Skip to main content

Advertisement

SpringerLink
Log in

College entry indicators for students from inclusive STEM schools in the United States: an HLM analysis of students’ achievement outcomes and school level indicators

  • Original Paper
  • Published:
SN Social Sciences Aims and scope Submit manuscript

Abstract

Inclusive STEM schools have been found the most promising way to meet the need of United State’s workforce in STEM fields. This study compares achievement outcomes of inclusive STEM schools and traditional schools. The data set obtained from Texas Education Agency included 9004 11th grade students from 53 inclusive STEM schools and 19,155 from 53 traditional schools. About half of the sample comprised female students, and 80% of the sample were Hispanic and African American students. Student’s high stake test scores as achievement outcomes and school level variables were analyzed using hierarchical linear modeling. The results revealed that regardless of school type, female students performed better on reading scores whereas male students performed better on mathematics and science scores. In addition, White and Asian students outperformed all other ethnic groups on performance measures. Also, economically disadvantaged students and students in special education program were outperformed by students not identified as disadvantaged or learning disabled. Dropout rate negatively associated with student’s reading, mathematics, and science scores, while percentage of students taking AP/IB end of course exam and SAT/ACT positively associated. In conclusion, inclusive STEM schools can be the solution to shortages in the STEM workforce; however, there still work remains.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AP:

Advanced placement

ACT:

American college testing

IB:

International baccalaureate

CCRS:

College and career readiness standards

CTE:

Career and technical education

HLM:

Hierarchical linear modeling

ISHS:

Inclusive STEM high school

NRC:

National research council

NSF:

National science foundation

PISA:

Program for international student assessment

S&E:

Science and engineering

SAT:

Scholastic assessment test

SES:

Socio-economic status

STAAR:

State of Texas assessments of academic readiness

STEM:

Science, technology, engineering, and math

TAKS:

Texas assessment of knowledge and skills

TEA:

Texas education agency

TIMSS:

Trends in international mathematics and science study

T-STEM:

Texas science, technology, engineering, and math

References

  • Atkinson RD, Hugo J, Lundgren D, Shapiro MJ, Thomas J (2007) Addressing the STEM challenge by expanding specialty math and science high schools. NCSSSMST J 12(2):14–23

    Google Scholar 

  • Campbell DT, Stanley JC, Gage NL (1963) Experimental and quasi-experimental designs for research. Houghton Mifflin, Boston, pp 171–246

    Google Scholar 

  • Christle CA, Jolivette K, Nelson CM (2007) School characteristics related to high school dropout rates. Remed Special Educ 28(6):325–339

    Article  Google Scholar 

  • Educational Policy Improvement Center (2009) Texas college and career readiness standards. University Printing Services at University of Texas-Austin, Austin

    Google Scholar 

  • Erdogan N, Stuessy CL (2015a) Modeling successful STEM high schools in the United States: an ecology framework. Int J Educ Math Sci Technol 3(1):77–92

    Article  Google Scholar 

  • Erdogan N, Stuessy CL (2015b) Examining inclusive STEM schools’ role in the college and career readiness of students in the United States: a multi-group analysis of students’ achievement outcomes. Educ Sci Theory Pract 15(6):1517–1529. https://doi.org/10.12738/estp.2016.1.0072

    Article  Google Scholar 

  • Erdogan N, Corlu MS, Capraro RM (2013) Defining innovation literacy: do robotics programs help students develop innovation literacy skills? Int Online J Educ Sci 5(1):1–9

    Google Scholar 

  • Graham JW, Olchowski AE, Gilreath TD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci 8(3):206–213

    Article  Google Scholar 

  • Heubert JP, Hauser RM (eds) (1998) High stakes: testing for tracking, promotion, and graduation. National Academies Press, Washington

    Google Scholar 

  • Kobrin JL (2007) Determining SAT benchmarks for college readiness. The College Board, New York

    Google Scholar 

  • Means B, House A, Young V, Wang H, Lynch S (2013) Expanding access to STEM-focused education: What are the effects [White paper]? SRI International, Washington

    Google Scholar 

  • Means B, Wang H, Wei X, Iwatani E, Peters V (2018) Broadening participation in STEM college majors: effects of attending a STEM-focused high school. AERA Open 4(4):2332858418806305

    Article  Google Scholar 

  • National Assessment of Educational Progress (2022) The nation’s report card: 2022 NAEP mathematics assessment. Institute of Education Sciences. https://www.nationsreportcard.gov/highlights/mathematics/2022/

  • National Center for Education Statistics (2019) TIMSS 2019 U.S. results. Institute of Education Sciences. https://nces.ed.gov/timss/results19/doc/TIMSS2019_compiled.pdf

  • National Center for Education Statistics (2021) Digest of education statistics: 2020. Institute of Education Sciences. https://nces.ed.gov/programs/digest/d21/tables/dt21_603.70.asp?current=yes

  • National Center for Science and Engineering Statistics (2021) Women, minorities, and persons with disabilities in science and engineering. National Science Foundation, Alexandria

    Google Scholar 

  • National Research Council (2011) Successful K-12 STEM education: identifying effective approaches in science, technology, engineering, and mathematics. Committee on Highly Successful Science Programs for K-12 Science Education. Board on Science Education and Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education. The National Academies Press, Washington

