A Data-Driven Analysis of Informatively Hard Concepts in Introductory Programming

Author:

Wiegand R. Paul1,Bucci Anthony2,Kumar Amruth N.3,Albert Jennifer L.4,Gaspar Alessio5

Affiliation:

1. University of Central Florida, Orlando, FL, USA

2. Unaffiliated, Cambridge, MA, USA

3. College of New Jersey, Mahwah, NJ, USA

4. The Citadel, Charleston, SC, USA

5. University of South Florida, Tampa, FL, USA

Funder

NSF

Publisher

ACM

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using Benchmarking Infrastructure to Evaluate LLM Performance on CS Concept Inventories: Challenges, Opportunities, and Critiques;Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1;2024-08-12

2. Taking Stock of Concept Inventories in Computing Education: A Systematic Literature Review;Proceedings of the 2023 ACM Conference on International Computing Education Research V.1;2023-08-07

3. Coping With Scoping: Understanding Scope and Parameters;Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1;2023-06-29

4. An Empirical Analysis of Code-Tracing Concepts;Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1;2022-07-07

5. Identifying Informatively Easy and Informatively Hard Concepts;ACM Transactions on Computing Education;2022-03-31

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