no significant differences More stipend recipients are male than scholarship recipients, though the differences are not significant according to Chi square tests. There is no significant difference between the gender balance for stipend recipients who worked previously and those who did not. GroupMale %Female % All Noyce recipients (N=618) 3862 Scholarship recipients (N=359) 3664 All stipend recipients (N=259) 4159 Stipend recipients who have not worked (N=86) 4258 Stipend recipients who worked previously (N=173) 4060

17 Age: stipend recipients who have worked are significantly older than all others While stipend recipients are generally older than scholarship recipients, the most important interaction is with previous work experience. Scholarship recipients and stipend recipients who did not work before beginning their teacher education program both have a mean birth year of 1977, while stipend recipients who worked previously (N=173) have an average age that is 10 years older. GroupMean Birth year/SD Current mean age All Noyce recipients 1974/9.733 Scholarship recipients 1977/8.230 All stipend recipients 1970/ Stipend recipients who have not worked 1977/5.030 Stipend recipients who worked previously 1967/10.240

18 Race/ethnicity: scholarship and stipend recipients; those who worked and those who did not work all differ Noyce % (N=618) Scholarship recipient % (N=359) Stipend recipient % (N=259) Stipend who have not worked % (N=86) Stipend who have worked % (N=173) White, non-Hispanic or not reported* Black, non-Hispanic or not reported American Indian or Alaskan Native, non-Hispanic or not reported Asian, non-Hispanic or not reported Native Hawaiian or other Pacific Islander, non- Hispanic or not reported Hispanic, single or multiple races Multiple Races, non- Hispanic or not reported Unidentified/insufficient data *Groups were created as for the other race/ethnicity table. Only white, black, Asian and Hispanic groups were analyzed for significance.

19 Education: those who worked previously also have earned higher degrees Given their young age, we wondered whether the “have not worked” group were mostly recent graduates, or if some also had graduate degrees. As the table shows, people who worked previously tend to have earned a higher degree than those who have not worked. DegreeFrequencyStipend recipient % Stipend/have not worked % Stipend/have worked % Bachelor’s Master’s Doctorate Other* *In the “other” group, two individuals have law degrees, and two have completed some but not all of their doctorates.

20 General area of previous occupation Mean length of occupation = 8.7 years

21 The list of previous occupations includes diverse job titles. Here are just a few, chosen to give a sense of the range: Research Scientist/Pharmaceutical TestingScience Geologist/USGSScience Graphic Artist/ Computer SpecialistTechnology Senior nuclear engineer Engineering Math Analyst for Engineering CompanyMathematics Non-certified science teacherK-12 Education Museum Educator & Youth Radio DirectorInformal Education Upward Bound Youth LeaderInformal Education College ProfessorHigher Education Social Services, Substance Abuse TreatmentSocial Services Financial AnalystBusiness Pension AnalystBusiness Bank tellerBusiness Fisherman and masonry businessBusiness ArchitectOther Landscape gardenerOther

22 Only half of career changers come from STEM professions

23 Program departure In the “other” category, reasons indicated that the individual in question decided that teaching was not a good career choice, given the demands of the profession. ReasonFrequency% of all departures% in the whole population Left to pursue other academic interests 59.4%0.8% Failed to meet program requirements %3.2% Left to pursue employment 35.7%0.5% Left due to family and/or economic constraints 917.0%1.5% Other 35.7%0.5% Unknown %2.1% Total 53100%8.6%

24 Prepared to teach but not teaching ReasonFrequencyPercent of those not teaching Percent in the whole population Has not yet completed requirements for a teaching credential 640.0%1.0% Chose a different career path 320.0%0.5% Unable to find a job in preferred area 16.7%0.2% Family/personal constraints 213.3%0.3% Unknown320.0%0.5% Total15100%2.4%

25 Conclusions The Noyce program supplies funds to a diverse set of institutions across the country, Institutions work in different ways to prepare STEM teachers for diverse settings. Noyce teachers less likely to be female and white than the average teacher. The Noyce program is designed to attract two groups: –well-trained undergraduates (scholarship recipients) –STEM professional career changers (stipend recipients) There are insignificant differences in gender balance and significant differences in racial/ethnic make-up of these two groups.

26 The racial and ethnic make-up differences may reflect the existence of programs that make outreach efforts to particular communities, or they may reflect more significant differences about career paths of different racial and ethnic groups. A third of the stipend recipients, those who have never worked, look more like the scholarship recipients than they look like their fellow stipend recipients in terms of their age and their previous educational experience. Of the true career changers, stipend recipients who worked, just over half come directly from STEM professions, while the other half come from business, education, or other fields.

27 Thus, characterizing all stipend recipients as “STEM career changers” is not representative of their true experience; only about a third of stipend recipients fit into that category. In further analyses, we suggest dividing stipend recipients into two groups, to reflect the distinct difference in age and educational history between those who have worked and those who have not worked. Our future analyses will explore whether the area of previous experience has any effect on their experience and success as well.


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