  • National Science and Technology Council (2018) Charting a course for success: America’s strategy for STEM education. The White House, Washington

    Google Scholar 

  • National Science Foundation (2012) Science and engineering indicators 2012. National Science Foundation, Arlington

    Google Scholar 

  • National Science Foundation (2022) The state of U.S. science and engineering 2022. National Science Foundation, Alexandria

    Google Scholar 

  • Navruz B, Erdogan N, Bicer A, Capraro R, Capraro M (2014) Would a STEM school ‘by any other name smell as sweet’? Int J Contemp Educ Res 1(2):67–75

    Google Scholar 

  • Organisation for Economic Co-operation and Development (2019) United States country note: PISA 2018 results. https://www.oecd.org/pisa/publications/PISA2018_CN_USA.pdf

  • Raudenbush SW, Bryk AS (2002) Hierarchical linear models: applications and data analysis methods, 2nd edn. Sage, Thousand Oaks

    Google Scholar 

  • Rubin DB (1996) Multiple imputation after 18+ years. J Am Stat Assoc 91(434):473–489

    Article  Google Scholar 

  • Rumberger RW, Palardy GJ (2005) Test scores, dropout rates, and transfer rates as alternative indicators of high school performance. Am Educ Res J 42(1):3–42

    Article  Google Scholar 

  • Sahin A, Erdogan N, Morgan J, Capraro M, Capraro R (2012) The effects of high school course taking and SAT scores on college major selection. Sak Univ J Educ 2(3):96–109

    Google Scholar 

  • Saw G (2019) The impact of inclusive STEM high schools on student outcomes: a statewide longitudinal evaluation of Texas STEM academies. Int J Sci Math Educ 17(8):1445–1457

    Article  Google Scholar 

  • Stehle SM, Peters-Burton EE (2019) Developing student 21st century skills in selected exemplary inclusive STEM high schools. Int J STEM Educ 6(39):1–15

    Google Scholar 

  • Stone III, JR (2011) Delivering STEM education through career and technical education schools and programs. Paper prepared for the National Academies Board on Science Education and Board on Testing and Assessment for “Highly Successful STEM Schools or Programs for K-12 STEM Education: A Workshop”, Washington

  • Stringfellow KD (2019) Implementation of the Texas college and career readiness standards: improving the college and career readiness of high school students. Texas A&M University, College Station

    Google Scholar 

  • Subotnik RF, Tai HR, Almarode J (2011) Study of the impact of selective SMT high schools: reflections on learners gifted and motivated in science and mathematics. Paper prepared for the National Academies Board on Science Education and Board on Testing and Assessment for “Highly Successful STEM Schools or Programs for K-12 STEM Education: A Workshop”, Washington

  • Texas Education Agency (1996) Adaptations for special populations: commissioner's rules concerning special education services. http://ritter.tea.state.tx.us/rules/tac/chapter089/ch089aa.html

  • Texas Education Agency (2013) Texas science, technology, engineering, and mathematics initiative (T-STEM). http://www.tea.state.tx.us/index2.aspx?id=4470&menu_id=814

  • Texas Education Agency (2014a) Texas assessment of knowledge and skills (TAKS) resources. http://www.tea.state.tx.us/student.assessment/taks/

  • Texas Education Agency (2014b) Technical digest for the academic year 2012–2013. http://tea.texas.gov/Student_Testing_and_Accountability/Testing/Student_Assessment_Overview/Technical_Digest_2012-2013/

  • Texas Education Agency (2020) T-STEM blueprint. https://tea.texas.gov/sites/default/files/2020_T-STEM_Blueprint_2-13-20.pdf

  • U.S. Bureau of Labor Statistics (2022) Employment in STEM education. https://www.bls.gov/emp/tables/stem-employment.htm#2

  • U.S. Department of Education (2010) A blueprint for reform: the reauthorization of the elementary and secondary education act. Education Publications Center, Alexandria

    Google Scholar 

  • Young MV, House A, Wang H, Singleton C, SRI International, Klopfenstein K (2011) Inclusive STEM schools: early promise in Texas and unanswered questions. Paper prepared for the National Academies Board on Science Education and Board on Testing and Assessment for “Highly Successful STEM Schools or Programs for K-12 STEM Education: A Workshop”, Washington

Download references

Acknowledgements

We would like to acknowledge the help of Aggie STEM and Texas Education Agency for providing the support and data for this research.

Funding

This research did not receive any funding.

Author information

Authors and Affiliations

  1. Texas A&M University, 4232 TAMU, College Station, TX, 77843, USA

    Niyazi Erdogan & Carol L. Stuessy

Authors
  1. Niyazi Erdogan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carol L. Stuessy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NE was the primary author of the manuscript. All authors participated in the discussions reported herein. The authors read, edited, and approved the manuscript.

Corresponding author

Correspondence to Niyazi Erdogan.

Ethics declarations

Competing interest

The authors declare that they have no competing interests.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 21 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Erdogan, N., Stuessy, C.L. College entry indicators for students from inclusive STEM schools in the United States: an HLM analysis of students’ achievement outcomes and school level indicators. SN Soc Sci 3, 111 (2023). https://doi.org/10.1007/s43545-023-00701-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s43545-023-00701-y

Keywords

Search

Navigation