Georgiana Haldeman

Georgiana Haldeman is an active computer science educator and researcher specializing in programming education, particularly for introductory courses (CS1). Her work focuses on improving code quality, program decomposition, and developing educational tools that enhance student learning experiences in computer science education.

Her research interests center around CS1 pedagogy, autograding systems, and code quality assessment. She has developed frameworks for teaching program decomposition and created educational tools like RAVIC (Runtime Analysis Visualizer for Introductory Courses) to help students visualize program execution. Her work often addresses both procedural and conceptual knowledge dimensions in programming education, recognizing the importance of developing both skill sets in novice programmers.

Analysis of her publication record shows a strong focus on practical educational interventions in computer science. Her work spans multiple dimensions of CS education including assessment methods, educational tool development, classroom activities for improving code quality, and gender diversity in computer science. She frequently collaborates with researchers like Monica Babes-Vroman, Andrew Tjang, and Thu D. Nguyen, suggesting established research partnerships in the CS education community.

Her recent publications (2023-2025) indicate active research in program decomposition frameworks, notional machines for databases, and synthesized teaching models that balance procedural and conceptual learning. This demonstrates continued innovation in computer science pedagogy and a commitment to addressing fundamental challenges in teaching introductory programming.