Julia Mae Markel

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I'm a fifth-year PhD student in computer science at Stanford advised by James Landay. My research interests are in human-computer interaction with a focus on human-centered AI and computer science education.

  • Julia M. Markel, Steven G. Opferman, James A. Landay, Chris Piech. GPTeach: Interactive TA Training with GPT Based Students. ACM Conference on Learning at Scale, 2023.

  • Julia M. Markel and Philip J. Guo. Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs. ACM Technical Symposium on Computer Science Education (SIGCSE), 2021. Best Paper Award

  • Julia M. Markel and Philip J. Guo. Designing the Future of Experiential Learning Environments for a Post-COVID World: A Preliminary Case Study. Symposium on the New Future of Work, 2020 (Blog post summary)

  • C. Ailie Fraser, Julia M. Markel, N. James Basa, Mira Dontcheva, Scott Klemmer. ReMap: Lowering the Barrier to Help-Seeking with Multimodal Search. ACM Symposium on User Interface Software and Technology (UIST), 2020.

  • Sam Lau, Ian Drosos, Julia M. Markel, Philip J. Guo. The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2020.

  • Priyan Vaithilingam, Julia M. Markel, Philip J. Guo. Papercode: Generating Paper-Based User Interfaces for Code Review, Annotation, and Teaching. ACM Symposium on User Interface Software and Technology (UIST) (poster), 2020.

  • C. Ailie Fraser, Julia M. Markel, N. James Basa, Mira Dontcheva, and Scott Klemmer. ReMap: Multimodal Help-Seeking. ACM Symposium on User Interface Software and Technology (UIST) (poster), 2019.

  • Philip J. Guo, Julia M. Markel, Xiong Zhang. Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website. ACM Conference on Learning at Scale (work-in-progress), 2020.

    • jmarkel@stanford.edu
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