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Chris Piech
Person information
- affiliation: Stanford University, CA, USA
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2020 – today
- 2024
- [c58]Ali Malik
, Juliette Woodrow
, Chao Wang
, Chris Piech
:
TeachNow: Enabling Teachers to Provide Spontaneous, Realtime 1: 1 Help in Massive Online Courses. ITiCSE (1) 2024 - [c57]Md Sazzad Islam
, Moussa Koulako Bala Doumbouya
, Christopher D. Manning
, Chris Piech
:
Handwritten Code Recognition for Pen-and-Paper CS Education. L@S 2024: 200-210 - [c56]Thomas Jefferson
, Chris Gregg
, Chris Piech
:
PyodideU: Unlocking Python Entirely in a Browser for CS1. SIGCSE (1) 2024: 583-589 - [c55]Evan Zheran Liu
, David Yuan
, Ahmed Ahmed
, Elyse Cornwall
, Juliette Woodrow
, Kaylee Burns
, Allen Nie
, Emma Brunskill
, Chris Piech
, Chelsea Finn
:
A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. SIGCSE (1) 2024: 736-742 - [c54]Ali Malik
, Juliette Woodrow
, Chris Piech
:
Learners Teaching Novices: An Uplifting Alternative Assessment. SIGCSE (1) 2024: 785-791 - [c53]Sierra Wang
, John C. Mitchell
, Chris Piech
:
A Large Scale RCT on Effective Error Messages in CS1. SIGCSE (1) 2024: 1395-1401 - [c52]Juliette Woodrow
, Ali Malik
, Chris Piech
:
AI Teaches the Art of Elegant Coding: Timely, Fair, and Helpful Style Feedback in a Global Course. SIGCSE (1) 2024: 1442-1448 - [c51]Sierra Wang
, John C. Mitchell
, Nick Haber
, Chris Piech
:
Math IDE: A Platform for Creating with Math. SIGCSE (2) 2024: 1844-1845 - [i31]Sonja Johnson-Yu, Nicholas Bowman, Mehran Sahami, Chris Piech:
SimGrade: Using Code Similarity Measures for More Accurate Human Grading. CoRR abs/2403.14637 (2024) - [i30]Ali Malik, Juliette Woodrow, Chris Piech:
Learners Teaching Novices: An Uplifting Alternative Assessment. CoRR abs/2403.14971 (2024) - [i29]Juliette Woodrow, Ali Malik, Chris Piech:
AI Teaches the Art of Elegant Coding: Timely, Fair, and Helpful Style Feedback in a Global Course. CoRR abs/2403.14986 (2024) - [i28]Ali Malik, Juliette Woodrow, Chao Wang, Chris Piech:
TeachNow: Enabling Teachers to Provide Spontaneous, Realtime 1: 1 Help in Massive Online Courses. CoRR abs/2404.11918 (2024) - [i27]Ali Malik, Stephen Mayhew, Chris Piech, Klinton Bicknell:
From Tarzan to Tolkien: Controlling the Language Proficiency Level of LLMs for Content Generation. CoRR abs/2406.03030 (2024) - [i26]Allen Nie, Yash Chandak, Miroslav Suzara, Ali Malik, Juliette Woodrow, Matt Peng, Mehran Sahami, Emma Brunskill, Chris Piech:
The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances. CoRR abs/2407.09975 (2024) - 2023
- [c50]Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing:
Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) 2023: 26-31 - [c49]Anaïs Tack, Ekaterina Kochmar, Zheng Yuan
, Serge Bibauw, Chris Piech:
The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues. BEA@ACL 2023: 785-795 - [c48]Yunsung Kim, Sreechan Sankaranarayanan, Chris Piech, Candace Thille:
Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency. EDM 2023 - [c47]Yunsung Kim
, Chris Piech
:
The Student Zipf Theory: Inferring Latent Structures in Open-Ended Student Work To Help Educators. LAK 2023: 464-475 - [c46]Yunsung Kim
, Chris Piech
:
High-Resolution Course Feedback: Timely Feedback Mechanism for Instructors. L@S 2023: 81-91 - [c45]Julia M. Markel
, Steven G. Opferman
, James A. Landay
, Chris Piech
:
GPTeach: Interactive TA Training with GPT-based Students. L@S 2023: 226-236 - [c44]Allen Nie, Yuhui Zhang, Atharva Amdekar, Chris Piech, Tatsunori B. Hashimoto, Tobias Gerstenberg:
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. NeurIPS 2023 - [c43]Charis Charitsis
