Research About STEM Education

UTeach faculty are experts in STEM and STEM teacher preparation. Their work in the field is published in peer-reviewed journals.

Alegre, F., Moreno, J., Dawson,T., Tanjong, E., & Kirshner, D. (2020). Computational thinking for STEM teacher leadership training at Louisiana State University. RESPECT 2020: Research on Equity and Sustained Participation in Engineering, Computing, and Technology. Portland, OR, United States, March 10–11, 2020.

Alegre, F., Moreno, J., Weltman, J., Kirshner, D., Underwood, J., Neubrander, F., & Madden, J. (2020). Introduction to Computational Thinking: a new high school curriculum using CodeWorld. In J. E. Goodell & S. Koc (Eds.), Preparing STEM Teachers: A replication model. Charlotte, NC: Information Age Publishing. 

Ares, N., Stroup, W. M., & Schademan, A. R. (2009). The power of mediating artifacts in group-level development of mathematical discourses. Cognition and Instruction27(1), 1–24.

Bendinelli, A. J., & Marder, M. (2012). Visualization of longitudinal student dataPhysical Review Special Topics–Physics Education Research,8(2), 1–15.

Carrejo, D. J., & Marshall, J. (2007) What is mathematical modelling? Exploring prospective teachers' use of experiments to connect mathematics to the study of motionMathematics Education Research Journal, 19(1), 45–76.

Confrey, J., & Makar, K. (2005). Critiquing and improving the use of data from high-stakes tests with the aid of dynamic statistics software. In C. Dede, J. Honan, & L. Peters (Eds.), Scaling up for success: Lessons from technology-based educational improvement (pp. 198–226). San Francisco: Jossey-Bass.

Confrey, J., Makar, K., & Kazak, S. (2004). Undertaking data analysis of student outcomes as professional development for teachersZDM: International Reviews on Mathematics Education, 36(1), 32–40. 

Craig, C., Verma, R., Stokes, D., Evans, P., & Abrol, B. (2018). The influence of parents on undergraduate and graduate students’ entering the STEM disciplines and STEM careers, International Journal of Science Education,40(6), 621-643.

Craig, C., Evans, P., Stokes, D., Bott, S. (2017). Attracting, preparing and retaining teachers in areas of high need: A teaching science as inquiry model. In M. Peters, B. Cowie & I. Menter (Eds.), A companion to research in teacher education. New York, NY: Springer Publishing.

Dickinson, G., Summers, E. J., & Jackson, J. (2010). Developing expertise in project-based science: A longitudinal study of teacher development and student perceptions. In R. E. Yager (Ed.), Exemplary science for resolving societal challenges (pp. 1–18). Arlington, VA: National Science Teachers Association.

Dickinson, G., & Summers, E. J. (2010). (Re)Anchored, video-centered engagement: The transferability of preservice training to practiceContemporary Issues in Technology and Teacher Education, 10(1)106–118.

Enderle, P., Dentzau, M., Roseler, K., Southerland, S. A., Granger, E., & Hughes, R. (2014). Examining the influence of RET's on science teachers' beliefs and practiceScience Education98, 1077–1108.

Evans, P. K., Dillard, K. C., Rodriguez-Wilhelm, D., & McAlister-Shields, L. (2019). Like-minded people: University-based interdisciplinary collaborations in STEM teacher preparation programs. Journal for STEM Education Research, 2(1), 35–54. 

Farrell, I. K., & Hamed, K. M. (2017). Examining the relationship between technological pedagogical content knowledge (TPACK) and student achievement utilizing the Florida value-added model. Journal of Research on Technology in Education49(3-4), 161–181. 

Farrell, I. & Hamed, K. (2016). Teaching with soap: Examples of project-based units for students and future educators. Science activities: Classroom projects and curriculum ideas, 53(2) 74–86. 

Fletcher, C. L., Warner, J. R., Garbrecht, L., & Ramsey, C. (2018). Lessons learned from developing a framework for evaluating the impact of CS teacher professional development on CS for All outcomes. Paper presented at 2018 AERA Annual Meeting, New York, NY.

Granger, E. M., Bevis, T., Saka, Y., Southerland, S. A., Sampson, V., & Tate, R. (2012). Efficacy of student-centered instruction in supporting student science learningScience338(6103), 105–108.

Hamilton, R. (2011, May 2). Is poverty, not teacher quality or charters, key to student outcomes? Interview with Michael Marder. The Texas Tribune.

Harron, J. (2018). Introducing preservice STEM teachers to computer science: A narrative of theoretically oriented design. Texas Education Review, 6(1), 1733. doi:10.15781/T20R9MM9X

Harron, J., Langdon, J., Gonzalez, J., & Cater, S. (2017) Digital forensicsThe Science Teacher, 84(8), 32–36. 

Horvath, M., Goodell, J., & Kosteas, V. (2018). Decisions to enter and continue in the teaching profession: Evidence from a sample of U.S. secondary STEM teacher candidatesTeaching and Teacher Education, 71, 57–65.

Houle, F., Kirby, K., & Marder, M. (2023). Ethics in physics: The need for culture change. Physics Today, 76(1), 28.

