Academic Profile
Barbara Fagundes, PhD
Postdoctoral Researcher Responsible AI Adoption Computing Education Faculty Development
Actively seeking postdoctoral, research scientist, and faculty positions focused on AI in teaching and learning, computing education research, K-12 STEM, and faculty development.
Research Agenda
Three interconnected areas
Pillar 01
Early computational thinking in K-2 settings
Pillar 02
Undergraduate STEM engagement and persistence
Pillar 03
Responsible AI integration in computing and engineering education
Barbara's research agenda focuses on strengthening the computing education pipeline across three interconnected areas: early computational thinking in K-2 settings, undergraduate STEM engagement and persistence, and responsible AI integration in computing and engineering education.
Her doctoral research examined how young children in K-2 classrooms develop foundational computational thinking concepts, including sequencing, algorithm design, and debugging, through structured learning experiences and educational robotics. This work, conducted within an NSF-funded project, generated peer-reviewed publications and curriculum resources used in multiple classroom settings.
At the postdoctoral level, her work has expanded in two directions. The first examines undergraduate student autonomy and motivation in STEM courses through the lens of Self-Determination Theory, with a focus on identifying the instructional practices that support or undermine student engagement and persistence. The second investigates how undergraduate students in computer science and engineering courses adopt and ethically use generative AI tools, with attention to learning processes, responsible use, and implications for course and curriculum design.
Across all three areas, her work is methodologically grounded in qualitative and mixed-methods approaches, including classroom video analysis, focus groups, interviews, thematic analysis, and survey design, and is oriented toward research-to-practice translation: producing findings that shape how instructors teach, how curricula are designed, and how learning environments are built.
Current Projects
Active research and scholarship
Generative AI in Undergraduate CS and Engineering Courses
Leading qualitative research on student adoption and ethical use of generative AI tools in technical undergraduate coursework. Methods include focus groups, thematic analysis, and interpretation of students' responsible AI use patterns. Findings are contributing to a published arXiv preprint and an ongoing manuscript on instructional implications for computing and engineering education.
Autonomy-Supportive Instructional Practices in Higher Education STEM
Developing a first-author manuscript examining faculty practices, barriers, and evolving perceptions around autonomy-supportive teaching in higher education STEM classrooms. Grounded in Self-Determination Theory. Target journal: International Journal of STEM Education.
Student Pedagogy Advocates Program
Co-leading a student-faculty partnership initiative at Purdue's Center for Instructional Excellence, embedding undergraduate student perspectives into instructional improvement processes. Work includes mentoring undergraduate partners and contributing to a conference paper disseminating the program model.
Research & Teaching Collaborations
Click any project to see collaborators.
Click a project node above to see collaborators and details.
Publications
Research outputs
Peer-reviewed journal articles
- Tank, K. M., Ottenbreit-Leftwich, A., Moore, T. J., Yang, S., Wafula, Z., Kim, J., Fagundes, B., & Chu, L. (2024). Investigating sequencing as a means to computational thinking in young children. International Journal of Computer Science Education in Schools, 6(3), 67-77. doi:10.21585/ijcses.v6i3.192
Preprints and submitted manuscripts
- Dickey, E., Bejarano, A., Kuperus, R., & Fagundes, B. (2025). Evaluating the AI-Lab intervention: Impact on student perception and use of generative AI in early undergraduate computer science courses. arXiv. doi:10.48550/arXiv.2505.00100
Manuscripts in preparation
- Fagundes, B., Harris-Thomas, B., Bonem, E., Guberman, D., & Levesque-Bristol, C. (2026). Supporting student autonomy in higher education STEM classrooms: Faculty practices, barriers, and evolving perceptions.
Peer-reviewed conference papers
- Fagundes, B., & Moore, T. J. (2025, June). Comparing computational thinking learning and engagement in first-grade boys and girls: A study of algorithm design and debugging (WIP). ASEE Annual Conference & Exposition.
