2.3k citations · 3.5k across the 27 of their papers we have counts for
28 papers
Discovering High-Quality Chess Puzzles with Offline Reinforcement Learning
Allen Nie, Anirudhan Badrinath, Nicholas Tomlin +5
Learning and skill mastery require extensive and deliberate practice. In many learning settings, producing high-quality pedagogical materials can require a high level of domain exp…
A Large-Scale Observational Study on Obtaining Lightweight, Randomized Weekly Student Feedback
Yunsung Kim, Hansol Lee, Candace Thille +1
Conventional methods of obtaining student feedback on course experience face a fundamental tradeoff between feedback frequency and quality: as feedback requests become more frequen…
AI Teaches the Art of Elegant Coding: Timely, Fair, and Helpful Style Feedback in a Global Course
Juliette Woodrow, Ali Malik, Chris Piech
Teaching students how to write code that is elegant, reusable, and comprehensible is a fundamental part of CS1 education. However, providing this "style feedback" in a timely manne…
Learners Teaching Novices: An Uplifting Alternative Assessment
Ali Malik, Juliette Woodrow, Chris Piech
We propose and carry-out a novel method of formative assessment called Assessment via Teaching (AVT), in which learners demonstrate their understanding of CS1 topics by tutoring mo…
SimGrade: Using Code Similarity Measures for More Accurate Human Grading
Sonja Johnson-Yu, Nicholas Bowman, Mehran Sahami +1
While the use of programming problems on exams is a common form of summative assessment in CS courses, grading such exam problems can be a difficult and inconsistent process. Throu…
Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency
Yunsung Kim, Sreechan Sankaranarayanan, Chris Piech +1
Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instruct…