Chris Piech


Assistant Professor of Computer Science Education, Stanford University.
PhD advised by Leo Guibas and Mehran Sahami.

Office: Gates Building, Room 202
Email: piech at cs.stanford.edu
Office Hours: Thursdays 1:30-3:30p

I was born and grew up in Nairobi, Kenya. When I was twelve I moved to Kuala Lumpur, Malaysia where I lived until I came to Stanford for university, liked it a lot and stayed. I love teaching and I'm into exploring our world (through both science and travelling). My research is in machine learning to understand human learning.


Teaching at Stanford

CS106A

Programming Methodologies

Last: Spring 2018

CS106B

Programming
Abstractions

Last: Fall 2016

CS221

Intro to Artificial Intelligence

Last: Summ 2013

Recent Papers

Fairness through Adversarial Learning: Recidivism Prediction

C. Wadsworth, F. Vera, C. Piech

5th Conference on Fairness, Accountability and Transparency in ML, Stockholm, Sweden. 2018

TMOSS: Understanding Excessive Collaboration

L. Yan, N. McKeown, M. Sahami, C. Piech

Proceedings of the 49th ACM Technical Symposium on Computer Science Education, Baltimore, USA. 2018

BlueBook: Secure, Electronic Computer Science Exams

C. Piech, C. Gregg

Proceedings of the 49th ACM Technical Symposium on Computer Science Education, Baltimore, USA. 2018

Deep Knowledge Tracing on Programming Excercises

L. Wang, A. Sy, L. Liu, C. Piech

Proceedings of the 10th International Conference on Educational Data Mining, Wuhan, China. 2017

Deep Knowledge Tracing

C. Piech, J. Bassen, J. Huang, S. Ganguli, M. Sahami, L. Guibas, J. Sohl-Dickstein

Proceedings of the 29th Conference on Neural Information Processing Systems, Montreal, Canada, 2015

Learning Program Embeddings to Propagate Feedback

C. Piech, J. Huang, A. Nguyen, M. Phulsuksombati, M. Sahami, L. Guibas

Proceedings of the 43rd International Conference on Machine Learning, Lille, France 2015

Inferring Problem Solving Policies

C. Piech, M. Sahami, J. Huang, L. Guibas

Proceedings of the 2nd ACM Conference on Learning at Scale, Vancouver, Canada, 2015

Scalable Homework Search

A. Nguyen, C. Piech, J. Huang, L. Guibas

Proceedings of the 23rd international conference on World Wide Web, Seoul, Korea, 2014

Variability of a Million Code Submissions

J. Huang, C. Piech, A. Nguyen, L. Guibas

MOOC Shop, 11th International Conference on the Learning Sciences, Boulder, USA. 2014

Tuning Peer Grading

C. Piech, J. Huang, Z. Chen, C. Do, A. Ng, D. Koller

Proceedings of the 6th International Conference on Educational Data Mining, Memphis, USA. 2013

The Future of Data-Enriched Assessment

C. Thille, E. Schneider, R. Kizilcec, C. Piech, S. Halawa, D. Greene

Research and Practice in Assessment vol 9. 2014

Measuring Stereotype and Identity in Computer Science

R. Semmens, C. Piech, M. Friend

Proceedings of the Third Conference on GenderIT, Philadelphia USA. 2015

Deconstructing Disengagment in MOOCs

R. Kizilcec, C. Piech, E. Schneider

Proceedings of the 3rd International Conference on Learning Analytics and Knowledge, Leuven, Belgium. 2013

As CS Enrollements Grow, Are we Attracting Weaker Students?

M. Sahami, C. Piech

Proceedings of the 47th ACM Technical Symposium on Computer Science Education, Memphis, USA. 2016

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 Education, Raleigh, USA. 2012

Informatics Education Using Nothing but a Browser

C. Piech, E. Roberts

Proceedings of the IFIP Conference on Informatics in a Globalised World of Education, Mombasa, Kenya. 2011


Teaching Tools

CS Bridge

Intro CS in Istanbul

Purple Book

Online Exam Grading (Soon)

Blue Book

Secure Electronic Exams (Soon)

Pensieve

Students See Their Own Progress

Tiny Feedback

Understand Your Lectures

CS Website Maker

Style and Design for CS Pages

Karel Online

Proto Coding Online

Course Pods

Proto Inperson MOOCs


Data Visualization

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Code.org problem solving policy graph of learned policy for how to solve a single open ended programming assignment from over 1M users. Each node is a unique partial-solution (and node 0 is the correct answer)