T-STEM academies’ academic performance examination by education service centers: A longitudinal study

Abstract

The purpose of the study is to examine the performance of Texas-STEM (T-STEM) academies in different regions to determine whether the academic achievement differs according to Education Service Centers (ESC). The ESCs’ goals were to improve the quality of school district programs and to increase student achievement. It was found that there was no statistically significant difference among T-STEM academies’ students’ mathematics mean scores in different ESCs when demographic variables taken into account. African American students’ mathematics mean scores were statistically significantly lower than those of White students in 9th grade; however, Asian students’ growth rate was statistically significantly higher than White students’ growth rate. Male students’ growth rate was statistically significantly higher than female students’ growth rate.

Keywords

• T-STEM Academies, Education Service Centers, Ethnicity, Gender

Teksas-FeTeMM okullarının akademik performanslarının ilişkili oldukları eğitim servis merkezlerine göre İncelemesi: Boylamsal bir çalışma

Öz

Bu çalışmanın amacı farklı bölgelerdeki Teksas-FeTeMM (T-FeTeMM) akademilerinde eğitim gören öğrencilerin akademik performanslarının bulundukları bölgedeki Eğitim Servis Merkezlerine (ESM) göre incelemektir. ESM’lerinin hedefleri okulların kalitesini ve bu okullarda eğitim gören öğrencilerin başarısını arttırmaktır. Bu çalışmada, ESM’lerin bulundukları bölgelere göre öğrenci başarılarında farklılık olup olmadığını belirlemek amacıyla T-FeTeMM öğrencilerinin üç yıllık performansları incelenmektedir. Farklı bölgelerde bulunan ESM’lerde yer alan T-FeTeMM akademisi öğrencilerinin matematik skorları arasında demografik değişkenler göz önüne alındığında anlamlı farklılık bulunmamıştır. Dokuzuncu sınıfta Afrika kökenli Amerikalı öğrencilerin skorlarının aritmetik ortalaması Beyaz Amerikalı öğrencilerinkinden istatistiksel olarak daha düşük bulunmuştur. Asya kökenli öğrencilerin matematik gelişim oranları ise Beyaz Amerikalı öğrencilerinkinden daha yüksek bulunmuştur. Erkek öğrencilerin matematik gelişim oranı kızlarınkinden daha yüksek bulunmuştur.

Anahtar Kelimeler

• Teksas-FeTeMM Okulları, Eğitim Servis Merkezleri, Etnik köken, Cinsiyet

References

1. Ausburn, J. P. (2010). Professional services provided by Texas Education Service Centers to promote improvement in Texas public schoolsuA descriptive study. (Doctoral dissertation) Available from ProQuest Dissertations and Theses database (UMI No. 3436761).
2. Avery, S., Chambliss, D., Pruiett, R., & Stotts, J. L. (2010). Texas science, technology, engineering, and mathematics academies design blueprint, rubric and glossary. Report of Texas High School Project T- STEM Initiative. Retrieved September 15, 2013, from http://Www.edtx.org/uploads/general/pdf— downloads/misc-PDFs/201 1_TSTEMDesignBlueprint.pdf
3. Bicer, A., Navruz, B., Capraro, R. M., & Capraro, M. M. (2014). STEM schools vs. non-STEM schools: Comparing students’ mathematics state based test performance. International Journal of Global Education, 3(3), 8-18.
4. Blackwell, B. (1995). The role of regional education service centers in improving the quality and content of primary and secondary education in Texas. (Doctoral dissertation) Available from ProQuest Dissertations and Theses database (UMI No. 9539143).
5. Corlu, M. S. (2014). FeTeMM eğitimi makale çağrı mektubu. Turkish Journal of Education, 3(l), 4-10.
6. Corlu, M. S., Capraro, R. M., & Capraro, M. M. (2014). Introducing STEM education: Implications for educating our teachers in the age of innovation. Education and Science, 3 9(171), 74-85.
7. Educate Texas. (2013). T—STEM academy design blueprint. Retrieved September 22, 2013, from http://WWW.edtx.org/uploads/general/pdf—downloads/miso-PDFs/EDTX_TSTEM_Academyblueprint.pdf
8. Hox, J. (2002). Multilevel analysis: Techniques and applications. Mahwah, NJ: Erlbaum