- Fagundes, B., Guberman, D., Smart, K., & Holder, K. (2025, June). Student pedagogy advocates: Enhancing teaching and learning through student-faculty partnerships (WIP). ASEE Annual Conference & Exposition. doi:10.18260/1-2--55986
- Wafula, Z., Tank, K. M., Moore, T. J., Ottenbreit-Leftwich, A. T., Fagundes, B., & Kim, J. (2024). Assessing computational thinking skills in early elementary students: A focus on sequencing tasks. SITE International Conference (pp. 400-405). learntechlib.org/p/223964
- Fagundes, B., Bhide, N., Moore, T. J., & Tank, K. M. (2021, July). Computational thinking in first-grade students using a computational device (WIP). ASEE Annual Conference & Exposition. doi:10.18260/1-2--36825
- Fagundes, B., Ehsan, H., Moore, T. J., Tank, K. M., & Cardella, M. E. (2020, June). First-graders' computational thinking in informal learning settings (WIP). ASEE Annual Conference & Exposition. doi:10.18260/1-2--35541
- Johnston, A. C., Lopez-Parra, R. D., Tank, K. M., Moore, T. J., & Fagundes, B. (2019, June). Design decision processes of first-grade students during an engineering design-based STEM unit. ASEE Annual Conference & Exposition. doi:10.18260/1-2--32599
- Yeter, I. H., Rynearson, A. M., Ehsan, H., Rehmat, A. P., Dasgupta, A., Fagundes, B., Menekse, M., & Cardella, M. E. (2019, June). Design and implementation of data collection in a large-scale, multi-year pre-college engineering study. ASEE Annual Conference & Exposition. doi:10.18260/1-2--32596
Presentations, workshops, and posters
- Moore, T., Tank, K., & Fagundes, B. (2023). Task interviews as a research tool: Cases from K-2 computational thinking. Workshop presented at the Pre-College Engineering Education Division (PCEE) at the 2023 ASEE Annual Conference & Exposition, Baltimore, MD.
- Ottenbreit-Leftwich, A., Moore, T. J., Tank, K. M., Kim, J., Fagundes, B., Chu, L., & Wafula, Z. (2023). Rethinking circle time: Development of K-2 CT literacy integrated curriculum [Poster presentation]. SIGCSE 2023: 54th ACM Technical Symposium on Computer Science Education, Toronto, Ontario, Canada (pp. 1394-1394). doi:10.1145/3545947.3576338
- Fagundes, B., Bhide, N., Moore, T. J., Drummond Oaks, M., & Godwin, A. (2022, June). Online professional development aid for teaching an engineering design-based curriculum in 8th grade (Resource Exchange). Work showcased at the Exhibit Hall in the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN.
- Lopez-Parra, R. D., Fagundes, B., Wallace, D., Bhide, N., Moore, T. J., Drummond Oaks, M., & Godwin, A. (2022, June). Engineering design-based curriculum for teaching 8th grade students renewable energy (Resource Exchange). Work showcased at the Exhibit Hall in the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN.
- Fagundes, B., & Bhide, N. (2021, July). Computational thinking in first-grade students using a computational device. Virtual poster presentation at the 2021 ASEE Annual Conference & Exposition. Online.
- Fagundes, B., & Cardella, M. (2018, December). Exploring engineering behaviors of young children interacting with a parent. ENE Explorer Poster Session presentation at the Engineering Education Researcher Seminar, Purdue University, West Lafayette, IN.
Methods and Tools
Methodological toolkit
Barbara's research draws on qualitative and mixed-methods approaches suited to studying learning in naturalistic and institutional settings. Her methodological toolkit includes classroom-based video data collection and analysis, semi-structured interviews and focus groups, thematic analysis, survey design and administration, and human subjects research protocols in K-12 and higher education contexts. She uses NVivo for qualitative data management, Qualtrics for survey design and data collection, and has experience coordinating large-scale data collection across multiple school and institutional sites.
CV and Contact