Research

I design and evaluate interactive systems that support both novices and instructors in computing education. Working at the intersection of Computing Education Research (CER) and Human-Computer Interaction (HCI), I integrate AI to understand how novice students learn effectively and help instructors deliver timely, meaningful feedback at scale. My research scaffolds novice learning through diagramming while reducing instructor workload in assessment. My research focuses on introductory CS education, particularly diagramming in learning, database diagramming, which plays a central role in conceptual understanding.

Research Areas

Current Focus

Scaffolding Novice Learning through Diagramming

Scaffolding student learning through alternative media — particularly diagramming, which lets novices express computational thinking without the syntactic burden of code writing. This work sits at the intersection of computing education research, human-computer interaction, and AI.

CS Education Diagramming ER Modeling HCI
Current Focus

Actionable and Effective Feedback at Scale

Reducing instructor workload in assessing student deliverables, so that feedback remains rich even as class sizes grow. Developing and evaluating automated grading systems for computing course assignments, including diagramming and code generation-based autograding frameworks.

Autograding Feedback AI in Education Databases

Publications

  • Prompting through Decomposition: Evaluating the Efficacy of Problem Decomposition Diagrams for Code Generation

    David H. Smith IV, S. Moonwara A. Monisha, Annapurna Vadaparty, Leo Porter, Daniel Zingaro

    Proceedings of the 57th ACM Technical Symposium on Computer Science Education (SIGCSE TS), 2026

  • Drawing Your Programs: Exploring the Applications of Visual-Prompting with GenAI for Teaching and Assessment

    David H. Smith IV, S. Moonwara A. Monisha, Annapurna Vadaparty, Leo Porter, Daniel Zingaro

    arXiv preprint, 2026

  • Empirical Evaluation of LLMs in Predicting Fixes of Configuration Bugs in Smart Home Systems

    Sheikh Moonwara Anjum Monisha, Anirudh Bharadwaj

    arXiv preprint, 2025

  • A Study on Classifying Stack Overflow Questions Based on Difficulty by Utilizing Contextual Features

    Maliha Noushin Raida, Zannatun Naim Sristy, Nawshin Ulfat, Sheikh Moonwara Anjum Monisha, Md. Jubair Ibna Mostafa, Md. Nazmul Haque

    Journal of Systems and Software, Vol. 208, 2024