9. Navruz, B., Erdogan, N., Bicer, A., Capraro, R. M., & Capraro, M. M. (2014). Would a STEM school ‘by any other name smell as sweet? International Journal of Contemporary Educational Research, 1(2), 67-75.
10. Pantic, Z. (2007). STEM sell. New England Journal of Higher Education, 22(1), 25-26.
11. Rogers-Chapman, M. F. (2013). Accessing STEM-focused education: Factors that contribute to the opportunity to attend STEM high schools across the United States. Education and Urban Society, 46, 716-737.
12. Tai, R. H., Sadler, P. M., & Mintzes, J. J. (2006). Factors inşuencing college science success. Journal of College Science Teaching, 36(1), 52-56.
13. Texas Public School System. (2013). History of regional education service centers. Retrieved January 29, 2014, from http://p0rtal.esc20.neUportal/page/portal/TPSS/Files/RegionalEducationServiceCenters.pdf
14. Texas System of Education Service Centers, (2011). Strategic plan 2010-2015. Retrieved January 29, 2014, from http://WWW.esc20.neUusers/0008/d0cs/esc_ab0utus/strategicplanl l.pdf
15. Texas System of Education Service Centers. (2013). History and mission. Retrieved January 29, 2014, from http://WWW.texasresc.net/about-escs/
16. Texas System of Education Service Centers, (2014). ESCS help schools operate. Retrieved January 29, 2014, from http://WWW.texasresc.net/about-escs/
17. Tyson, W., Lee, R., Borman, K. M., & Hanson, M. A. (2007). Science, technology, engineering, and mathematics (STEM) pathways: High school science and math coursework and postsecondary degree attainment. Journal of Education for Students Placed at Risk, 12(3), 243-270.
18. Young W. M., House, A., Wang, H., Singleton, C., SRI International, & Klopfenstein, K. (2011, May). Inclusive STEM schools: Early promise in Texas and unanswered questions. Paper presented at the National Research Council Workshop on Successful STEM Education in K-12 Schools. Retrieved February 15, 2013, from http://sites.nationalacademies.org/xpedio/idcplg?Ichervice=GET_FlLE&dDocName=DBASSE_072639 &RevisionSelectionMethod=Latest
19. Model 1: Unconditional Model
20. MATHiJ-k = ngjk + 7ı'1jk*(TlME,-jk) + eijk
21. T0jk = [600k + rOjk
22. ”ij : ıBlOk '" rljk Level-3 Model
23. faa/< = V000 + Hook
24. Blak = V100 + ulak Mixed Model
25. MATHijk = V000 + y100*TIMEijk+ roj-k + rljk *TIMEl-jk‘l' “00k + ulak *TIMEijk + eijk
26. urkish Journal of EducationTUR. 2014 Volume 3, Issue 4 www.mrjeorg Model 2
27. MATHijk = nojk + 7:1jk*(TIME,-jk) + eijk
28. T0jk = [600k + Boz/(*(ij) + ,302k*(AAjk) + 50330453) + şO4k*(DISjk)
29. + BOS/(*(FEMALEjk) + VOjk
30. ”uk : ,BIOk + ,611k*(1'ljk) + ,BIZk*(AAjk) + 51330451119 + #14k*(DlSjk)
31. + Bljk*(FEMALEk) + rljk Level-3 Model şOOk = V000 + M00k ŞOlk = V010 + M01k şOZk = V020 + M02k 50% : V030 + M03k
32. fazı/< : V040 + M04k Boş/< : V050 + Moşk şIOk : V100 + M10k Şllk : V110 + Mllk
33. l))lzk : V120 + M12k ş13k : V130 + M13k #14k : V140 + M14k
34. Bük : V150 + Mlşk Mixed Model
35. MATHijk : V000 + V010*ij + V020*AAjk + V030*Asjk + 9/040 *DISjk + y050*FEMALEjk + y100* TIMEijk + y110* TIMEijk *ij + y120*TIMEijk*AAjk + y130* TIMEijk*ASjk + y140*TIME[jk*DISjk + y150*TIME[jk*FEMALEjk + rojk + r Ijk *TIMEijk‘l' ”001: + Halk *ij + Mozk *AAjk + Mo3k *Asjk + Mo4k *DISjk + “05k *FEMALEjk + ulOk *TIMEijk + ullk *TIMEijk*ij + Link *TIMEijk*AAjk + ll13k *TIMEijk*ASjk + M14k *TIMEijk*DISjk + 015k *TIMEijk*FEMALEjk + e,,»k
36. urkish Journal of EducationTUR. 2014 Volume 3, Issue 4 www.turje.0rg