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Generative AI and large language models have the potential to drastically improve the landscape of computing education by automatically generating personalized feedback and content.
Karel the Robot: A Gentle Introduction to the Art of Programming
Richard E Pattis, Jim Roberts, and Mark Stehlik · 1995
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Scratch: Programming for All
Mitchel Resnick, John H. Maloney, Andrés Monroy-Hernández, Natalie Rusk, Evelyn Eastmond, Karen Brennan, Amon Millner, Eric Rosenbaum, Jay S. Silver, Brian Silverman, and Yasmin B. Kafai · 2009
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Intro to Programming with Karel the Dog
CodeHS · 2012
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Autonomously Generating Hints by Inferring Problem Solving Policies
Chris Piech, Mehran Sahami, Jonathan Huang, and Leonidas J. Guibas · 2015
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Hint Generation Under Uncertainty: The Effect of Hint Quality on Help-Seeking Behavior
Thomas W. Price, Rui Zhi, and Tiffany Barnes · 2017
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Programming Methodology (Spring 2018)
Stanford University’s CS106A · 2018
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Zero-shot Learning of Hint Policy via Reinforcement Learning and Program Synthesis
Aleksandr Efremov, Ahana Ghosh, and Adish Singla · 2020
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Synthesizing Tasks for Block-based Programming
Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, and Adish Singla · 2020
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Evaluating Large Language Models Trained on Code
Mark Chen et al · 2021
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Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming
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Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models
Sami Sarsa, Paul Denny, Arto Hellas, and Juho Leinonen · 2022
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GitHub Copilot: Your AI Pair Programmer
GitHub · 2022
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Hussein Mozannar, Gagan Bansal, Adam Fourney, and Eric Horvitz · 2022
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Is Github Copilot a Substitute for Human Pair-programming? An Empirical Study
Saki Imai · 2022
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Evaluating ChatGPT and GPT-4 for Visual Programming
Adish Singla · 2023
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Sparks of Artificial General Intelligence: Early Experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, and Yi Zhang · 2023
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Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning
David Baidoo-Anu and Leticia Owusu Ansah · 2023
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Generative AI and the Future of Education: Ragnarök or Reformation? A Paradoxical Perspective from Management Educators
Weng Marc Lim, Asanka Gunasekara, Jessica Leigh Pallant, Jason Ian Pallant, and Ekaterina Pechenkina · 2023
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Using Large Language Models to Enhance Programming Error Messages
Juho Leinonen, Arto Hellas, Sami Sarsa, Brent N. Reeves, Paul Denny, James Prather, and Brett A. Becker · 2023
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The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
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From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks
Adish Singla and Nikitas Theodoropoulos · 2022
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Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes
Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, and Adish Singla · 2022
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OpenAI
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Hour of Code: Classic Maze Challenge
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Code.org: Learn Computer Science
Code.org
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Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors
Tung Phung, Victor-Alexandru Pădurean, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, and Gustavo Soares
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Is AI the Better Programming Partner? Human-Human Pair Programming vs. Human-AI pAIr Programming
Qianou Ma, Tongshuang Wu, and Kenneth R. Koedinger · 2023
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Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks
Alperen Tercan, Ahana Ghosh, Hasan Ferit Eniser, Maria Christakis, and Adish Singla · 2023
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Neural Task Synthesis for Visual Programming
Victor-Alexandru Pădurean, Georgios Tzannetos, and Adish Singla · 2023
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