All Stories

  1. Incentivizing Good Programming Practices: The Impact of Early Program Submission on Student Course and Exam Performance

    Article • February 2025, ACM (Association for Computing Machinery)

    Ashley Pang

  2. Midterm Exam Outliers Efficiently Highlight Potential Cheaters on Programming Assignments

    Article • February 2025, ACM (Association for Computing Machinery)

    Ashley Pang

  3. Style Anomalies Can Suggest Cheating in CS1 Programs

    Article • July 2024, ACM (Association for Computing Machinery)

    Ashley Pang

  4. Performance Analysis and Interviews of Non-CS-Major Students Sanctioned for Cheating in CS1

    Article • July 2024, ACM (Association for Computing Machinery)

    Ashley Pang

  5. ChatGPT and Cheat Detection in CS1 Using a Program Autograding System

    Article • July 2024, ACM (Association for Computing Machinery)

    Ashley Pang

  6. Experiences Teaching a CS1 Common Course across 7 Institutions

    Article • March 2024, ACM (Association for Computing Machinery)

    Ashley Pang

  7. Towards Comprehensive Metrics for Programming Cheat Detection

    Article • March 2024, ACM (Association for Computing Machinery)

    Ashley Pang

  8. Towards Grading for Equity in a Large CS1 Class: An Experience with Flexible Deadlines and Resubmissions

    Article • June 2023, ACM (Association for Computing Machinery)

    Ashley Pang

  9. Impact of Student Time Spent on Performance in a CS1 Class, Including Prior Experience Effect

    Article • June 2023, ACM (Association for Computing Machinery)

    Ashley Pang

  10. Variability-Inducing Requirements for Programs: Increasing Solution Variability for Similarity Checking

    Article • June 2023, ACM (Association for Computing Machinery)

    Ashley Pang

  11. Impact of Several Low-Effort Cheating-Reduction Methods in a CS1 Class

    Article • March 2023, ACM (Association for Computing Machinery)

    Ashley Pang

  12. Teaching Coral, an introductory language, before C++

    Article • March 2023, ACM (Association for Computing Machinery)

    Ashley Pang