, Chris Piech
, John C. Mitchell
:
Detecting the Reasons for Program Decomposition in CS1 and Evaluating Their Impact. SIGCSE (1) 2023: 1014-1020 - [c42]Moussa Doumbouya, Baba Mamadi Diané, Solo Farabado Cissé, Djibrila Diané, Abdoulaye Sow, Séré Moussa Doumbouya, Daouda Bangoura, Fodé Moriba Bayo, Ibrahima Sory 2. Condé, Kalo Mory Diané, Chris Piech, Christopher D. Manning:
Machine Translation for Nko: Tools, Corpora, and Baseline Results. WMT 2023: 312-343 - [i25]Colin Sullivan, Mo Tiwari, Sebastian Thrun, Chris Piech:
Bayesian Decision Trees via Tractable Priors and Probabilistic Context-Free Grammars. CoRR abs/2302.07407 (2023) - [i24]Anaïs Tack, Ekaterina Kochmar, Zheng Yuan, Serge Bibauw, Chris Piech:
The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues. CoRR abs/2306.06941 (2023) - [i23]Moussa Koulako Bala Doumbouya, Baba Mamadi Diané, Solo Farabado Cissé, Djibrila Diané, Abdoulaye Sow, Séré Moussa Doumbouya, Daouda Bangoura, Fodé Moriba Bayo, Ibrahima Sory 2. Condé, Kalo Mory Diané, Chris Piech, Christopher D. Manning:
Machine Translation for Nko: Tools, Corpora and Baseline Results. CoRR abs/2310.15612 (2023) - [i22]Mo Tiwari, Ryan Kang, Donghyun Lee, Sebastian Thrun, Chris Piech, Ilan Shomorony, Martin Jinye Zhang:
BanditPAM++: Faster k-medoids Clustering. CoRR abs/2310.18844 (2023) - [i21]Allen Nie, Yuhui Zhang, Atharva Amdekar, Chris Piech, Tatsunori Hashimoto, Tobias Gerstenberg:
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. CoRR abs/2310.19677 (2023) - [i20]Yunsung Kim, Sreechan Sankaranarayanan, Chris Piech, Candace Thille:
Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency. CoRR abs/2311.08594 (2023) - 2022
- [c41]Anaïs Tack, Chris Piech:
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues. EDM 2022 - [c40]Charis Charitsis, Chris Piech, John C. Mitchell
:
Function Names: Quantifying the Relationship Between Identifiers and Their Functionality to Improve Them. L@S 2022: 93-101 - [c39]Charis Charitsis, Chris Piech, John C. Mitchell
:
Using NLP to Quantify Program Decomposition in CS1. L@S 2022: 113-120 - [c38]Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn:
Giving Feedback on Interactive Student Programs with Meta-Exploration. NeurIPS 2022 - [c37]Mo Tiwari, Ryan Kang, Jaeyong Lee, Chris Piech, Ilan Shomorony, Sebastian Thrun, Martin J. Zhang:
MABSplit: Faster Forest Training Using Multi-Armed Bandits. NeurIPS 2022 - [c36]Charis Charitsis, Chris Piech, John C. Mitchell
:
Feedback on Program Development Process for CS1 Students. SIGCSE (2) 2022: 1150 - [i19]Anaïs Tack, Chris Piech:
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues. CoRR abs/2205.07540 (2022) - [i18]Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn:
Giving Feedback on Interactive Student Programs with Meta-Exploration. CoRR abs/2211.08802 (2022) - [i17]Mo Tiwari, Ryan Kang, Je-Yong Lee, Sebastian Thrun, Chris Piech, Ilan Shomorony, Martin Jinye Zhang:
MABSplit: Faster Forest Training Using Multi-Armed Bandits. CoRR abs/2212.07473 (2022) - [i16]Mo Tiwari, Ryan Kang, Je-Yong Lee, Luke Lee, Chris Piech, Sebastian Thrun, Ilan Shomorony, Martin Jinye Zhang:
Faster Maximum Inner Product Search in High Dimensions. CoRR abs/2212.07551 (2022) - 2021
- [c35]Moussa Doumbouya, Lisa Einstein, Chris Piech:
Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users. AAAI 2021: 14757-14765 - [c34]Sonja Johnson-Yu, Nicholas Bowman, Mehran Sahami, Chris Piech:
SimGrade: Using Code Similarity Measures for More Accurate Human Grading. EDM 2021 - [c33]Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech:
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. EDM 2021 - [c32]Charis Charitsis, Chris Piech, John C. Mitchell
