Biography
Mariana Silva is a Teaching Associate Professor in Computer Science at the University of Illinois at Urbana-Champaign. Before joining CS@Illinois in 2017, she was a lecturer in the Department of Mechanical Science and Engineering for 5 years. She received her Bachelor’s and Master’s degrees in mechanical engineering from the Federal University of Rio de Janeiro, Brazil and earned a PhD in Theoretical and Applied Mechanics from the University of Illinois in 2009. Her doctoral research focused on the theory, computation, and design optimization of physical systems governed by partial differential equations. It addressed problems in the areas of static and transient structural topology optimization, material design, energy mitigation, fracture mechanics and robust optimization.
Silva is an expert in the use of computer-based tools for teaching and learning in large STEM university courses, with extensive experience in course development for engineering, computer science, and mathematics. Her educational research focuses on the use of computerized assessment and collaborative learning in higher education. Silva was a research collaborator in the NSF Cyberlearning Grant, “DIP: Improving Collaborative Learning in Engineering Classes through Integrated Tools,” where she was responsible for creating the weekly collaborative activities, training course staff to support these classes and helping with the development of a software that allows synchronized editing via tablets during in-person classes. She is currently the PI for the NSF IUSE Grant “Enhancing equity and access via digitally-mediated collaborative learning experiences” which aims to explore the interconnections between online learning, equity, and access.
Research Interests
- Fostering collaborations and group work during programming activities
- Exploration of technological innovations for large-scale teaching, such as the development of online course assessments.
Education
- PhD Theoretical and Applied Mechanics, University of Illinois at Urbana-Champaign, 2009
- MS Mechanical Engineering, Federal University of Rio de Janeiro, Brazil, 2003
- BS Mechanical Engineering, Federal University of Rio de Janeiro, Brazil, 2001
Courses Taught
- CS 199 1PY (CS 199 D1, CS 199 D2, CS 199 LD1, CS 199 MTS, CS 199 PY1) - Python for Data
- CS 357 (MATH 357) - Numerical Methods I
- CS 498 OL3 (CS 498 OL4) - Intro to Online Learning Sys
- MATH 299 - Computational Tools Linear Alg
- MATH 415 - Applied Linear Algebra
- TAM 251 - Introductory Solid Mechanics
Additional Campus Affiliations
Teaching Associate Professor, Computer Science
KEEN Catalyst, Grainger College of Engineering
Recent Publications
Downey, K., Miller, K., Silva, M., & Zilles, C. (2024). One Solution to Addressing Assessment Logistical Problems: An Experience Setting Up and Operating an In-person Testing Center. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (pp. 317-323). (SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3626252.3630902
Fong, M. M., Huang, S., Alawini, A., Silva, M. T., & Herman, G. L. (2024). Exploring Computing Students' Sense of Belonging Before and After a Collaborative Learning Course. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (pp. 359-365). (SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3626252.3630850
Gulati, R., West, M., Zilles, C., & Silva, M. T. (2024). Comparing the Security of Three Proctoring Regimens for Bring-Your-Own-Device Exams. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (pp. 429-435). (SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3626252.3630809
Montagner, I. D. S., Ferrão, R. C., Kurauchi, A., Silva, M. T., & Zilles, C. (2024). Evaluating Mastery-oriented Grading in an Intensive CS1 Course. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (pp. 303-309). (SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3626252.3630841
Chen, H., West, M., Hilgenfeldt, S., & Silva, M. (2023). Measuring the Impact of a Computational Linear Algebra Course on Students' Exam Performance in a Subsequent Numerical Methods Course. In SIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education (pp. 115-121). (SIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3545945.3569778