Explanipedia

ReDefining Code Comprehension: Function Naming as a Mechanism for Evaluating Code Comprehension Open

David H. Smith, Max Fowler, Paul Denny, Craig Zilles · 2025

Counting the Trees in the Forest: Evaluating Prompt Segmentation for Classifying Code Comprehension Level Open

David H. Smith, Max Fowler, Paul Denny, Craig Zilles · 2025

Generating Planning Feedback for Open-Ended Programming Exercises with LLMs Open

Mehmet Arif Demirtaş, Claire Zheng, Max Fowler, Kathryn Cunningham · 2025

To complete an open-ended programming exercise, students need to both plan a high-level solution and implement it using the appropriate syntax. However, these problems are often autograded on the correctness of the final submission through…

Mining Hierarchies with Conviction: Constructing the CS1 Skill Hierarchy with Pairwise Comparisons over Skill Distributions Open

Dip Kiran Pradhan Newar, Max Fowler, David H. Smith, Seth Poulsen · 2024

Background and Context: Some skills taught in introductory programming courses are categorized into 1) explaining code, 2) arranging lines of code in correct sequence, 3) tracing through the execution of a program, and 4) writing code from…

Validating, Refining, and Identifying Programming Plans Using Learning Curve Analysis on Code Writing Data Open

Mehmet Arif Demirtaş, Max Fowler, N. Hu, Kathryn Cunningham · 2024

Prompting for Comprehension: Exploring the Intersection of Explain in Plain English Questions and Prompt Writing Open

David H. Smith, Paul Denny, Max Fowler · 2024

Learning to program requires the development of a variety of skills including the ability to read, comprehend, and communicate the purpose of code. In the age of large language models (LLMs), where code can be generated automatically, deve…

Explaining Code with a Purpose: An Integrated Approach for Developing Code Comprehension and Prompting Skills Open

Paul Denny, David H. Smith, Max Fowler, James Prather, Brett A. Becker , et al. · 2024

Reexamining Learning Curve Analysis in Programming Education: The Value of Many Small Problems Open

Mehmet Arif Demirtaş, Max Fowler, Kathryn Cunningham · 2024

[to appear in EDM 2024] Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. Knowledge components, units of knowledge that can be measured by p…

Explaining Code with a Purpose: An Integrated Approach for Developing Code Comprehension and Prompting Skills Open

Paul Denny, David H. Smith, Max Fowler, James Prather, Brett A. Becker , et al. · 2024

Reading, understanding and explaining code have traditionally been important skills for novices learning programming. As large language models (LLMs) become prevalent, these foundational skills are more important than ever given the increa…

Designing and Piloting a High School CS+X Topics Course Open

Kathleen Isenegger, Max Fowler, Yael Gertner, Raya Hegeman-Davis, Leonard Pitt · 2024

Racial and gender representation among computer science (CS) students continues to lag behind national demographics in the U.S. One way to improve students' interests in CS is to connect CS to other fields to expand students' perceptions o…

"\"I Don't Gamble To Make My Livelihood\": Understanding the Incentives For Open

Max Fowler, David H. Smith, Binglin Chen, Craig Zilles · 2023

Background: Prior work has primarily been concerned with identifying: (1) how Open Education Resources (OERs) can be used to increase the availability of educational materials, (2) what motivations are behind their adoption and usage in cl…

Am I Wrong, or Is the Autograder Wrong? Effects of AI Grading Mistakes on Learning Open

Tiffany Wenting Li, Silas Hsu, Max Fowler, Zhilin Zhang, Craig Zilles , et al. · 2023

Errors in AI grading and feedback often have an intractable set of causes and are, by their nature, difficult to completely avoid. Since inaccurate feedback potentially harms learning, there is a need for designs and workflows that mitigat…

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