:
Simplifying Automated Assessment in CS1. ICETM 2021: 226-231 - [c31]Charis Charitsis, Chris Piech, John C. Mitchell
:
Assessing Function Names and Quantifying the Relationship Between Identifiers and Their Functionality to Improve Them. L@S 2021: 291-294 - [c30]Allen Nie, Emma Brunskill, Chris Piech:
Play to Grade: Testing Coding Games as Classifying Markov Decision Process. NeurIPS 2021: 1506-1518 - [c29]Maxwell Bigman, Ethan Roy, Jorge Garcia, Miroslav Suzara, Kaili Wang, Chris Piech:
PearProgram: A More Fruitful Approach to Pair Programming. SIGCSE 2021: 900-906 - [c28]Christopher Piech, Ali Malik, Kylie Jue, Mehran Sahami:
Code in Place: Online Section Leading for Scalable Human-Centered Learning. SIGCSE 2021: 973-979 - [i15]Moussa Doumbouya, Lisa Einstein, Chris Piech:
Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users. CoRR abs/2104.13083 (2021) - [i14]Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn:
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR abs/2107.14035 (2021) - [i13]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Modeling Item Response Theory with Stochastic Variational Inference. CoRR abs/2108.11579 (2021) - [i12]Allen Nie, Emma Brunskill, Chris Piech:
Play to Grade: Testing Coding Games as Classifying Markov Decision Process. CoRR abs/2110.14615 (2021) - 2020
- [c27]Chris Piech, Ali Malik, Laura M. Scott, Robert T. Chang, Charles Lin:
The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response. AAAI 2020: 471-479 - [c26]Chris Piech, Engin Bumbacher, Richard Lee Davis:
Measuring Ability-to-Learn Using Parametric Learning Gain Functions. EDM 2020 - [c25]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Variational Item Response Theory: Fast, Accurate, and Expressive. EDM 2020 - [c24]Chris Piech, Lisa Yan, Lisa Einstein, Ana Saavedra, Baris Bozkurt, Eliska Sestáková
, Ondrej Guth, Nick McKeown:
Co-Teaching Computer Science Across Borders: Human-Centric Learning at Scale. L@S 2020: 103-113 - [c23]Chris Piech, Sami Abu-El-Haija:
Human Languages in Source Code: Auto-Translation for Localized Instruction. L@S 2020: 167-174 - [c22]Serhat Arslan
, Mo Tiwari, Chris Piech:
Using Google Search Trends to Estimate Global Patterns in Learning. L@S 2020: 185-195 - [c21]Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony:
BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits. NeurIPS 2020 - [i11]Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman:
Variational Item Response Theory: Fast, Accurate, and Expressive. CoRR abs/2002.00276 (2020) - [i10]Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony:
Bandit-PAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits. CoRR abs/2006.06856 (2020)
2010 – 2019
- 2019
- [c20]Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech:
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. AAAI 2019: 782-790 - [c19]Noah Arthurs, Ben Stenhaug, Sergey Karayev, Chris Piech:
Grades are not Normal: Improving Exam Score Models Using the Logit-Normal Distribution. EDM 2019 - [c18]Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke:
Using Latent Variable Models to Observe Academic Pathways. EDM 2019 - [c17]Lisa Yan, Nick McKeown, Chris Piech:
The PyramidSnapshot Challenge: Understanding Student Process from Visual Output of Programs. SIGCSE 2019: 119-125 - [c16]Lisa Yan, Annie Hu, Chris Piech:
Pensieve: Feedback on Coding Process for Novices. SIGCSE 2019: 253-259 - [i9]Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, John Mitchell, Noah D. Goodman, Chris Piech:
Generative Grading: Neural Approximate Parsing for Automated Student Feedback. CoRR abs/1905.09916 (2019) - [i8]Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke:
