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Background and Context. The increasing integration of large language models (LLMs) in computing education presents an emerging challenge in understanding how students use LLMs and craft prompts to solve computational tasks. Prior research…

A number of automated techniques and tools were proposed in the research literature over the years which aim to support the spreadsheet developer in the process of testing and debugging a faulty spreadsheet. One underlying assumption of…

Software Engineering · Computer Science 2015-03-12 Dietmar Jannach , Thomas Schmitz

Programs are a kind of communication to both computers and people, hence as students are trained to write programs they need to learn to write well-designed, readable code rather than code that simply functions correctly. The difficulty in…

Computers and Society · Computer Science 2022-11-08 J. Walker Orr

Blocking is a mechanism to improve the efficiency of Entity Resolution (ER) which aims to quickly prune out all non-matching record pairs. However, depending on the distributions of entity cluster sizes, existing techniques can be either…

Databases · Computer Science 2021-03-17 Sainyam Galhotra , Donatella Firmani , Barna Saha , Divesh Srivastava

Teaching proofs is a crucial component of any undergraduate-level program that covers formal reasoning. We have developed a calculational reasoning format and refined it over several years of teaching a freshman-level course, "Logic and…

Logic in Computer Science · Computer Science 2023-11-16 Andrew T. Walter , Ankit Kumar , Panagiotis Manolios

We present a new method for automatically providing feedback for introductory programming problems. In order to use this method, we need a reference implementation of the assignment, and an error model consisting of potential corrections to…

Programming Languages · Computer Science 2012-11-19 Rishabh Singh , Sumit Gulwani , Armando Solar-Lezama

Distributed computation is a framework used to break down a complex computational task into smaller tasks and distributing them among computational nodes. Erasure correction codes have recently been introduced and have become a popular…

Information Theory · Computer Science 2021-08-17 Royee Yosibash , Ram Zamir

When working on intelligent tutor systems designed for mathematics education and its specificities, an interesting objective is to provide relevant help to the students by anticipating their next steps. This can only be done by knowing,…

Artificial Intelligence · Computer Science 2020-03-02 Ludovic Font , Sébastien Cyr , Philippe R. Richard , Michel Gagnon

Gradient boosting is a prediction method that iteratively combines weak learners to produce a complex and accurate model. From an optimization point of view, the learning procedure of gradient boosting mimics a gradient descent on a…

Machine Learning · Computer Science 2022-11-30 Erwan Fouillen , Claire Boyer , Maxime Sangnier

We consider the problem of learning to perform a task from demonstrations given by teachers or experts, when some of the experts' demonstrations might be adversarial and demonstrate an incorrect way to perform the task. We propose a novel…

Machine Learning · Computer Science 2023-06-13 Prithviraj Dasgupta

Blocks-based programming has become the lingua franca for introductory coding. Studies have found that experience with blocks-based programming can help beginners learn more traditional text-based languages. We explore how blocks…

Programming Languages · Computer Science 2018-06-27 David Bau , Jeff Gray , Caitlin Kelleher , Josh Sheldon , Franklyn Turbak

Immediate feedback has been shown to improve student learning. In programming courses, immediate, automated feedback is typically provided in the form of pre-defined test cases run by a submission platform. While these are excellent for…

Proof Designer is a computer software program designed to help Mathematics students learn to write mathematical proofs. Under the guidance of the user, Proof Designer assists in writing outlines of proofs in elementary set theory. Proof…

History and Overview · Mathematics 2015-07-20 Moez A. AbdelGawad

In this contribution, we augment the metric learning setting by introducing a parametric pseudo-distance, trained jointly with the encoder. Several interpretations are thus drawn for the learned distance-like model's output. We first show…

Machine Learning · Computer Science 2020-08-17 Joao Monteiro , Isabela Albuquerque , Jahangir Alam , R Devon Hjelm , Tiago Falk

Students have enthusiastically taken to online programming lessons and contests. Unfortunately, they tend to struggle due to lack of personalized feedback when they make mistakes. The overwhelming number of submissions precludes manual…

Software Engineering · Computer Science 2016-03-16 Shalini Kaleeswaran , Anirudh Santhiar , Aditya Kanade , Sumit Gulwani

Providing feedback on programming assignments manually is a tedious, error prone, and time-consuming task. In this paper, we motivate and address the problem of generating feedback on performance aspects in introductory programming…

Programming Languages · Computer Science 2014-09-18 Sumit Gulwani , Ivan Radiček , Florian Zuleger

Software developers use metrics to evaluate code quality and productivity, but these practices are still rare in programming education. This project bridges the gap by collecting real-time learning analytics from individual student and…

Sequential testing problems involve a complex system with several components, each of which is "working" with some independent probability. The outcome of each component can be determined by performing a test, which incurs some cost. The…

Data Structures and Algorithms · Computer Science 2023-08-22 Rohan Ghuge , Anupam Gupta , Viswanath Nagarajan

An introductory programming course (CS1) is an integral part of any undergraduate curriculum. Due to large number and diverse programming background of students, providing timely and personalised feedback to individual students is a…

Computers and Society · Computer Science 2017-02-03 Rajdeep Das , Umair Z. Ahmed , Amey Karkare , Sumit Gulwani

The recently developed Distributed Block Proximal Method, for solving stochastic big-data convex optimization problems, is studied in this paper under the assumption of constant stepsizes and strongly convex (possibly non-smooth) local…

Optimization and Control · Mathematics 2020-03-06 Francesco Farina , Giuseppe Notarstefano