All Stories

  1. Designing and Implementing Skill Tests at Scale: Frequent, Computer-Based, Proctored Assessments with Minimal Infrastructure Requirements
  2. Improving LLM-Generated Educational Content: A Case Study on Prototyping, Prompt Engineering, and Evaluating a Tool for Generating Programming Problems for Data Science
  3. How Novices Use Program Visualizations to Understand Code that Manipulates Data Tables
  4. "I'm not sure, but...": Expert Practices that Enable Effective Code Comprehension in Data Science
  5. Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools
  6. How Instructors Incorporate Generative AI into Teaching Computing
  7. From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
  8. Teaching Data Science by Visualizing Data Table Transformations: Pandas Tutor for Python, Tidy Data Tutor for R, and SQL Tutor
  9. Codehound: Helping Instructors Track Pedagogical Code Dependencies in Course Materials
  10. The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses
  11. How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently
  12. TweakIt: Supporting End-User Programmers Who Transmogrify Code
  13. Experiment Reconstruction Reduces Fixation on Surface Details of Explanations