Using Latent Variable Models to Observe Academic Pathways. CoRR abs/1905.13383 (2019) - [i7]Chris Piech, Ali Malik, Laura M. Scott, Robert T. Chang, Charles Lin:
The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing. CoRR abs/1906.01811 (2019) - [i6]Chris Piech, Sami Abu-El-Haija:
Human Languages in Source Code: Auto-Translation for Localized Instruction. CoRR abs/1909.04556 (2019) - 2018
- [c15]Lisa Yan, Nick McKeown, Mehran Sahami, Chris Piech:
TMOSS: Using Intermediate Assignment Work to Understand Excessive Collaboration in Large Classes. SIGCSE 2018: 110-115 - [c14]Chris Piech, Chris Gregg
:
BlueBook: A Computerized Replacement for Paper Tests in Computer Science. SIGCSE 2018: 562-567 - [i5]Christina Wadsworth, Francesca Vera, Chris Piech:
Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction. CoRR abs/1807.00199 (2018) - [i4]Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech:
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. CoRR abs/1809.01357 (2018) - 2017
- [c13]Lisa Wang, Angela Sy, Larry Liu, Chris Piech:
Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning. EDM 2017 - [c12]Lisa Wang, Angela Sy, Larry Liu, Chris Piech:
Deep Knowledge Tracing On Programming Exercises. L@S 2017: 201-204 - [c11]Thomas W. Price
, Neil C. C. Brown, Chris Piech, Kelly Rivers:
Sharing and Using Programming Log Data (Abstract Only). SIGCSE 2017: 729 - 2016
- [b1]Chris Piech:
Uncovering patterns in student work: machine learning to understand human learning. Stanford University, USA, 2016 - [c10]Mehran Sahami, Chris Piech:
As CS Enrollments Grow, Are We Attracting Weaker Students? SIGCSE 2016: 54-59 - 2015
- [c9]Rob Semmens, Chris Piech, Michèlle Friend
:
Who Are You? We Really Wanna Know... Especially If You Think You're Like a Computer Scientist. GenderIT 2015: 40-43 - [c8]Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas J. Guibas:
Learning Program Embeddings to Propagate Feedback on Student Code. ICML 2015: 1093-1102 - [c7]Chris Piech, Mehran Sahami, Jonathan Huang, Leonidas J. Guibas:
Autonomously Generating Hints by Inferring Problem Solving Policies. L@S 2015: 195-204 - [c6]Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein:
Deep Knowledge Tracing. NIPS 2015: 505-513 - [i3]Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas J. Guibas:
Learning Program Embeddings to Propagate Feedback on Student Code. CoRR abs/1505.05969 (2015) - [i2]Chris Piech, Jonathan Spencer, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein:
Deep Knowledge Tracing. CoRR abs/1506.05908 (2015) - 2014
- [c5]Andy Nguyen, Christopher Piech, Jonathan Huang, Leonidas J. Guibas:
Codewebs: scalable homework search for massive open online programming courses. WWW 2014: 491-502 - 2013
- [c4]Jonathan Huang, Chris Piech, Andy Nguyen, Leonidas J. Guibas:
Syntactic and Functional Variability of a Million Code Submissions in a Machine Learning MOOC. AIED Workshops 2013 - [c3]Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong B. Do, Andrew Y. Ng, Daphne Koller:
Tuned Models of Peer Assessment in MOOCs. EDM 2013: 153-160 - [c2]René F. Kizilcec, Chris Piech, Emily Schneider:
Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. LAK 2013: 170-179 - [i1]Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong B. Do, Andrew Y. Ng, Daphne Koller:
Tuned Models of Peer Assessment in MOOCs. CoRR abs/1307.2579 (2013) - 2012
- [c1]Chris Piech, Mehran Sahami, Daphne Koller, Steve Cooper, Paulo Blikstein
:
Modeling how students learn to program. SIGCSE 2012: 153-160
Coauthor Index
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