Currently, Noah is contributing to research projects as a CI AI Education Fellow at the Computing Research Association (CRA). Prior to this, Noah conducted research advised by Professor Lecia Barker at the University of Colorado Boulder.
Current Projects:
Qualitative analysis of roundtable discussions of AI educators, in order to establish consensus on the articulation of the AI knowledge areas, identify the enabling infrastructure needed for expanding high-quality AI education, and develop strategies for increasing AI education capacity.
Designing and testing a theoretically informed curriculum to utilize interdisciplinary transfer between algebra and programming to decrease intrinsic cognitive load, increase self-efficacy, and improve conceptual understanding in introductory programming. This work was initially fielded in summer 2022, presented at the 2024 ACM ITICSE Doctoral Consortium and published as a full paper at ACM Koli Calling 2024.
Conducting mixed methods research—interviews, survey, and discourse analysis—investigating why computer science professionals specify into different sub-disciplines (e.g., AI, HCI, Cybersecurity).
Other Projects:
Created a visualized explainable for the artificial intelligence algorithm "Bayesian Knowledge Tracing", utilizing active user hypothesis generation as a model, and designed and conducted cognitive task analysis interviews on participants learning about the algorithm. This was accepted as a workshop paper to IEEE VIS 2019 and as a full paper in ACM AIED 2023. With Catherine Yeh and Professor Iris Howley.
Conducted survey study to investigate undergraduate CIS students preconceptions of Cybersecurity and Artificial Intelligence, which has been published as a paper and poster in ACM SIGCSE 2024. With Professor Casey Fiesler.
Coded a software extension to the Micro:bit MakeCode interface to incorporate physical play coding blocks, with the goal of making programming education more accessible and fun. Published at ACM CHI 2024. With Professor Junnan Yu.
Conducted a mixed methods study of undergraduate CIS students during the COVID-19 pandemic to investigate the challenges and opportunities afforded by synchronous remote learning in Computer and Information Science (CIS) education. A portion of this research was accepted as a book chapter, Student perspectives on distraction and engagement in the synchronous remote classroom, with further results published in a paper and poster in the 2023 ACM SIGSCE conference and a paper in IEEE FIE 2023.
Contributed to a 47-participant interview study investigating first year women’s experiences in computing courses. Involves running a lab group of four undergraduate researchers, collaborating in study design, and giving feedback on the interview and data analysis process. Results to be submitted to ACM SIGCSE 2025.
Created an interdisciplinary pre-college summer statistics curriculum to teach R-Studio/R-Markdown to High-School students for the data education non-profit Data Stories. Please contact if you think this curriculum may be of use to you!
Created a collection of interactive elements for use in virtual CIS classrooms to serve teachers during the pandemic shutdown as part of the NCWIT K-12 Alliance Back to School and Virtual Resources huddle. These resources aim to engender feelings of interest, belonging, and identity around CIS, and encourage students to continue taking classes.