Open AccessProceedings Article
Learning Program Embeddings to Propagate Feedback on Student Code
Chris Piech,Jonathan Huang,Andy Nguyen,Mike Phulsuksombati,Mehran Sahami,Leonidas J. Guibas +5 more
- pp 1093-1102
TLDR
A neural network method is introduced to encode programs as a linear mapping from an embedded precondition space to an embedded postcondition space and an algorithm for feedback at scale is proposed using these linear maps as features.Abstract:
Providing feedback, both assessing final work and giving hints to stuck students, is difficult for open-ended assignments in massive online classes which can range from thousands to millions of students. We introduce a neural network method to encode programs as a linear mapping from an embedded precondition space to an embedded postcondition space and propose an algorithm for feedback at scale using these linear maps as features. We apply our algorithm to assessments from the Code.org Hour of Code and Stanford University's CS1 course, where we propagate human comments on student assignments to orders of magnitude more submissions.read more
Citations
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Fret: Functional Reinforced Transformer With BERT for Code Summarization
TL;DR: A novel model called Fret is proposed, which stands for Functional REinforced Transformer with BERT, which provides a new way to generate code comments by learning code functionalities and deepening code understanding while alleviating the problem of long dependency.
Melford: Using Neural Networks to Find Spreadsheet Errors
TL;DR: This paper shows that applying neural networks to spreadsheets allows us to find an important class of error with high precision, and uses a spatial abstraction of the cells around a particular cell to build a classifier that predicts whether a cell should contain a formula whenever it contains a number.
Journal ArticleDOI
Using the Engagement Profile to Design an Engaging Robotic Teaching Assistant for Students
Martin Cooney,Wolfgang Leister +1 more
TL;DR: The findings suggest that using a social robot as a teaching assistant is promising using the chosen capabilities and Engagement Profile tool, and enhancing the robot’s autonomous capabilities and further investigating the role of embodiment are some important topics to be considered.
CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs
TL;DR: Two global context information are explored, namely intra-class and inter-class context information, and the model CoCoGUM: Contextual Code Summarization with Multi-Relational Graph Neural Networks on UMLs is proposed, which outperforms state-of-the-art methods.
Posted Content
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs
TL;DR: A novel framework that utilizes black-box function evaluations, in conjunction with symbolic expressions that define relationships between the given functions is presented, which generalizes significantly better to expressions of higher depth and is able to fill partial equations with valid completions.
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James Bergstra,Yoshua Bengio +1 more
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Proceedings Article
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Book
A complexity measure
TL;DR: In this paper, a graph-theoretic complexity measure for managing and controlling program complexity is presented. But the complexity is independent of physical size, and complexity depends only on the decision structure of a program.