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20212026
most citedBiological learning in key-value memory networks

3 citations · 4 across the 7 of their papers we have counts for

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cs.CY2026

Planning on Paper: Problem Decomposition with Diagrams in Introductory Computing

Annapurna Vadaparty, Devamardeep Hayatpur, Adalbert Gerald Soosai Raj +2

Background and Context. Problem decomposition is a core concern of computing education. It has also become increasingly relevant: in response to GenAI, many CS1 educators are advoc…

cs.CY2026

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

David H. Smith, S. Moonwara A. Monisha, Annapurna Vadaparty +2

When designing a program, both novice programmers and seasoned developers alike often sketch out -- or, perhaps more famously, whiteboard -- their ideas. Yet despite the introducti…

cs.CY2025

Assessing Problem Decomposition in CS1 for the GenAI Era

Samvrit Srinath, Annapurna Vadaparty, David H. Smith +2

Problem decomposition--the ability to break down a large task into smaller, well-defined components--is a critical skill for effectively designing and creating large programs, but…

cs.CY2025

Integrating Large Language Models and Evaluating Student Outcomes in an Introductory Computer Science Course

Annapurna Vadaparty, David H. Smith, Samvrit Srinath +5

Generative AI (GenAI) models have broad implications for education in general, impacting the foundations of what we teach and how we assess. This is especially true in computing, w…

cs.CY2024

CS1-LLM: Integrating LLMs into CS1 Instruction

Annapurna Vadaparty, Daniel Zingaro, David H. Smith +4

The recent, widespread availability of Large Language Models (LLMs) like ChatGPT and GitHub Copilot may impact introductory programming courses (CS1) both in terms of what should b…