Chris Piech
Chris Piech
Assistant Professor, Stanford University
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
On the opportunities and risks of foundation models
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258, 2021
Deconstructing disengagement: analyzing learner subpopulations in massive open online courses
RF Kizilcec, C Piech, E Schneider
Proceedings of the third international conference on learning analytics and …, 2013
Deep knowledge tracing
C Piech, J Bassen, J Huang, S Ganguli, M Sahami, LJ Guibas, ...
Advances in neural information processing systems 28, 2015
Tuned models of peer assessment in MOOCs
C Piech, J Huang, Z Chen, C Do, A Ng, D Koller
International Conference on Educational Data Mining, 2013
Programming pluralism: Using learning analytics to detect patterns in the learning of computer programming
P Blikstein, M Worsley, C Piech, M Sahami, S Cooper, D Koller
Journal of the Learning Sciences 23 (4), 561-599, 2014
Modeling how students learn to program
C Piech, M Sahami, D Koller, S Cooper, P Blikstein
Proceedings of the 43rd ACM technical symposium on Computer Science …, 2012
Learning program embeddings to propagate feedback on student code
C Piech, J Huang, A Nguyen, M Phulsuksombati, M Sahami, L Guibas
Proceedings of the 32nd International Conference on Machine Learning, Lille …, 2015
Achieving fairness through adversarial learning: an application to recidivism prediction
C Wadsworth, F Vera, C Piech
arXiv preprint arXiv:1807.00199, 2018
Codewebs: scalable homework search for massive open online programming courses
A Nguyen, C Piech, J Huang, L Guibas
Proceedings of the 23rd international conference on World wide web, 491-502, 2014
Autonomously generating hints by inferring problem solving policies
C Piech, M Sahami, J Huang, L Guibas
Proceedings of the second (2015) acm conference on learning@ scale, 195-204, 2015
Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning
L Wang, A Sy, L Liu, C Piech
Proceedings of the 10th International Conference on Educational Data Mining;, 2017
Syntactic and functional variability of a million code submissions in a machine learning mooc
J Huang, C Piech, A Nguyen, L Guibas
AIED 2013 Workshops Proceedings Volume 25, 2013
Deep knowledge tracing on programming exercises
L Wang, A Sy, L Liu, C Piech
Proceedings of the fourth (2017) ACM conference on learning@ scale, 201-204, 2017
The future of data-enriched assessment.
C Thille, E Schneider, RF Kizilcec, C Piech, SA Halawa, DK Greene
Research & Practice in Assessment 9, 5-16, 2014
The AI teacher test: Measuring the pedagogical ability of blender and GPT-3 in educational dialogues
A Tack, C Piech
arXiv preprint arXiv:2205.07540, 2022
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
M Wu, M Mosse, N Goodman, C Piech
AAAI Conference on Artificial Intelligence, 2019
Variational item response theory: Fast, accurate, and expressive
M Wu, RL Davis, BW Domingue, C Piech, N Goodman
arXiv preprint arXiv:2002.00276, 2020
K means
C Piech, A Ng
Internet: http://stanford. edu/~ cpiech/cs221/handouts/kmeans. html,[Mar 05 …, 2013
Pensieve: Feedback on coding process for novices
L Yan, A Hu, C Piech
Proceedings of the 50th acm technical symposium on computer science …, 2019
Banditpam: Almost linear time k-medoids clustering via multi-armed bandits
M Tiwari, MJ Zhang, J Mayclin, S Thrun, C Piech, I Shomorony
Advances in Neural Information Processing Systems 33, 10211-10222, 2020
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Artikkelit 1–20