Virginia Tech

HICE Lab

DBWorkout

Gamified SQL Practice Tool

DBWorkout is an interactive platform that helps students practice SQL through immediate feedback and gamification. Used in CS 4604 (Introduction to Database Management Systems) at Virginia Tech.

FundingTLOS grants: $10,000 ($5,000 Fall 2024, $5,000 Fall 2025)
StatusActive Development
Team20+ members, 4 project leads
Websitedbworkout.cs.vt.edu

Features

  • Progressive SQL challenges at varying difficulty levels
  • Points, badges, and leaderboards
  • Real-time query validation
  • Analytics dashboards for students and instructors

Collaborators

Sehrish Basir Nizamani, Saad Nizamani, Sally Hamouda

LLM & HCI

Large Language Models for Usability Evaluation

Investigating how AI can enhance usability evaluation in software design by applying LLMs to identify design flaws and support UX professionals.

StatusActive (22 undergraduate researchers, Summer 2025)
Publication"Catching UX Flaws in Code" (IEEE VL/HCC 2025)

Research Questions

  1. Can LLMs detect usability problems in code during development?
  2. How can AI tools enhance traditional evaluation approaches?
  3. What are the constraints and biases in AI-based assessment?
  4. How can LLMs teach usability concepts?

Key Finding

LLMs can identify potential usability issues early in development by examining source code directly, before issues manifest in the final UI.

AI in CS Education

Preparing Students for Problem-Solving with LLMs

Examining how to responsibly incorporate AI and LLMs into CS curricula through evidence-based teaching approaches and assessment tools.

FundingCETL grant: $10,000 (Fall 2025)
CourseCS 2104

Team

  • Leaders: Margaret Ellis, Naren Ramakrishnan
  • Researchers: Nikitha Chandrashekar, Yoonji Lee

Recognition

Poster "Demystify, Use, Reflect: Preparing students to be informed LLM-users" accepted to SIGCSE 2026. Presented at Conference on Higher Education Pedagogy (CHEP) February 2025.

Multimodal Classroom Evaluation

AI-Assisted Teaching Observation Framework

Developing an AI-assisted framework for classroom observation that combines NLP and video analysis to provide instructors with comprehensive feedback while reducing evaluator burden.

Funding4-VA Collaborative Research Grant: $30,000
StatusMulti-institutional collaborative research (Fall 2025)

Objectives

  • AI models for analyzing classroom teaching practices
  • Automated identification of effective pedagogical strategies
  • Real-time instructor feedback
  • Faculty development support

Technical Approach

Multimodal analysis integrating NLP for discourse patterns, computer vision for engagement assessment, and explainable AI for transparent evaluations.

Ethical Considerations

Emphasis on instructor consent, privacy-preserving methods, human oversight, bias evaluation, and formative (not summative) assessment focus.

Culture and HCI

Cultural Dimensions in Human-Computer Interaction

Exploring how culture shapes HCI and usability evaluation, investigating how cultural preferences influence website design, user expectations, and evaluation methodologies.

Research Questions

  • How do cultural preferences shape website design expectations?
  • What disconnects exist between stated preferences and actual practices?
  • How can evaluation methods become culturally appropriate?

Key Publications

  • Universal Access in the Information Society (2025) - Cultural preferences vs. practices in Pakistani university websites
  • Behaviour & Information Technology (2022) - Domain and culture-oriented heuristics
  • IEEE Trans. Professional Communication (2022) - Heuristic evaluation vs. guideline scoring

Collaborating Institutions

University of Sindh, University of Mirpurkhas (Pakistan)