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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models
Stephen MacNeil, Paul Denny, Andrew Tran, et al.
(2024), pp. 11-18
Open Access | Times Cited: 14

Showing 14 citing articles:

Patterns of Student Help-Seeking When Using a Large Language Model-Powered Programming Assistant
Brad E. Sheese, Mark Liffiton, Jaromír Šavelka, et al.
(2024), pp. 49-57
Open Access | Times Cited: 23
Desirable Characteristics for AI Teaching Assistants in Programming Education
Paul Denny, Stephen MacNeil, Jaromír Šavelka, et al.
(2024), pp. 408-414
Open Access | Times Cited: 22
Debugging with an AI Tutor: Investigating Novice Help-seeking Behaviors and Perceived Learning
Stephanie Yang, H. Zhao, Yudian Xu, et al.
(2024), pp. 84-94
Closed Access | Times Cited: 4
The Promise and Pitfalls: A Literature Review of Generative Artificial Intelligence as a Learning Assistant in ICT Education
Ritesh Chugh, Darren Turnbull, Ahsan Morshed, et al.
Computer Applications in Engineering Education (2025) Vol. 33, Iss. 2
Open Access
Integrating Small Language Models with Retrieval-Augmented Generation in Computing Education: Key Takeaways, Setup, and Practical Insights
Zezhu Yu, Suqing Liu, Paul Denny, et al.
(2025), pp. 1302-1308
Closed Access
BugSpotter: Automated Generation of Code Debugging Exercises
Victor-Alexandru P durean, Paul Denny, Adish Singla
(2025), pp. 896-902
Open Access
Can LLMs See What I See? A Study on Five Prompt Engineering Techniques for Evaluating UX on a Shopping Site
Sungjin Shin, Jeesun Oh, Sangwon Lee
(2025), pp. 1-7
Closed Access
Automating Personalized Parsons Problems with Customized Contexts and Concepts
Andre del Carpio Gutierrez, Paul Denny, Andrew Luxton-Reilly
(2024), pp. 688-694
Open Access | Times Cited: 2
Improving LLM Classification of Logical Errors by Integrating Error Relationship into Prompts
Yanggyu Lee, Suchae Jeong, Jihie Kim
Lecture notes in computer science (2024), pp. 91-103
Closed Access | Times Cited: 2
First Year CS Students Exploring And Identifying Biases and Social Injustices in Text-to-Image Generative AI
Mikko Apiola, Henriikka Vartiainen, Matti Tedre
(2024), pp. 485-491
Closed Access | Times Cited: 2
Navigating the Pitfalls: Analyzing the Behavior of LLMs as a Coding Assistant for Computer Science Students—A Systematic Review of the Literature
Farman Ali Pirzado, Awais Ahmed, Román Alejandro Mendoza-Urdiales, et al.
IEEE Access (2024) Vol. 12, pp. 112605-112625
Open Access | Times Cited: 2
Synthetic Students: A Comparative Study of Bug Distribution Between Large Language Models and Computing Students
Stephen MacNeil, Magdalena Rogalska, Juho Leinonen, et al.
(2024), pp. 137-143
Open Access | Times Cited: 2
Large Language Models are Catalyzing Chemistry Education
Yuanqi Du, Chenru Duan, Andres M. Bran, et al.
(2024)
Open Access | Times Cited: 1
Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
Niklas Humble
International Journal of Educational Technology in Higher Education (2024) Vol. 21, Iss. 1
Open Access
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