Email: snbaker@tacc.utexas.edu
Stephanie Baker joined TACC’s Evaluation Services team in 2019. In her current role, she leads mixed methods research and evaluation projects in STEM and STEM education, focusing on areas such as cyberinfrastructure, engineering, artificial intelligence, mathematical modeling, user experience, and computer science education. Before joining TACC, she honed her research and evaluation skills as a postdoctoral fellow and then research associate at The University of Texas at Austin's STEM Center in the College of Education. Stephanie's personal research agenda centers on studying noncognitive factors crucial for success in STEM fields—such as sense of belonging—as well as the use of novel data collection instruments and analytic methods in people research. Her work draws on extensive technical training, considerable experience developing practical measures, and a proven ability to turn complex data into actionable insights.
Jacobson, M. R., Baker, S. N., Yang, Y., Childs, J., Wang, Z., & Garbrecht, L.S. (2025). Data sharing and evaluation: Evaluation’s role in improving the quality of open science data sharing platforms. New Directions for Evaluation. https://doi.org/10.1002/ev.20621
Baker, S., Garbrecht, L., Yang, Y., & Fan, Z. (2024). DesignSafe Annual Evaluation Report 2023-2024. DesignSafe-Cyberinfrastructure. https://doi.org/10.17603/ds2-hwr8-xh62
Martin, N. D., Baker, S. N., & Warner, J. R. (2024) Disparities in students’ experience of computer science are exacerbated when considering who does and does not take advanced placement exams. Texas Education Research Center Policy Brief. https://texaserc.utexas.edu/wp-content/uploads/2024/04/EPIC-118-Policy-Brief_4.4.24-.pdf
Wang, Z., Martin, N. D., Baker, S. N., & Haynes, M. (2024). A measurement invariance analysis of the Motivation to Teach Computer Science (MTCS) scale among female and male educators. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 1, 1409-1413. ACM Digital Library. https://doi.org/10.1145/3626252.3630766
Martin, N. D., Baker, S. N., Haynes, M., & Warner, J. R. (2023). The Motivation to Teach Computer Science (MTCS) scale: Development, validation, and implications for use. Computer Science Education, 34(2), 310-327. https://doi.org/10.1080/08993408.2023.2182561
Warner, J. R., Baker, S. N., Haynes, M., Jacobson, M., Bibriescas, N. & Yang, Y. (2022). Gender, race, and economic status along the computing education pipeline: Examining disparities in course enrollment and wage earnings. In Proceedings of the 2022 ACM Conference on International Computing Education Research, 1, 61-72. ACM Digital Library. https://doi.org/10.1145/3501385.3543968
Warner, J. R., Fletcher, C. L., Martin, N. D., Baker, S. N., (2022). Applying the CAPE framework to measure equity and inform policy in computer science education. Policy Futures in Education. https://doi.org/10.1177/14782103221074467