Jett, C. C., Stinson, D. W., & Williams, B. A. (2015). Communities for and with Black male students: Four strategies can be effective in creating supportive learning environments. Mathematics Teacher, 109(4), 284–289.

Kirshner, D. (2016). Configuring learning theory to support teaching. In L. English & D. Kirshner (Eds.), Handbook of international research in mathematics education (3rd Ed) (pp. 98–149). New York: Taylor & Francis.

Lowery, K., Rodriquez, S., & Benfield, P. (2019). Making in the middle: Making as a performance task. Science Scope042(07).

Ludwig, R., & Chimonidou, A. (2013). Hands-on-science: Hands-on, integrated natural sciences for pre-service elementary teachersPaper presented at 2013 NARST Annual International Conference, Rio Grande, Puerto Rico. 

Marder, M., Horn, C., Stephens, S., & Rhodes, A. (2022). Student learning and teacher retention for graduates of Texas Noyce programs. Education Policy Analysis Archives30(147).

Marder, M., David, B., & Hamrock, C. (2020). Math and science outcomes for students of teachers from standard and alternative pathways in Texas. Education Policy Analysis Archives, 28(27).

Marder, M. (2019). Can we inspire every high-school student to take physics? Texas nearly did. APS News, 28(10).

Marder, M. (2018, March). Rise and fall of Texas STEM education: College readiness and course-taking since House Bill 5 of 2013. [White paper].

Marder, M., Brown, C. R., & Plisch, M. (2017). Recruiting Teachers in High-Needs STEM Fields: A survey of current majors and recent STEM grads. The Physics Teacher55(5), 318–318. doi: 10.1119/1.4981053

Marder, M., Patzek, T, & Tinker, S. (2016). Physics, fracking, fuel, and the future. In Physics Today 69(7), 46–52.

Marder, M., &  Walkington, C. (2014). Classroom observation and value-added models give complementary information about quality of mathematics teaching. In T. Kane, K. Kerr, & R. Pianta (Eds.), Designing teacher evaluation systems: New guidance from the Measuring Effective Teaching project (pp. 234–277). New York: John Wiley & Sons.

Marder, M. (2013). A problem with STEMCBE Life Sciences Education12(2), 148–150.

Marder, M. (2012). Failure of U.S. public secondary schools in mathematicsAASA Journal of Scholarship and Practice, 9(1), 8–24.

Marder, M. (2012). Measuring teacher quality with value-added modelingKappa Delta Pi Record, 48, 156–161.

Marder, M. (2011).  Research methods for scienceCambridge, England: Cambridge University Press.

Marder, M., & Bansal, D. (2009). Flow and diffusion of high-stakes test scores. Proceedings of the National Academies of Science, 106, 17267–17270. 

Marshall, J., & Harron, J. R. (2018). Making learners: A framework for evaluating making in STEM educationInterdisciplinary Journal of Problem-Based Learning, 12(2). doi: 10.7771/1541-5015.1749

Marshall, J., & Young, E. S. (2006). Preservice teachers' theory development in physical and simulated environmentsJournal of Research in Science Teaching, 43(9), 907–937. 

Rodriguez, S., Allen, K., Harron, J., & Qadri, S. A. (2019). Making and the 5E learning cycleThe Science Teacher86(5). doi: 10.2505/4/tst18_086_05_48

Rodriguez, S. R., Fletcher, S. S., & Harron, J. R. (2019). Introducing ‘making’ to elementary and secondary preservice science teachers across two university settingsInnovations in Science Teacher Education, 4(4).

Rodriguez, S., Morrison, A., & Benfield, P. (2019). Pulley islands: Third graders conquer a tinkering challenge. Science and Children56(8).

Rodriguez, S., Harron, J., Benfield, P., & Reyes, M. (2018). Illuminating food webs: A maker jigsawScience Scope, 42(1), 54–64.

Rodriguez, S., Harron, J., Fletcher, S., & Spock, H. (2018). Elements of making: A framework to support making in the science classroom. The Science Teacher, 85(2), 24–30.

Siegel, L. M., Dickinson, G., Hooper, E. J., & Daniels, M. (2008). Teaching algebra and geometry concepts by modeling telescope opticsMathematics Teacher, 101(7), 490–497.

Smith, J., & Nadelson, L. (2016). Learning for you and learning for me: Mentoring as professional development for mentor teachers. Mentoring & Tutoring: Partnership in Learning, 24(1), 59–72.

Sparks, D. (2018). The process of becoming: Identity development of African American female science and mathematics preservice teachersJournal of Science Teacher Education, 29(3), 243–261.

Stroup, W., Hills, T., & Carmona, G. (2011). Computing the average square: An agent-based introduction to aspects of psychometric practiceTechnology, Knowledge and Learning16(3), 199–220.

Stroup, W. M. (2005). Learning the basics with calculusJournal of Computers in Mathematics and Science Teaching24(2), 179–196.

Stroup, W. M., Ares, N. M., & Hurford, A. C. (2005). A dialectic analysis of generativity: Issues of network-supported design in mathematics and scienceMathematical Thinking and Learning7(3), 181–206.

Walkington, C., Sherman, M., & Petrosino, A. (2012). ‘Playing the game' of story problems: coordinating situation-based reasoning with algebraic representationThe Journal of Mathematical Behavior, 31, 174–195.