VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.

Browsing by Author "Tang, Xiaohang"

Now showing 1 - 4 of 4
  • Thumbnail Image
    CFlow: Supporting Semantic Flow Analysis of Students' Code in Programming Problems at Scale
    Zhang, Ashley; Tang, Xiaohang; Oney, Steve; Chen, Yan (ACM, 2024-07-09)
    Introductory programming courses have been growing rapidly, now enrolling hundreds or thousands of students. In such large courses, it can be overwhelmingly difficult for instructors to understand class-wide problem-solving patterns or issues, which is crucial for improving instruction and addressing important pedagogical challenges. In this paper, we propose a technique and system, CFlow, for creating understandable and navigable representations of code at scale. CFlow is able to represent thousands of code samples in a visualization that resembles a single code sample. CFlow creates scalable code representations by (1) clustering individual statements with similar semantic purposes, (2) presenting clustered statements in a way that maintains semantic relationships between statements, (3) representing the correctness of different variations as a histogram, and (4) allowing users to navigate through solutions interactively using semantic filters. With a multi-level view design, users can navigate high-level patterns, and low-level implementations. This is in contrast to prior tools that either limit their focus on isolated statements (and thus discard the surrounding context of those statements) or cluster entire code samples (which can lead to large numbers of clusters—for example, if there are 𝑛 code features and 𝑚 implementations of each, there can be 𝑚𝑛 clusters). We evaluated the effectiveness of CFlow with a comparison study, found participants using CFlow spent only half the time identifying mistakes and recalled twice as many desired patterns from over 6,000 submissions.
  • Thumbnail Image
    GesMessages: Using Mid-air Gestures to Manage Notifications
    Li, Xiang; Chen, Yuzheng; Tang, Xiaohang (ACM, 2023-10-13)
    This paper introduces GesMessages, an innovative mid-air interactive application that uses simple gestures to manage real-time message notifications on laptops and large displays. Leveraging cameras on computers or smart devices, the application offers three distinct gestures: expanding notifications for immediate attention, hiding non-urgent messages, and deleting spam messages. We present the technical setup and system design. Additionally, we explore potential applications in context-awareness systems, contributing to gestural interaction research. Our work fosters a deeper understanding of mid-air interaction’s impact on message management and future interactive systems.
  • Thumbnail Image
    VizGroup: An AI-assisted Event-driven System for Collaborative Programming Learning Analytics
    Tang, Xiaohang; Wong, Sam; Pu, Kevin; Chen, Xi; Yang, Yalong; Chen, Yan (ACM, 2024-10-13)
    Programming instructors often conduct collaborative learning activities, like Peer Instruction, to foster a deeper understanding in students and enhance their engagement with learning. These activities, however, may not always yield productive outcomes due to the diversity of student mental models and their ineffective collaboration. In this work, we introduce VizGroup, an AI-assisted system that enables programming instructors to easily oversee students’ real-time collaborative learning behaviors during large programming courses. VizGroup leverages Large Language Models (LLMs) to recommend event specifications for instructors so that they can simultaneously track and receive alerts about key correlation patterns between various collaboration metrics and ongoing coding tasks. We evaluated VizGroup with 12 instructors in a comparison study using a dataset collected from a Peer Instruction activity that was conducted in a large programming lecture. The results showed that VizGroup helped instructors effectively overview, narrow down, and track nuances throughout students’ behaviors.
  • Thumbnail Image
    VizPI: A Real-Time Visualization Tool for Enhancing Peer Instruction in Large-Scale Programming Lectures
    Tang, Xiaohang; Chen, Xi; Wong, Sam; Chen, Yan (ACM, 2023-10-29)
    Peer instruction (PI) has shown significant potential in facilitating student engagement and collaborative learning. However, the implementation of PI for large-scale programming lectures has proven challenging due to difficulties in monitoring student engagement, discussion topics, and code changes. This paper introduces VizPI, an interactive web tool that enables instructors to conduct, monitor, and assess PI for programming exercises in real-time. With features that visualize the progress of student discussions and code submissions, VizPI allows for more effective oversight of PI activities and the provision of personalized feedback at scale. Our work aims to transform the pedagogical approach to PI in programming education, making it more engaging and adaptable to student needs.